Applied Geography

Archive for the ‘Spatial Analysis’ Category

Spatial and Temporal Analysis of Congestion in Urban Transportation Networks

In GIScience, Modeling, Spatial Analysis, Temporal Analysis on September 2, 2010 at 6:46 am

Swiss Transport Research Conference, August 2010

Yuxuan Ji and Nikolas Geroliminis

“It has been recently shown that a macroscopic fundamental diagram (MFD) linking space-mean flow, density and speed exists in the urban transportation networks under some conditions. An MFD is further well defined if the network is homogeneous with links of similar properties. However many real urban transportation networks are heterogeneous with different levels of congestion. The objective of this paper is to study the existence of MFD and the feasibility of simple control strategies to alleviate the congestion in the heterogeneous networks, which can be partitioned into homogeneous components. To achieve these goals, this paper focuses on the clustering of transportation networks based on the spatial and temporal features of congestion. A partitioning mechanism, which consists of three consecutive algorithms, is designed to minimize the variance of link densities while maintaining the spatial compactness of the clusters. Small variance of link densities within a cluster increases the aggregated flow for the same average density and spatial compactness makes feasible the application of perimeter control strategies. Firstly, Normalized Cut is applied to over segment the network into several clusters and a new metric is introduced to evaluate the partitioning results. Secondly, a merging algorithm is developed to improve the metric and total variance of link densities, and the optimal number of clusters is estimated and determined. Finally, a boundary adjustment algorithm is designed to further improve the metric and decrease the variances of the clusters while keeping the compactness of the shapes. Both the objectives of smaller variances and spatial compactness can be achieved after this partitioning mechanism. The simulation further demonstrates the superiority of our method in both effectiveness and robustness compared with other clustering algorithms.”

Anchor Uncertainty and Space-time Prisms on Road Networks

In GIS, Spatial Analysis, Temporal Analysis on September 1, 2010 at 7:40 am

International Journal of Geographical Information Science, Volume 24, Issue 8 August 2010 , pages 1223 – 1248

Bart Kuijpers; Harvey J. Miller; Tijs Neutens; Walied Othman

“Space-time prisms capture all possible locations of a moving person or object between two known locations and times given the maximum travel velocities in the environment. These known locations or ‘anchor points’ can represent observed locations or mandatory locations because of scheduling constraints. The classic space-time prism as well as more recent analytical and computational versions in planar space and networks assume that these anchor points are perfectly known or fixed. In reality, observations of anchor points can have error, or the scheduling constraints may have some degree of pliability. This article generalizes the concept of anchor points to anchor regions: these are bounded, possibly disconnected, subsets of space-time containing all possible locations for the anchor points, with each location labelled with an anchor probability. We develop two algorithms for calculating network-based space-time prisms based on these probabilistic anchor regions. The first algorithm calculates the envelope of all space-time prisms having an anchor point within a particular anchor region. The second algorithm calculates, for any space-time point, the probability that a space-time prism with given anchor regions contains that particular point. Both algorithms are implemented in Mathematica to visualize travel possibilities in case the anchor points of a space-time prism are uncertain. We also discuss the complexity of the procedures, their use in analysing uncertainty or flexibility in network-based prisms and future research directions.”

Migrant Boats: A Geo-temporal Analysis and Visualization of Migrant Boats

In Social Science, Spatial Analysis, Temporal Analysis on September 1, 2010 at 7:26 am

University of British Columbia Computer Science Department project, Fall 2009

Anika Mahmud

“This particular paper tries to solve one of the mini challenges of VAST challenge 2008 where the task is to find the changing pattern of migrants using boat from Isla Del Sueno to Florida over three years. This paper focuses on geo-temporal analysis of the synthesis data and its visualization using info visualization technique.”

Spatial and Temporal Analysis of Forest Cover Changes in the Bartin Region of Northwestern Turkey

In Environmental Science, Imagery, Spatial Analysis, Temporal Analysis on September 1, 2010 at 7:18 am

African Journal of Biotechnology, Vol. 9 (35), pp. 5676-5685, 30 August 2010

Ayhan Atesoglu and Metin Tunay

“This study analyzed the changes in the forest areas in Bartin province of Turkey and the surrounding areas using remote sensing data and GIS techniques. Three Landsat Thematic Mapper (TM) images of the study region, recorded in 1987, 1992, and 2000, were utilized. The main land-use characteristics were derived using a maximum-likelihood classification technique. The remotely sensed data allows monitoring of current land use/land cover and detection of temporal changes. Furthermore, a temporal and spatial comparison of the classified image can be performed using Geographical Information System (GIS) to show land-use changes. GIS analysis of the classification results based on reference datasets revealed that the area covered by forests decreased significantly and that the amount of the reduction corresponded mainly to increased agricultural land use. The reasons for this negative impact on forested areas were growth in the region’s population, and expansion of agricultural areas and settlements. The classification results also showed that past, afforestation work had been successful.”

Research Explores Factors in Obesity

In GIS, Spatial Analysis on September 1, 2010 at 6:56 am

South Dakota State University researchers are using the tools of spatial analysis to explore nationwide data for insights on what influences obesity.

“We can identify and map some of these regions or ‘hotspots’ of high and low obesity,” said associate professor Michael Wimberly of SDSU’s Geographic Information Science Center of Excellence. “Ultimately what we want to do is explain what some of the drivers are.”

SDSU postdoctoral researcher Akihiko Michimi, who is working on the project with Wimberly, said one glaring regional difference is that the rate of obesity is high in much of the rural South United States, but low in the rural West and in New England states.

Michimi and Wimberly’s first journal article about the study appeared June 29 in the American Journal of Preventive Medicine.

The SDSU study set out to map spatial patterns of obesity and risk factors nationwide by using Behavioral Risk Factor Surveillance System data from telephone surveys compiled annually by the Centers for Disease Control and Prevention. The BRFSS data includes self-reported height and weight, as well as respondents’ answers to questions about their levels of physical activity, and about fruit and vegetable consumption.

“The advantage of using BRFSS compared to a variety of other data sources is that we can get wall-to-wall national coverage. They actually do sampling in every county across the United States,” Wimberly said. “So we can map things, first of all, and we can also use various spatial statistics to test hypotheses about what the environmental correlates of obesity, physical activity, fruit and vegetable consumption are at a national level as opposed to other studies that have been more localized.”

For example, the SDSU analysis shows that the rural South and parts of the Great Plains had low proportions of people who are physically active in their leisure time, while the rural West, New England, and the upper Midwest had high proportions.

When analyzing data for another factor — the proportion of adults consuming fruits and vegetables five times or more per day — researchers found the West Coast, New England and parts of the South had the highest proportions. But the Lower Mississippi Valley, the Great Plains and the Mid-Appalachian Mountain region had low proportions.

Michimi and Wimberly said a current idea in research is that factors in society can set up “obesogenic environments” that give rise to obesity — if factors discourage physical activity or encourage eating the wrong sorts of food, for example.

One of the angles they’re currently exploring in a follow-up study is the possibility that distance from supermarkets — a possible indicator of access to nutritious foods rather than highly processed, less healthful foods — could play a role.

SDSU’s preliminary analysis of data from the 48 contiguous United States showed that the probability of obesity increased with distance from supermarkets, while consumption of five or more servings of fruits and vegetables per day decreased. The research also showed clear differences between large metropolitan areas and sparsely populated rural areas.

“Sometimes people have to drive 25 or 30 miles to get to a supermarket or grocery store,” Michimi said. “But big cities on the East Coast or West Coast have a high population density. If they have a large number of people, they have a large number of stores. So the distance to the supermarkets in general is much, much shorter compared to the distances to the supermarkets on the Great Plains.”

Wimberly said there are no easy answers about what’s responsible for obesity. But analyzing it with the tools of geography could make some less obvious factors visible.

“The geographic perspective opens up a unique window. Looking at maps, people relate very intuitively to the patterns and it really catalyzes a lot of new thought, ideas, hypotheses. That’s the power of what we refer to as ‘exploratory spatial data analysis,’ working with the data using statistical techniques that allow us to tease out real spatial trends from the underlying noise and using that as a method for hypothesis generation. We can also pull multiple sources of data together to actually test hypotheses about the underlying relationships.”

The U.S. Department of Agriculture’s National Research Initiative funded the work through a grant from its Human Nutrition and Obesity Program.

[Source: South Dakota State University press release]

Bicycle Crash Casualties in a Highly Motorized City

In Social Science, Spatial Analysis on August 31, 2010 at 7:25 am

Accident Analysis and Prevention, 2010; 42(6): 1902-1907

Loo BP, Tsui KL

“The characteristics of bicycle crashes in cities where bicycles are a minor transport mode have received little attention in road safety research. However, the characteristics of these injury-inflicting bicycle crashes are expected to be very different from those happening in cities where cycling is generally considered as one of the major transport modes. Specifically, this study has the following three objectives: (1) to conduct the first scientific spatial analysis of bicycle crashes in Hong Kong; (2) to analyze the circumstances leading to bicycle crashes; and (3) to conduct an epidemiological study on injury patterns of cyclist casualties. Various spatial and statistical tools, including buffer analysis, chi-square tests, analysis-of-variance and binary logistic regression, are used to analyze the bicycle crashes in Hong Kong from 2005-2007. An important finding of this paper is that the bicycle safety problem has a clear spatial dimension. The crash circumstances in different parts of the city differed systematically. Furthermore, the findings suggest that initiatives to develop new cycle tracks and to encourage bicycles as a transport mode must be planned carefully with new infrastructure and policies to ensure the safety of cyclists.”

Learn to Conduct Network-Based Spatial Analysis

In ESRI, Education, GIS, Spatial Analysis on August 31, 2010 at 7:13 am

Free Esri Training Will Show How ArcGIS Network Analyst Solves Routing and Location Problems

An upcoming live training seminar will demonstrate how Esri’s ArcGIS Network Analyst technology can answer logistics and other questions such as: What is the quickest and most cost-effective way for a fleet of trucks to deliver 300 packages in one day? Where should a fire station be opened to ensure fast response time to a new residential development?

How many customers can reach a specific store or restaurant within five minutes?

To learn how to use the software extension, tune in to Using Network Analyst in ArcGIS Desktop 10 on Thursday, September 2, 2010. This seminar will air on www.esri.com/lts at 9:00 a.m., 11:00 a.m., and 3:00 p.m. (Pacific daylight time).

ArcGIS Network Analyst helps users conduct network-based spatial analysis such as calculating drive times, defining service areas, and completing optimum route and shortest path analyses.

Seminar attendees will learn how to

  • Solve problems where network travel time or costs must be minimized.
  • Work with time windows, curb approach restrictions, and other constraints.
  • Find the best routes between multiple locations.
  • Find the best set of routes for a fleet of vehicles.
  • Find the optimal location for a new facility to minimize overall travel time or costs.

This seminar will be of interest to geographic information system (GIS) analysts, managers, dispatchers, planners, or researchers who want to use ArcGIS Desktop or ArcGIS Server to do distance-based analysis where distance or travel time is measured on transportation networks.

A broadband Internet connection and an Esri Global Account are needed to participate in the training seminar. Creating a global account is easy and free: visit www.esri.com/lts, click Login, and register your name and address. A few weeks after the live presentation, this seminar will be archived and available for viewing on the Esri Training Web site.

[Source: Esri press release]

University of Florida Researchers to Document Boating Patterns; Could Aid Endangered Whales

In Environmental Science, GIS, Spatial Analysis on August 31, 2010 at 7:04 am

One of the world’s most endangered whale species makes its way south every winter to give birth in waters near northeast Florida and southeast Georgia.

During that trip, North Atlantic right whales face two major threats: fishing gear and boats.

University of Florida researchers are embarking on a two-year study that is the first attempt to map boating traffic patterns in the northeast Florida area.

Mapping those patterns could, in turn, allow whale managers to better focus outreach efforts and more accurately assess the effects of future marine-related projects on protected species.

The UF researchers, Bob Swett and Charles Sidman, will use geographic information system, or GIS, technology to better understand boater travel patterns off the coasts of St. Johns, Duval and Nassau counties. The work will begin with boater surveys, answering questions about their usual routes and seasonal boating habits.

The researchers will also take to the air to log positions and characteristics of recreational boats. Then, all of the information will become part of a graphic representation that will help managers and policy makers understand what’s happening in area waterways.

“Once you have the patterns, you can start comparing them to the known sightings of right whales—to find the hotspots, if you will,” said Sidman, associate director for research for Florida Sea Grant, a UF-hosted ocean and coastal science program that works closely with UF’s Institute of Food and Agricultural Sciences.

Swett, a GIS expert, is an associate professor in UF’s school of forest resources and conservation. He also coordinates the Florida Sea Grant Boating and Waterway Management Program.

Somewhere between 325 and 400 whales remain of the species that was hunted nearly to extinction by 18th- and 19th-century whalers.

It’s been illegal to hunt right whales since 1935, but vessel strikes and fishing gear entanglement continue to be a threat to the creatures, which can grow 55 feet long and weigh 70 tons.

The whales typically arrive off the Florida-Georgia coast in December and stay until early spring, said Barb Zoodsma, a biologist with the National Oceanographic and Atmospheric Administration who coordinates right whale recovery efforts in the Southeast. NOAA is funding the $246,000 study.

Awareness among recreational boaters about right whales is not as high as it could be, she said, and the whales are more frequently seen bearing scars from collisions with boat-engine propellers.

Although rules state that boaters must keep well away from right whales, captains she’s spoken with after collisions said they never saw the animal before impact.

“From what captains have described to me, the impact is so tremendous that at first, they thought they’d hit a large container that had fallen off a ship,” she said. “So it’s not just about protecting the whales, it’s a boater-safety issue, too.”

[Source: University of Florida press release]

Spatial Analysis of Soil Water Balance in an Agricultural District of Southern Italy

In Environmental Science, Modeling, Spatial Analysis on August 30, 2010 at 10:40 am
Crop Modeling and Decision Support, 2009, 282-290

D. Ventrella, E. D. Giacomo, L. Giglio, M. Castellini and D. Palumbo

“An efficient management of water resources is considered very important for Italy and in particular for Southern areas characterized by a typical Mediterranean climate in order to improve the economical and environmental sustainability of the agricultural activity. The purpose of this study is to analyze the components of soil water balance in an important district of 110 Km2 situated in the Ionical coastal area of Southern Italy and mainly cropped with horticultural crops. The study was performed by using the spatially distributed and physically based model SIMODIS in order to individuate the best irrigation management maximizing the water use efficiency and minimizing water losses by deep percolation and soil evaporation. SIMODIS was applied for 24 soil types distributed in 96 cadastral units for three years characterized by low, normal and high spring summer rainfall. Water melon cultivation was simulated adopting three water supply managements: rainfed and two irrigation strategies based on ➀ soil water availability and ➁ plant water status adopting a threshold daily stress value. For each year and management, several water management indicators were calculated and mapped in GIS environment. For seasonal irrigation depth, actual evapotranspiration and irrigation efficiency, the cumulative distribution functions were also determined. The analysis allowed to individuate the areas particularly sensitive to water losses by deep percolation because of their hydraulic functions characterized by low water retention and large values of saturated hydraulic conductivity. For these areas, the irrigation based on plant water status caused very high water losses by drainage. At the contrary, the irrigation scheduled on soil base allowed to control better this component of soil water balance. SIMODIS resulted a useful tool to analyse the soil water balance at spatial scale and to support the local irrigation authority for planning the irrigation water distribution not only for economical and productive purposes but also for minimizing the pollution risks of deep soil and groundwater resources.”

More information

A Method for Quantifying Stream Network Topology over Large Geographic Extents

In Environmental Science, Modeling, Spatial Analysis on August 30, 2010 at 7:03 am

Journal of Spatial Hydrology, Vol.10, No.1 Spring 2010

R. Betz, N.P. Hitt, R.L. Dymond and C.D. Heatwole

“An understanding of stream network topology is necessary for a landscape-level perspective of stream hydrology and ecology. We present a method for quantifying stream network topology that overcomes computational constraints of DEM-based analysis over large geographic extents. This method converts vector stream flow paths to raster flow paths to predict spatially-explicit stream properties from a network-constrained upstream cell count (UCC) to flow origins. UCC data enable calculations of stream network structure at designated grain sizes and spatial extents. UCC values were strongly related to empirical measures of upstream basin area (R2 = 0.94) and stream width (R2 = 0.65) within the mid-Atlantic highlands, USA, suggesting that UCC data provide a reasonable surrogate for empirical measures of stream size within the stream network. By reducing raster grids to the flow path, the UCC method reduced file sizes by 99% compared to digital elevation models. The UCC method can improve our understanding of fluvial landscape hydrology and ecology by enabling spatial analysis of stream networks over large geographic extents.”

Weevils in the Landscape: Using Spatial Analysis to Identify Potential Areas of Non-target Feeding by Introduced Biological Control Organisms

In Environmental Science, GIS, Spatial Analysis on August 27, 2010 at 6:53 am

Entomological Society of America Annual Meeting, 9-12 December 2007

Greg Wiggins, Jerome Grant, Paris Lambdin, John Wilkerson, and Jack Ranney

“Despite their usefulness in integrated pest management programs, concern that many introduced biological control agents will eventually begin using non-target species and detrimentally impact native populations is growing. The efficacy of two weevils (Rhinocyllus conicus and Trichosirocalus horridus) introduced in the U.S. against the Eurasian musk thistle (Carduus nutans) is countered by their impact on some native Cirsium thistles. Non-target feeding of these weevils may impact plant reproduction and plant populations. Because the biologies of these weevils are closely linked with musk thistle, the distribution of musk thistle populations may influence non-target activity. The use of geographic information systems (GIS) could be useful in analyzing the spatial relationships among musk thistle, weevil and native thistles by characterizing suitable habitats for each thistle species over a large spatial scale. In Spring 2004 a four-year study was initiated to: 1) characterize habitats where exotic thistles and native thistles can occur and 2) identify potential areas of non-target feeding using spatial analysis. The study area (ca. 4,800 km2) for the spatial analysis consisted of four counties in eastern Tennessee. Two native thistles (C. carolinianum and C. discolor) and two introduced thistles (C. nutans and C. discolor) were selected as model species, and thistle population localities documented from 2005 through 2007 were used to generate the model. Mahalanobis distance was used to identify suitable habitats for each thistle species. Other spatial data used to generate the models, model testing procedures and results and applications of these spatial analyses will be discussed.”

Interactive Spatial Analysis of Lineaments

In GIScience, Spatial Analysis, Statistics on August 26, 2010 at 9:09 am

Computers & Geosciences, Volume 36 , Issue 8 (August 2010)

Thushan Chandrasiri Ekneligoda and Herbert Henkel

“An interactive software tool, here called Spatial Analysis of Lineaments (SAL), has been developed for calculating the spatial properties azimuth, length, spacing, and unidirectional frequency of lineaments which are defined by their start and end coordinates. In a series of steps the user is guided by displays of relevant statistical distributions, which can be user designed. Statistical outliers can be excluded and the total sample of lineaments can be subdivided into azimuth sets and, if required, into spatial clusters. Special attention is given to the removal of spatial outliers in an interactive way. Several rule-based decisions are made to determine the nearest lineament in the spacing calculation. As a default procedure, the program defines a window whose size depends on the mode value of the length distribution of the lineaments in the study area. The software can accept a large amount of lineaments and can analyze the spatial properties of each azimuth set avoiding the repetitive calling of the original database. A simple rule was developed to derive the unidirectional lineament frequency. The spatial properties are presented as histograms for each azimuth set together with the mode, mean, standard deviation, and number of involved lineaments.”

Online Forum Asks if GIS Can Bring Choice Back into a “One Size Fits All” Retail Landscape

In ESRI, GIS, Spatial Analysis on August 25, 2010 at 8:06 am

Locating Business Intelligently Is Topic of Spatial Roundtable

Simon Thompson, director of global business solutions, Esri, asks retailers to raise the bar and start reflecting local flavors and themes in the stores they open. “On my last drive across Kansas, it wasn’t the wheat fields or the flatness that amazed me but the repetitive retail landscape,” Thompson explains. “It seemed that every small town was a clone of the one I had just left—the same restaurant chains, grocers, drugstores, and general merchants.”

Thompson asks those with an opinion to share their insight on the current “one size fits all” retail landscape via Spatial Roundtable, a forum sponsored by Esri to discuss important topics. Can retailers use location intelligence through geographic information system (GIS) technology and data to discover the differences between each town and city? Can we use this information to give these communities what they need to satisfy customer demand, create vibrant communities, and thrive? Or do we give in to, as Thompson describes it, “the Wicked Witch of the Great Recession”?

Spatial Roundtable is designed for industry thought leaders to share their points of view about concerns, trends, challenges, and technologies. Participants in the online Spatial Roundtable discussion include the main contributor, who initiates the discussion, and invited topic-expert guests. Site visitors may also add comments. Topics remain open for discussion for 6 weeks. Archived topics are accessible for 24 months.

Visit www.spatialroundtable.com.

[Source: Esri press release]

Common Errors in Disease Mapping

In GIS, Spatial Analysis, Statistics, Temporal Analysis on August 23, 2010 at 6:33 am

Geospatial Health, Volume 4, Number 2, May 2010, Pages 139-154

Ricardo Ocaña-Riola

“Many morbid-mortality atlases and small-area studies have been carried out over the last decade. However, the methods used to draw up such research, the interpretation of results and the conclusions published are often inaccurate. Often, the proliferation of this practice has led to inefficient decision-making, implementation of inappropriate health policies and negative impact on the advancement of scientific knowledge. This paper reviews the most frequent errors in the design, analysis and interpretation of small-area epidemiological studies and proposes a diagnostic evaluation test that should enable the scientific quality of published papers to be ascertained. Nine common mistakes in disease mapping methods are discussed. From this framework, and following the theory of diagnostic evaluation, a standardised test to evaluate the scientific quality of a small-area epidemiology study has been developed. Optimal quality is achieved with the maximum score (16 points), average with a score between 8 and 15 points, and low with a score of 7 or below. A systematic evaluation of scientific papers, together with an enhanced quality in future research, will contribute towards increased efficacy in epidemiological surveillance and in health planning based on the spatio-temporal analysis of ecological information.”

A Geographical Information System-based Analysis of Cancer Mortality and Population Exposure to Coal Mining Activities in West Virginia, United States of America

In Environmental Science, GIS, Spatial Analysis on August 19, 2010 at 6:36 am

Geospatial Health, Volume 4, Number 2, May 2010, Pages 243-256

Michael Hendryx,  Evan Fedorko,  Andrew Anesetti-Rothermel

“Cancer incidence and mortality rates are high in West Virginia compared to the rest of the United States of America. Previous research has suggested that exposure to activities of the coal mining industry may contribute to elevated cancer mortality, although exposure measures have been limited. This study tests alternative specifications of exposure to mining activity to determine whether a measure based on location of mines, processing plants, coal slurry impoundments and underground slurry injection sites relative to population levels is superior to a previously-reported measure of exposure based on tons mined at the county level, in the prediction of age-adjusted cancer mortality rates. To this end, we utilize two geographical information system (GIS) techniques – exploratory spatial data analysis and inverse distance mapping – to construct new statistical analyses. Total, respiratory and “other” age-adjusted cancer mortality rates in West Virginia were found to be more highly associated with the GIS-exposure measure than the tonnage measure, before and after statistical control for smoking rates. The superior performance of the GIS measure, based on where people in the state live relative to mining activity, suggests that activities of the industry contribute to cancer mortality. Further confirmation of observed phenomena is necessary with person-level studies, but the results add to the body of evidence that coal mining poses environmental risks to population health in West Virginia.”

Call For Papers: IJAGR Special Issue on Spatial and Temporal Data Analysis

In GIS, Imagery, Modeling, Spatial Analysis, Temporal Analysis, Visualization on August 18, 2010 at 9:31 am

The Spatial Analysis and Modeling (SAM) Specialty Group of the Association of American Geographers (AAG) is currently soliciting research papers to be published in a special issue of International Journal of Applied Geospatial Research (IJAGR). We specifically look for papers that illustrate recent advances in spatial and temporal data analysis to address geographical issues, as well as related research in spatial data mining. Authors who are interested in contributing to the special issue should submit a letter of intent that describes the main content of paper by September 15, 2010. The guest editors will decide if the paper fits the scope of the special issue and invite the authors of selected papers to submit a full paper by January 15, 2011.

Many geographic phenomena occur in both space and time. Methods for spatial and temporal analyses have been increasingly important for spatial studies due to the rich datasets that have been made available for a wide range of applications. These methods are essential in applications such as spatial patterns of traffic accidents, infant mortality variations, landscape pattern changes, and unemployment rate changes, often over multiple time periods. We welcome papers in all relevant research areas including, but not limited to, transportation, urban and environment planning, crime, health, economics, statistics, and GIS.

This special issue aims at introducing the spatial and temporal data analysis to the GIScience/SAM/IJAGR audience.

Topics to be discussed in this special issue include (but are not limited to) the following:

  • Applications of tools such as GIS or remote sensing for space-time analysis
  • Multilevel modeling
  • Panel/Longitudinal data analysis
  • Space and time model
  • Space-time analyses
  • Space-time clusters
  • Spatial data mining
  • Spatial variation in temporal trends
  • Spatio-temporal processes
  • Spatio-temporal representation/geovisualization

Researchers and practitioners who are interested in contributing to the special issue should submit a letter of intent that describes the main content of paper by September 15, 2010. The guest editors will decide if the paper fits the scope of the special issue and invite the authors of selected papers to submit full papers for this special theme issue on Spatial and Temporal Data Analysis on or before January 15, 2011. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/development/author_info/guidelines submission.pdf. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:

Changjoo Kim (changjoo.kim@uc.edu)
Eric Delmelle (Eric.Delmelle@uncc.edu)
Ningchuan Xiao (xiao.37@osu.edu)
Guest Editors

Spatio-temporal Crime Prediction Model Based on Analysis of Crime Clusters

In GIS, Social Science, Spatial Analysis, Statistics, Temporal Analysis on August 18, 2010 at 6:41 am

Master’s Thesis,  Middle East Technical University, September 2007

Esra Polat

“Crime is a behavior disorder that is an integrated result of social, economical and environmental factors. In the world today crime analysis is gaining significance and one of the most popular subject is crime prediction. Stakeholders of crime intend to forecast the place, time, number of crimes and crime types to get precautions. With respect to these intentions, in this thesis a spatio-temporal crime prediction model is generated by using time series forecasting with simple spatial disaggregation approach in Geographical Information Systems (GIS).

“The model is generated by utilizing crime data for the year 2003 in Bahçelievler and Merkez Çankaya police precincts. Methodology starts with obtaining clusters with different clustering algorithms. Then clustering methods are compared in terms of land-use and representation to select the most appropriate clustering algorithms. Later crime data is divided into daily apoch, to observe spatiotemporal distribution of crime.

“In order to predict crime in time dimension a time series model (ARIMA) is fitted for each week day, Then the forecasted crime occurrences in time are disagregated according to spatial crime cluster patterns.

“Hence the model proposed in this thesis can give crime prediction in both space and time to help police departments in tactical and planning operations.”

A Spatially Explicit Habitat Model for the King Rail, Rallus Elegans, in Agricultural Wetlands

In Environmental Science, GIS, Modeling, Spatial Analysis on August 12, 2010 at 9:40 am

95th Ecological Society of America (ESA) Annual Meeting, Pittsburgh, PA, 01-06 August 2010

Bradley A. Pickens

“Background/Question/Methods: The southwest Louisiana rice agricultural region is critical for millions of wintering, migratory, and breeding waterbirds. Wetland birds of concern include a variety of secretive marsh birds, wading birds, shorebirds, wintering and breeding ducks, and cranes. Land use conversions and invasive species threaten wetland birds by reducing available rice habitat in the region. Yet, priority areas for wetland bird conservation have not been identified, and the spatial pattern of habitat variables on the landscape was also unknown. Our objective was to develop a spatially explicit habitat suitability model for the king rail, Rallus elegans, a secretive marsh bird of high conservation concern. We used geographic information systems (GIS) and readily available GIS data to build a habitat model to identify priority king rail habitat and to identify potential threats to the bird in southwest Louisiana. The habitat model was derived from GIS data layers of ditches/streams, rice density, and canopy cover. Canopy cover and ditches were previously found to be associated with king rails at a localized spatial scale, however our broad-scale spatial analysis included these variables measured within a 1-km radius of each cell.

“Results/Conclusions: We developed an empirical model based on presence/absence data obtained from call-back bird surveys in rice fields from 2007-2009. We used 50% of the data as training data for a logistic regression habitat model and used the other 50% of the data to validate the model. The analysis was conducted by using a receiver operating characteristic (ROC) statistic, and the results showed the model successfully distinguished the presence and absence of king rails on the landscape. The combination of canopy cover and ditches measured at a 1-km scale were important in predicting king rail presence/absence. The results also emphasized the importance of the southern parishes in southwest Louisiana for supporting a large king rail population. Recently, these parishes have been rapidly losing rice fields due to salt water intrusion and invasive woody species, posing a substantial threat to king rails in the region. This regional landscape approach can inform land use decisions and conservation programs in the region.”

Spatio-temporal Analysis of Precipitation and Temperature Distribution over Turkey

In Environmental Science, Geography, Spatial Analysis, Statistics, Temporal Analysis on August 12, 2010 at 7:08 am

ISPRS XXXVIII

P. A. Bostan and Z. Akyürek

“In this study, mean annual precipitation and temperature values observed at 225 meteorological observations over Turkey are used to disclose spatial distribution of mean annual precipitation and temperature values. Data components were obtained from the Turkish State Meteorological Service for 34 years period (1970-2003). The basic objectives of the study are: to infer the nature of spatial variation of precipitation and temperature over Turkey based on meteorological observations and to model the pattern of variability of these data components by using secondary variables extracted from SRTM and river network. Modeling the spatial distribution of data sets is implemented with Co-kriging (COK), Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) techniques with using secondary variables such as elevation, aspect, distance to river, roughness, drop (elevation differences between station and grid), sdgrid (standard deviation of 5*5 km grid), and plan-profile curvature. Correlations among the listed variables were analyzed and highly correlated ones were removed from the analysis. The study found a presence of high spatial non-stationary in the strength of relationships and regression parameters. The co-kriging interpolation method gave strong relationship for temperature (r2= 0.823) but comparatively weak relationship for precipitation (r2= 0.542). OLS method resulted with lower relationships for temperature (r2= 0.68) and for precipitation (r2= 0.3). The highest adjusted r2 values were obtained with GWR method; 0.96 for temperature and 0.66 for precipitation.”

An Iconography-Based Modeling Approach for the Spatio-Temporal Analysis of Architectural Heritage

In Social Science, Spatial Analysis, Temporal Analysis on August 11, 2010 at 7:09 am

2010 Shape Modeling International Conference, Aix en Provence, France, 21-23 June 2010

Livio De Luca, Chawee Busarayat, Chiara Stefani, Noemie Renaudin, Michel Florenzano, and Philippe Véron

“The study of historic buildings is usually based on the collection and analysis of iconographic sources such as photographs, drawings, engravings, paintings or sketches. This paper describes a methodological approach to make use of the existing iconographic corpus for the analysis and the 3D management of building transformations. Iconography is used for different goals. Firstly, it’s a source of geometric information (image-based-modeling of anterior states); secondly, it’s used for the re-creation of visual appearance (image-based texture extraction); thirdly it’s a proof of the temporal distribution of shape transformations (spatio-temporal modeling); finally it becomes a visual support for the study of building transformations (visual comparison between different temporal states). The aim is to establish a relation between the iconography used for the hypothetical reconstruction and the 3D representation that depends on it. This approach relates to the idea of using 3D representations like visualization systems capable of reflecting the amount of knowledge developed by the study of a historic building.”

Vulnerability Assessment of Water Resources to Climate Change Using GIS

In Climate Change, GIS, Spatial Analysis, Temporal Analysis on August 11, 2010 at 6:59 am

2010 ESRI International User Conference, San Diego, CA

Guishan CUI, Sang-chul LEE, Woo-Kyun LEE, and Ji-woong CHUNG

“Climate change has influenced on various environmental and social sectors. Especially, it has significant impact on water resource, such as drought and flood. In this study, we assessed the flood and drought vulnerability to climate change using GIS-based spatio-temporal information. Vulnerability is assessed in terms of sensitivity, exposure and adaptation. We prepared criteria and indicators for climate change impact assessment to flood and drought, and integrated GIS based data which is correspondent to indicators. As a result, we mapped flood and drought vulnerability and suggested adaptation strategies in Korea. South-eastern region of Korea is likely to be vulnerable to flood. And central-western region of Korea is vulnerable to drought.”

Spatio-temporal Analysis of Pneumonia and Influenza Hospitalizations in Ontario, Canada

In Spatial Analysis, Temporal Analysis on August 10, 2010 at 6:29 am

Geospatial Health 2(2), 2008, pp. 191-202

Eric J. Crighton, Susan J. Elliott, Pavlos Kanaroglou, Rahim Moineddin, and Ross E.G. Upshur

“Pneumonia and influenza represent a significant public health and health care system burden that is expected to increase with the aging of developed nations’ populations. The burden of these illnesses is far from uniform however, with recent studies showing that they are both highly spatially and temporally variable. We have combined spatial and time-series analysis techniques to examine pneumonia and influenza hospitalizations in the province of Ontario, Canada, to determine how temporal patterns vary over space, and how spatial patterns of hospitalizations vary over time. Knowledge of these patterns can provide clues to disease aetiology and inform the effective management of health care system resources. Spatial analysis revealed significant clusters of high hospitalization rates in northern and rural counties (Moran’s I = 0.186; P <0.05), while county level time series analysis demonstrated significant upward trends in rates in almost a quarter of the counties (P <0.05), and significant seasonality in all but one county (Fisher-Kappa and Barlett Kolmogorov Smirnov tests significant at the level P <0.01). Areas of weak seasonality were typically seen in rural areas with high rates of hospitalizations. The highest levels of spatial clustering of pneumonia and influenza hospitalizations were found to occur in months when rates were lowest. The findings provide evidence of spatio-temporal interaction over the study period, with marked spatial variability in temporal patterns, and temporal variability in spatial patterns. Results point to the need for the effective allocation of services and resources based on regional and seasonal demands, and more regionally focused prevention strategies. This research represents an important step towards understanding the dynamic nature of these illnesses, and sets the stage for the application of spatio-temporal modelling techniques to explain them.”

Spatial Analysis of Mixed-conifer Seedling Dispersal in Contrasting Regeneration Environments

In Environmental Science, Spatial Analysis on August 9, 2010 at 2:06 pm

95th Ecological Society of America (ESA) Annual Meeting, Pittsburgh, PA, 01-06 August 2010

Seth W. Bigelow and Michael J. Papaik

“Background/Question/Methods: Mixed-conifer forests of the Sierra Nevada underwent a marked shift to dominance by shade-tolerant trees during the 20th century, but the concomitant emergence of a disturbance regime of large high-intensity fires may now provide opportunities for establishment of shade-intolerant pine species. We assessed conifer seedling establishment in stem-mapped tree stands representing three regeneration environments: isolated remnant patches nine yr after high-intensity fire, contiguous stands nine yr after low-intensity wildfire, and silvicultural openings ~1 ha in size. We asked how seedling density varied as function of distance from parent tree, and how seedling establishment varied among substrate type (e.g., conifer litter compared to bare soil), and how substrate availability varied among regeneration environments. Seedling density was estimated as a function of distance from parent tree and substrate favorability, assuming a log-normal dispersal curve.

“Results/Conclusions: Only ponderosa pine and white fir were sampled in sufficiently high numbers to allow estimation of dispersal parameters. Modal ponderosa pine dispersal distance was 45 m, almost twice the distance of white fir. Ponderosa pine seedling distribution was narrowly clustered around the modal dispersal distance, possibly because of dispersal limitation from large seed size. White fir, which has smaller seeds, maintained high dispersion densities at relatively long distances from individual trees. Ponderosa pine seedlings established preferentially in areas of high herbaceous cover, and white fir preferred bare soil. Conifer litter was the most common substrate by a wide margin in all regeneration environments, and even though it was not the most favorable substrate for either species it accounted for a high proportion of seedling occurrences. Group selection openings had a larger proportion of bare soil than the other environments (25% of soil surface vs. 12-15% in burned areas), which was associated with dense white fir regeneration. We conclude that adequate regeneration of the shade-intolerant ponderosa pine was occurring in group-selection openings, but insufficient natural regeneration of pine was occurring in the post-fire environments to effect substantial change in relative abundance of shade-intolerant species.”

Geographic and Temporal Analysis of Folate-Sensitive Fetal Malformations

In Spatial Analysis, Temporal Analysis on August 9, 2010 at 7:51 am

Reproductive Science: Journal of the Society for Gynecologic Investigation, July 2003 10: 298-301

Trent E. J. Gordon, MS, Elizabeth A. Leeth, MS, Cynthia J. Nowinski, MD, Scott N. MacGregor, DO, Michelle Kambich, MS, and Richard K. Silver, MD

“Objective: To identify potential geographic and temporal clustering of folate-sensitive fetal malformations as a prelude to a targeted preconception curriculum in folic acid supplementation.

“Methods: Our comprehensive prenatal anomaly database was queried to select fetal malformations presumed to be sensitive to preconception folate insufficiency. Evidence of geographic clustering was evaluated by distribution of individual cases using zip codes of matermal residence. Potential temporal clustering of anomalies was sought by tabulating the frequency of each anomaly category during 5 consecutive 2-year intervals between 1992 and 2001.

“Results: Over a 10-year period, approximatley 2000 fetal anomalies were identified, of which 400 (20%) were considered potentially folate sensitive. We found geographic clustering of ventral wall defects as well as obstructive uropathy by zip code analysis. Significant increases in the frequencies of cardiac defects (P < .001) and obstructive uropathy (P < .001) were noted during the epoch of this study. A moderate increase in anomaly frequency was also seen in the diagnostic subcategory of gastroschisis, in which 15 of 27 total gastroschisis cases occurred in 2000-2001.

“Conclusion: Geographic clustering and temporal trends in anomally rates were noted in certain folate-sensitive malformation categories. Identification of specific, high-incidence regions may provide an opportunity for targeted interentions designed to supplement the national folic acid campaign.”

Urban Road Network Accessibility Evaluation Method base on GIS Spatial Analysis Techniques

In GIS, Social Science, Spatial Analysis on August 9, 2010 at 7:04 am

Proceedings, URISA XXXVIII

Hu Weiping and Wu Chi

“The urban road network plays a key role in the urban spatial structure. It is the main city social-economy activities and transportation carrier. Today, more and more researchers pay attention on road network. One of the most important problems is how to evaluate the accessibility of road network. This paper tries to discuss it. Firstly, road accessibility concept and some appraisal methods are discussed. Then, the spatial analysis method on road network assessment has established based on the GIS spatial analysis technology, some urban road network accessibility evaluation models are built up. The models use ESRI Corporation’s ArcGIS Engine components and Microsoft Corporation. Net Framework, and focus on the road network connectivity, the shortest travel time and the weighted average travel time. The paper presented three main road network accessibility evaluating indicators, introduced theory basis of the model construction in detail, and the model construction process. Taking Foshan city as an example, the models were tested using the urban road network data. Finally, further urban road network accessibility evaluation models are discussed.”

Post-harvest Mortality in Selection-managed Northern Hardwoods: A Spatial Analysis of Edge Effects

In Environmental Science, Spatial Analysis on August 6, 2010 at 8:07 am

95th Ecological Society of America (ESA) Annual Meeting, Pittsburgh, PA, 01-06 August 2010

Michael M. Fuller, Fraser H. Smith, and Sean C. Thomas

“Background/Question/Methods: Selection management, which maintains an uneven-aged stand structure and high canopy cover, has been promoted as an ecologically sustainable form of forest management. Although retention harvesting may immediately preserve integral forest structural characteristics, adequate evaluation of stand responses will determine the success or failure of such treatments. In previous work, we quantified a temporal spike in stem mortality following retention harvest. While the mechanisms underlying this increase in post-harvest mortality (PHM) are generally understood, the patterns of mortality are unclear, particularly in operational stands. Here we analyzed the influence of the cut block edge on the rate and spatial pattern of PHM for four different mortality classes in Yukon boreal forest. The different mortality classes relate closely to specific mechanisms by which stems die, such as by wind throw and fungal attack. Using 20m radius sample plots set along the forest edge of retention plots, we computed the frequency and spatial-dependency of mortality for each class.

“Results/Conclusions: Distance from the edge of the cut block influenced the rate of mortality for stems located within intact forest along the boundary of retention plots. The rate of mortality differed among the four mortality classes, suggesting that the mechanisms influencing PHM are spatially heterogeneous. Our results indicate that efforts to mitigate the negative impacts of selection management can be improved by recognizing how the major drivers of PHM change with the spatial proximity, and possibly the shape characteristics, of the cut block edge.”

Spatial Cluster Analysis of Early Stage Breast Cancer: A Method for Public Health Practice using Cancer Registry Data

In Spatial Analysis on August 6, 2010 at 7:29 am

Cancer Causes & Control, Volume 20, Issue 7, September 2009

J. Meliker, G. Jacquez, P. Goovaerts, G. Copeland, and M. Yassine

“Cancer registries are increasingly mapping residences of patients at time of diagnosis, however, an accepted protocol for spatial analysis of these data is lacking. We undertook a public health practice-research partnership to develop a strategy for detecting spatial clusters of early stage breast cancer using registry data. Spatial patterns of early stage breast cancer throughout Michigan were analyzed comparing several scales of spatial support, and different clustering algorithms. Analyses relying on point data identified spatial clusters not detected using data aggregated into census block groups, census tracts, or legislative districts. Further, using point data, Cuzick-Edwards’ nearest neighbor test identified clusters not detected by the SaTScan spatial scan statistic. Regression and simulation analyses lent credibility to these findings. In these cluster analyses of early stage breast cancer in Michigan, spatial analyses of point data are more sensitive than analyses relying on data aggregated into polygons, and the Cuzick-Edwards’ test is more sensitive than the SaTScan spatial scan statistic, with acceptable Type I error. Cuzick-Edwards’ test also enables presentation of results in a manner easily communicated to public health practitioners. The approach outlined here should help cancer registries conduct and communicate results of geographic analyses. OBJECTIVES: Cancer registries are increasingly mapping residences of patients at time of diagnosis, however, an accepted protocol for spatial analysis of these data is lacking. We undertook a public health practice-research partnership to develop a strategy for detecting spatial clusters of early stage breast cancer using registry data. METHODS: Spatial patterns of early stage breast cancer throughout Michigan were analyzed comparing several scales of spatial support, and different clustering algorithms. RESULTS: Analyses relying on point data identified spatial clusters not detected using data aggregated into census block groups, census tracts, or legislative districts. Further, using point data, Cuzick-Edwards’ nearest neighbor test identified clusters not detected by the SaTScan spatial scan statistic. Regression and simulation analyses lent credibility to these findings. CONCLUSIONS: In these cluster analyses of early stage breast cancer in Michigan, spatial analyses of point data are more sensitive than analyses relying on data aggregated into polygons, and the Cuzick-Edwards’ test is more sensitive than the SaTScan spatial scan statistic, with acceptable Type I error. Cuzick-Edwards’ test also enables presentation of results in a manner easily communicated to public health practitioners. The approach outlined here should help cancer registries conduct and communicate results of geographic analyses.”

A Fundamental Change in Science: A Brief Interview with Prof. David Maidment

In Conferences, ESRI, Environmental Science, GIS, Interviews, Science, Spatial Analysis, Temporal Analysis on August 5, 2010 at 7:35 am

Q: At the Friday morning closing session of the 2010 ESRI International User Conference, Scott Morehouse invited you on stage for a few minutes to share your experience that week.  Can you share that experience again?

A: Well I already knew a lot about what was going to happen before the User Conference had even started, because I’d worked closely with Jack Dangermond on a paper a couple of months prior to the Conference, and I’d also worked closely with Clint Brown and Scott Morehouse before that.  But when I saw it all come together on Monday at the plenary session, somehow the neurons got connected in my mind and I sent a message to my staff back in Austin—get me an iPad!—while the plenary session was going on.  I now have an iPad.

By Tuesday, the impact of what was happening at the conference was overwhelming, and I went into kind of a vision-lock.  All these ideas were competing in my mind, and I was sitting in a Conference session and suddenly I realized, I’m still carrying a plastic bag.  What is this?  It’s my laundry!  I came out of my hotel room with my laundry bag and suddenly I went into vision-lock and I forgot all about my laundry!

It took me awhile to process it through, but by Thursday, in the Water Resources User Group, I gave a talk on implementing Jack’s vision in Hydro.  I’ve attended the ESRI User Conference 21 years in a row, and I’ve been teaching the Hydro seminar since 1994.  And the 2010 User Conference was by far the most important to me ever.  And why this is so important is because water changes with time.  Because of this, it’s been so inconvenient to deal with it in a GIS framework.  At least up until now.

I woke up Friday morning of the User Conference, and I realized, this is a fundamental change in science.  The implications are just immeasurable.  I don’t think we know where the limit of them is.  And it took me all week to process what happened to reach that conclusion.

Prof. David Maidment speaking at the Friday morning closing session of the 2010 ESRI International User Conference.

Q: You call this a fundamental change in science.  Can you explain in more detail exactly what you mean by that?

A: What’s happened is that time and space have come together—space-time.  Now, that’s been true in science for some time, because you could have spatially continuous arrays like time-varying sea surface temperatures and so on.  But it’s not been true in GIS.  So the fundamental breakthrough here in geographic information science is representing space-time processes on discrete spatial objects.  And that’s a fundamentally new thing that’s not been possible or accessible before.

Q: From a personal perspective, how is this going to change the way you do research?

A: What it means is that we can really bring water into GIS.   We can study the properties of water itself as they vary in space and time, and not just the watersheds, rivers, and aquifers through which water flows.  That is so important for better understanding how water impacts human life and sustains living communities.   Access to water information through the iPad and iPhone are also breakthroughs – water information everywhere, all the time!   Water is so vital to people and we are bringing knowledge of water closer to them.

Dr. David R. Maidment is the Hussein M. Alharthy Centennial Chair in Civil Engineering and the Director of the Center for Research in Water Resources at the University of Texas at Austin.  He can be reached at maidment@mail.utexas.edu.

Spatial Analysis of Livelihoods of Smallholder Farmers in Striga-infested Maize-growing Areas of Eastern and Southern Africa

In GIS, Social Science, Spatial Analysis, Statistics on August 5, 2010 at 6:31 am

International Institute of Tropical Agriculture and African Agricultural Technology Foundation report, January 2009

H. Bouwmeester, V.M. Manyong, K.D. Mutabazi, C. Maeda, G. Omanya, H.D. Mignouna, and M. Bokanga

“This report presents results from a spatial analysis of selected data generated through a livelihoods project in Striga infested areas of Malawi, Tanzania, and Uganda. In addition to mapping spatial patterns on livelihood indicators using Global Information Systems (GIS), the study also compared two interpolation techniques (ordinary Kriging and averaging) of measured values to surrounding locations. Livelihood indicators considered and spatially mapped in this report are related to natural capital, human capital, financial capital, maize growing Striga infestation and livelihood outcomes. Results show that many variables and indicators are clearly related to space. This is especially true in Malawi where many maps show a clear gradient from the “poor” south to the “rich” north. Many other maps in Tanzania and Uganda seem to suggest a similar correlation in space as nearby administrative units tend to have similar values on indicators. Although the survey that generated data used for this report was set up according to socioeconomic criteria and not so much on spatial criteria, the findings show that any economical study can profit from spatial analysis. The report also makes recommendations on how to improve on the collection and recording of geo-referenced data in the farmers’ fields.

“The livelihood project was designed to understand the effects of Striga on the livelihoods of the poor. Therefore, the sampled households were always located in areas known to be heavily infested with Striga. Expansion of areas of interest to areas not heavily infested to assess the effects on the researched indicators is recommended. This study indicates the power of GIS in exposing the socioeconomic consequences of a biological threat (Striga in this case) on smallholder farmers via a set of quantifiable indicators. Therefore, it can be said that databases designed for socioeconomic purposes can be very useful in spatial analysis. Two methods of interpolation were applied that allow socioeconomic properties to be predicted for unvisited sites. The results indicate that applying the two methods generate a spatial correlation in many of the economic indicators.”

Analysis of Spatial and Temporal Evolution of the NDVI on Vegetated and Degraded Areas in the Central Spanish Pyrenees

In Environmental Science, Imagery, Spatial Analysis, Temporal Analysis on August 4, 2010 at 9:57 am

ISPRS Technical Commission VII Symposium: 100 Years ISPRS – Advancing Remote Sensing Science, 05-07 July 2010, Vienna, Austria

Luis Carlos Alatorre, and S. Beguería

“The temporal evolution of vegetation activity on various land cover classes in the Spanish Pyrenees was analyzed. Two time series of the normalized difference vegetation index (NDVI) were used, corresponding to March (early spring) and August (the end of summer). The series were generated from Landsat TM and Landsat ETM+ images for the period 1984-2007. An increase in the NDVI in March was found for vegetated areas, and the opposite trend was found in both March and August for degraded areas (badlands and erosion risk areas). The rise in minimum temperature during the study period appears to be the most important factor explaining the increased NDVI in the vegetated areas. In degraded areas, no climatic or topographic variable was associated with the negative trend in the NDVI, which may be related to erosion processes taking place in these regions.”

Does Competition Improve Public School Efficiency? A Spatial Analysis

In Social Science, Spatial Analysis on August 3, 2010 at 6:43 am

Dissertation, Mississippi State University, 2010

Kaustav Misra

“Proponents of educational reform often call for policies to increase competition between schools. It is argued that market forces naturally lead to greater efficiencies, including improved student learning, when schools face competition. In many parts of the country, public schools experience significant competition from private schools; however, the literature is not clear as to whether public versus private competition generates significant improvements in technical efficiency. A major hurdle for researchers examining this issue is determining a workable definition of competition by which they can measure the degree of competition within local markets. I address this challenge by developing a School Competition Index (SCI) for Mississippi through implementation of several Geographical Information System (GIS) tools. The SCI reveals the degree of competition for each public school based on their spatial location relative to peer private schools operating within their service area. GIS is a unique way to measure the degree of competition among public schools and private schools. Including components of market structure is not sufficient to measure the effects of competition in a market; market characteristics, which vary between locations, are also important. Market characteristics such as, religiosity, school location, and social capital are used in this dissertation as exogenous variables. Two stage stochastic frontier analysis and single equation stochastic frontier analysis are both employed to evaluate school efficiency. This dissertation finds that higher degrees of competition from private schools significantly increase public elementary school efficiency, as measured by the proficiency rates in different examinations. At the same time, competition from private schools does not improve public high schools efficiency. The results suggest that a rural-urban student academic achievement gap persists, and that community social capital stock is also important to some extent. Regardless of model or estimation procedure, students race and socio-economic status significantly reduce public school efficiency. It is anticipated that the current results will inform policymakers regarding the viability of competition-based reforms after considering all these factors.”

CAUSTA: Clifford Algebra-based Unified Spatio-Temporal Analysis

In GIScience, Spatial Analysis, Temporal Analysis on August 2, 2010 at 10:46 am

Transactions in GIS, Volume 14 Issue s1, Pages 59 – 83

Linwang Yuan, Zhaoyuan Yu, Shaofei Chen, Wen Luo, Yongjun Wang, and Guonian Lü

“Introducing Clifford algebra as the mathematical foundation, a unified spatio-temporal data model and hierarchical spatio-temporal index are constructed by linking basic data objects, like pointclouds and Spatio-Temporal Hyper Cubes of different dimensions, within the multivector structure of Clifford algebra. The transformation from geographic space into homogeneous and conformal space means that geometric, metric and many other kinds of operators of Clifford algebra can be implemented and we then design the shortest path, high-dimensional Voronoi and unified spatial-temporal process analyses with spacetime algebra. Tests with real world data suggest these traditional GIS analysis algorithms can be extended and constructed under Clifford Algebra framework, which can accommodate multiple dimensions. The prototype software system CAUSTA (Clifford Algebra based Unified Spatial-Temporal Analysis) provides a useful tool for investigating and modeling the distribution characteristics and dynamic process of complex geographical phenomena under the unified spatio-temporal structure.”

Spatial Behavior and Linguistic Representation: Collaborative Interdisciplinary Specialized Workshop

In Conferences, GIScience, Spatial Analysis on August 2, 2010 at 8:59 am

Journal of Spatial Information Science, Number 1 (2010), pp. 115-120

Thora Tenbrink, Jan Wiener, Christophe Claramunt, Marios Avraamides, Rainer Malaka, and Hanspeter A Mallot

“The Collaborative Interdisciplinary Specialized Workshop on Spatial Behavior and Linguistic Representation took place on April 23-24, 2010, at the Hanse-Wissenschaftskolleg, Institute for Advanced Study (HWK), in Delmenhorst, Germany. We report the scientific motivation for this workshop and report its outcomes together with the impact of a gathering of this kind for the scientific community.”

Mass Fraction Spatiotemporal Geostatistics and its Application to Map Atmospheric Polycyclic Aromatic Hydrocarbons after 9/11

In Environmental Science, GIS, Spatial Analysis, Statistics, Temporal Analysis on August 2, 2010 at 7:36 am

Stochastic Environmental Research and Risk Assessment, Volume 23, Number 8 / December, 2009

William B. Allshouse, Joachim D. Pleil, Stephen M. Rappaport, and Marc L. Serr

“This work proposes a space/time estimation method for atmospheric PM2.5 components by modelling the mass fraction at a selection of space/time locations where the component is measured and applying the model to the extensive PM2.5 monitoring network. The method we developed utilizes the nonlinear Bayesian maximum entropy framework to perform the geostatistical estimation. We implemented this approach using data from nine carcinogenic, particle-bound polycyclic aromatic hydrocarbons (PAHs) measured from archived PM2.5 samples collected at four locations around the World Trade Center (WTC) from September 22, 2001 to March 27, 2002. The mass fraction model developed at these four sites was used to estimate PAH concentrations at additional PM2.5 monitors. Even with limited PAH data, a spatial validation showed the application of the mass fraction model reduced the mean squared error (MSE) by 7–22%, while in the temporal validation there was an exponential improvement in MSE positively associated with the number of days of PAH data removed. Our results include space/time maps of atmospheric PAH concentrations in the New York area after 9/11.”

Space-Time Integration in Geography and GIScience

In GIScience, Geography, Modeling, Spatial Analysis, Temporal Analysis on August 2, 2010 at 6:56 am

AAG Newsletter of the Association of American Geographers, July/August 2010

Doug Richardson

“Every year, the Association of American Geographers (AAG) identifies a particularly timely or relevant set of themes to feature during its Annual Meetings. Last year an over-riding theme was climate change, for example, and previous years have included featured sessions on topics on as human rights, landscape and literature, sustainable development in Africa, geography of water, and many other topics.

“Among several special themes at its upcoming Annual Meeting in Seattle, April 12- 16, 2011, will be multiple sessions focused on the research status, recent advances and research needs of space-time integration, modeling and analysis in geography and GIScience. This special set of invited papers will feature many leading GIScience researchers from Asia and Europe as well nas from other regions of the world, and will form a three-day high-profile symposium within the AAG Annual Meeting.”

New Perspectives on the Energy Return on (Energy) Investment (EROI) of Corn Ethanol

In Environmental Science, Green Technologies, Spatial Analysis on August 2, 2010 at 6:32 am

Environment, Development and Sustainability, published online 11 July 2010

David J. Murphy, Charles A. S. Hall, and Bobby Powers

“Research on corn ethanol is overly focused on whether corn ethanol is a net energy yielder and, consequently, has missed some other fundamental issues, including (1) whether there is significant error associated with current estimates of the EROI of corn ethanol, (2) whether there is significant spatial variability in the EROI of corn ethanol production, (3) whether yield increases will translate linearly to increases in EROI, (4) the extent to which assumptions about co-product credits impact the EROI of corn ethanol, and (5) how much of the ethanol production from biorefineries is net energy. We address all of these concerns in this research by: (1) performing a meta-error analysis of the calculation of EROI, (2) calculating the EROI for 1,287 counties across the United States, and (3) performing a sensitivity analysis for the values of both yield and co-products within the calculation of EROI. Our results show that the average EROI calculated from the meta-error analysis was 1.07 ± 0.2, meaning that we are unable to assert whether the EROI of corn ethanol is greater than one. The average EROI calculated across 1,287 counties in our spatial analysis was 1.01, indicating that the literature tended to use optimal values for energy inputs and outputs compared to the average conditions across the Unites States. Increases in yield had a trivial impact on EROI, while co-product credits had a large impact on EROI. Based on our results from the spatial analysis and the location of biorefineries across the United States, we conclude that the net energy supplied to society by ethanol is only 0.8% of that supplied from gasoline. Recent work indicates that only energy sources extracted at EROIs of 3:1 or greater have the requisite net energy to sustain the infrastructure of the transportation system of the United States. In light of this work, we conclude that production of corn ethanol within the United States is unsustainable and requires energy subsidies from the larger oil economy.”

Space-Time Kernels

In Modeling, Spatial Analysis, Statistics, Temporal Analysis on July 30, 2010 at 8:04 am

ISPRS Commission II Mid-Term Symposium: Theory, Data Handling and Modelling in GeoSpatial Information Science – 26-28 May 2010, Hong Kong

Jiaqiu Wang, Tao Cheng, and James Haworth

“Kernel methods are a class of algorithms for pattern recognition. They play an important role in the current research area of spatial and temporal analysis since they are theoretically well-founded methods that show good performance in practice. Over the years, kernel methods have been applied to various fields including machine learning, statistical analysis, imaging processing, text categorization, handwriting recognition and many others. More recently, kernel-based methods have been introduced to spatial analysis and temporal analysis. However, how to define kernels for space-time analysis is still not clear. In the paper, we firstly review the relevant kernels for spatial and temporal analysis, then a space-time kernel function (STK) is presented based on the principle of convolution kernel for space-time analysis. Furthermore, the proposed space-time kernel function (STK) is applied to model space-time series using support vector regression algorithm. A case study is presented in which STK is used to predict China’s annual average temperature. Experimental results reveal that the space-time kernel is an effective method for space-time analysis and modelling.”

Crop Production and Road Connectivity in Sub-Saharan Africa: A Spatial Analysis

In GIS, Social Science, Spatial Analysis on July 30, 2010 at 6:24 am

World Bank Policy Research Working Paper No. WPS 5385, July 2010

Dorosh, Paul; Wang, Hyoung-Gun; You, Liang; and Schmidt, Emily

“This study examines the relationship between transport infrastructure and agriculture in Sub-Saharan Africa using new data obtained from geographic information systems (GIS). First, the authors analyze the impact of road connectivity on crop production and choice of technology. Second, they explore the impact of investments that reduce road travel times. Finally, they show how this type of analysis can be used to compare cost-benefit ratios for alternative road investments in terms of agricultural output per dollar invested. The authors find that agricultural production is highly correlated with proximity (as measured by travel time) to urban markets. Likewise, adoption of high-productive/high-input technology is negatively correlated with travel time to urban centers. There is therefore substantial scope for increasing agricultural production in Sub-Saharan Africa, particularly in more remote areas. Total crop production relative to potential production is 45 percent for areas within four hours’ travel time from a city of 100,000 people. In contrast, it is just 5 percent for areas more than eight hours away. Low population densities and long travel times to urban centers sharply constrain production. Reducing transport costs and travel times to these areas would expand the feasible market size for these regions. Compared to West Africa, East Africa has lower population density, smaller local markets, lower road connectivity, and lower average crop production per unit area. Unlike in East Africa, reducing travel time does not significantly increase the adoption of high-input/high-yield technology in West Africa. This may be because West Africa already has a relatively well-connected road network.”

Detecting Spatiotemporal Change of Land Use and Landscape Pattern in a Coastal Gulf Region, Southeast of China

In GIS, Imagery, Spatial Analysis, Temporal Analysis on July 29, 2010 at 9:00 am

Environment, Development and Sustainability, Volume 12, Number 1 / February, 2010

Jinliang Huang, Jie Lin, and Zhenshun Tu

“Geographic information system (GIS), remote sensing (RS), gradient analysis, and landscape pattern metrics were coupled to quantitatively characterize the spatiotemporal change of land use and landscape pattern over the period 1988–2007 in a coastal gulf region, southeast China. The results obtained show an increase in cropland, buildup land, and aquiculture area and decrease in orchard, woodland, and beach area during 1988–2007. Landscape fragmented processes were strengthened and landscape pattern structure became more complicated in the last two decades in Luoyuan gulf region. The dynamics intensity of landscape pattern is stronger during 2002–2007 than that during 1988–2002. Spatial difference of urban–rural landscape pattern can be detected distinctively in two transects in terms of landscape metrics. Urbanization processes and the policy developed to transfer seawater into buildup land are two driving forces leading to the spatiotemporal change of landscape pattern in Luoyuan gulf region in the last two decades.”

OLAP-based Analysis and Visualization of Large Volumes of Hydrologic Data

In Spatial Analysis, Visualization on July 29, 2010 at 8:39 am

AWRA 2010 Spring Specialty Conference, Orlando, Forida, March 29-31, 2010

Matthew Rodriguez, David Valentine, Thomas Whitenack, and Ilya Zaslavsky

“One of the goals of the CUAHSI Hydrologic Information System project (Maidment, 2009) is to create a comprehensive portrait of hydrologic observations for the U.S., integrating observational data and metadata from multiple sources, at the national, regional, and local levels. The data are made available via a uniform set of web service interfaces, called CUAHSI Water Data Services. Once a source of hydrologic observations is exposed via such set of methods, it is registered in the HIS Central registry (hiscentral.cuahsi.org) and its metadata is harvested into the central metadata catalog. The catalog currently indexes 9 million time series for 1.8 million measurement points, supporting web service access to about 4.3 billion data points. Such large catalogs and databases of observational and model-generated data are time consuming to query using common relational database tools. This paper describes a technique for rapid analysis and visualization of data summaries in large hydrologic data repositories using Online Analytical Processing (OLAP). OLAP databases, often called data cubes, are special representations that support high performance querying of large multidimensional data collections. The OLAP techniques are applied to the analysis of observation data catalogs and databases from several federal agencies, including EPA STORET, USGS NWIS, and USDA SNOTEL. We present sample OLAP analysis related to hydrologic data availability from the observations data catalogs, and geographic and temporal analysis of available data totals from the federal repositories. In addition, we demonstrate a novel web application for spatial analysis of OLAP data cubes built over observational and model-generated hydrologic datasets.”

Wakame: Sense Making of Multi-Dimensional Spatial-Temporal Data

In Spatial Analysis, Temporal Analysis, Visualization on July 29, 2010 at 8:31 am

Mitsubishi Electric Research Laboratories, Report #TR2010-031, June 2010

Clifton Forlines and  Kent Wittenburg

“As our ability to measure the world around us improves, we are quickly generating massive quantities of high-dimensional, spatial-temporal data. In this paper, we concern ourselves with datasets in which the spatial characteristics are relatively static but many dimensions prevail and data is sampled over different time periods. Example applications include building energy management of HVAC unit diagnostics. We present methods employed in our Wakame visualization system to support such tasks as discovering anomalies and comparing performance across multiple time series. Novel methods include animated transitions that relate data in spatially located 3D views with conventional 2D graphs. Additionally, several components of our prototype employ analytics to guide the user to ”interesting” portions of the dataset.”

The Need For a Spatial Analysis of Educational Inequities

In Education, Social Science, Spatial Analysis on July 29, 2010 at 7:09 am

European Conference on Educational Research 2009 Conference

Kirstin Kerr

“Across Europe, education, disadvantage and place are strongly linked. In areas characterised by high levels of disadvantage, where families most vulnerable to social exclusion are concentrated, children are most likely to achieve poor educational outcomes (Palmer et al 2007). Huge resources have been directed towards breaking this pattern – from strategies promoting school effectiveness and improvement, to area-based initiatives including France’s Zones d’Education Prioritaire, and England’s Education Action Zones (Bénabou et al 2005, Hatcher and Leblond 2001). Yet despite this, the link remains strongly ingrained. Policy’s relative failure in this respect suggests that it has been based on an inadequate understanding of the nature of educational inequities (Gulson 2005, Power et al 2005). Following this, this paper argues that policies need to be informed by spatial understanding of education inequities, which focuses attention on the local structures, processes and relationships which create these. It asks: “What can be learnt from a spatial analysis of educational inequities?” The paper reports empirical data from a spatial analysis of educational inequities in an urban inner-city ward in North West England. This has a number of ramifications – conceptually, and for research and policy: 1. It starts to develop a framework for the spatial analyses of educational inequities focusing on: (1) an area’s observable features (e.g. the locations of schools, demographic characteristics, housing types) (Butler and Hamnett 2007); (2) how areas are experienced and ‘lived’ (Lefbvre 1991); and (3) how these dimensions of space interact and impact on education. 2. It identifies the need for research which can: (1) explain how local dynamics shape educational outcomes; and (2) identify the key underlying factors at work, those which can be acted upon, and by whom. 3. It suggests that policymakers can respond to such analyses by creating broad national frameworks with some scope for strategic development at local level.”

Estimating Similarity of Communities: A Parametric Approach to Spatio-temporal Analysis of Species Diversity

In Environmental Science, Modeling, Spatial Analysis, Statistics, Temporal Analysis on July 28, 2010 at 8:58 am

Ecography, Published Online 20 July 2010

Steinar Engen, Vidar Grøtan and Bernt-Erik Sæther

“Several stochastic models with environmental noise generate spatio-temporal Gaussian fields of log densities for the species in a community. Combinations of such models for many species often lead to lognormal species abundance distributions. In spatio-temporal analysis it is often realistic to assume that the same species are expected to occur at different times and/or locations because extinctions are rare events. Spatial and temporal β-diversity can then be analyzed by studying pairs of communities at different times or locations defined by a bivariate lognormal species abundance model in which a single correlation occurs. This correlation, which is a measure of similarity between two communities, can be estimated from samples even if the sampling intensities vary and are unknown, using the bivariate Poisson lognormal distribution. The estimators are approximately unbiased, although each specific correlation may be rather uncertain when the sampling effort is low with only a small fraction of the species represented in the samples. An important characteristic of this community correlation is that it relates to the classical Jaccard- or the Sørensen-indices of similarity based on the number of species present or absent in two communities. However, these indices calculated from samples of species in a community do not necessarily reflect similarity of the communities because the observed number of species depends strongly on the sampling intensities. Thus, we propose that our community correlation should be considered as an alternative to these indices when comparing similarity of communities. We illustrate the application of the correlation method by computing the similarity between temperate bird communities.”

A Spatio-temporal Climate-based Model of Early Dengue fever Warning in Southern Taiwan

In Environmental Science, Modeling, Spatial Analysis, Statistics, Temporal Analysis on July 28, 2010 at 6:40 am

Stochastic Environmental Research and Risk Assessment, published online July 17, 2010

Hwa-Lung Yu, Shang-Jen Yang, Hsin-Ju Yen, and George Christakos

“Dengue Fever (DF) has been identified by the World Health organization (WHO) as one of the most serious vector-borne infectious diseases in tropical and sub-tropical areas. During 2007, in particular, there were over 2,000 DF cases in Taiwan, which was the highest number of cases in the recorded history of Taiwan epidemics. Most DF studies have focused mainly on temporal DF patterns and its close association with climatic covariates, whereas they have understated spatial DF patterns (spatial dependence and clustering) and composite space–time effects. The present study proposes a spatio-temporal DF prediction approach based on stochastic Bayesian Maximum Entropy (BME) analysis. Core and site-specific knowledge bases are considered, including climate and health datasets under conditions of uncertainty, space–time dependence functions, and a Poisson regression model of climatic variables contributing to DF occurrences in southern Taiwan during 2007. The results show that the DF outbreaks in the study area are highly influenced by climatic conditions. Furthermore, the analysis can provide the required “one-week-ahead” outbreak warnings based on spatio-temporal predictions of DF distributions. Therefore, the proposed approach can provide the Taiwan Disease Control Agency with a valuable tool to timely identify, control, and even efficiently prevent DF spreading across space–time.”

Sensitivity of River Discharge to El Niño Southern Oscillation (ENSO)

In Environmental Science, Geography, Spatial Analysis on July 27, 2010 at 7:54 am

Geophysical Research Letters, Volume 37, 2010

Philip J. Ward, Wisse Beets, Laurens M. Bouwer, Jeroen C. J. H. Aerts, and Hans Renssen

“El Niño Southern Oscillation (ENSO) has significant impacts on streamflows around the world. While many studies have assessed correlations, an assessment of the magnitude of this impact is lacking, and little is known of ENSO’s impact on extreme discharges. We use a daily discharge dataset to provide a global assessment of the sensitivity of annual mean and flood discharges to ENSO, and a gridded climate dataset to assess the global impact of ENSO on precipitation and temperature. We find that, on average, for the stations studied ENSO has a greater impact on annual high-flow events than on mean annual discharge, especially in the extra-tropics. The quantification of ENSO impacts provides relevant information for water-management, allowing the identification of problem areas and providing a basis for risk assessments.”

Spatial and Temporal Analysis of Extreme Midwestern Blizzard Storm Tracks and Subsequent Federal Disaster Declarations

In Spatial Analysis, Temporal Analysis on July 27, 2010 at 7:27 am

Ph.D. Dissertation, University of Kansas, 26 April 2010

Christopher John Atkinson

“Using the NOAA Central Library United States Daily Weather Maps Project, the Hydrometeorological Prediction Center (HPC) online weather charts, Storm Data records from the National Climatic Data Center (NCDC), and the Academic OneFile from the University of Kansas, this study identified 145 extreme Midwestern blizzards, defined as storms with minimum central pressures at or below 992 mb, occurring between September 1, 1966, and May 31, 2008. This 42&ndash;year time period was split into two 21&ndash;year segments for comparative analyses of any changes in the spatial and temporal character of these storms: 1) September 1, 1966&ndash;May 31, 1987 (Time Period I: 79 blizzards); and, 2) September 1, 1987&ndash;May 31, 2008 (Time Period II: 66 blizzards). Changes in the frequency and intensity of extreme Midwestern blizzards proved to be statistically insignificant. All 145 blizzards in Time Periods I and II were mapped using ArcGIS 9.3 with data from the GISS Atlas of Extratropical Storm Tracks and the HPC weather maps and charts online resource. A 50&ndash;km buffer flanked each storm track and helped account for any uncharted errors in the original re&ndash;analysis procedures done by the GIS. Additionally, the 50&ndash;km buffer provided a construct for identifying the trajectory for each snowstorm within the 12&ndash;state study region, defined as North Dakota, South Dakota, Nebraska, Kansas, Missouri, Iowa, Minnesota, Wisconsin, Michigan, Illinois, Indiana, and Ohio. This study indicated a statistically insignificant southward shift of the median storm track in Time Period II. Of the 79 blizzards in Time Period I and the 66 blizzards in Time Period II, only 23 storms (6 in Time Period I and 17 in Time Period II) resulted in federal emergency and disaster declarations (FEDD). Logistic regression analyses of seven independent variables utilizing the Forward LR model failed to accurately predict when federal declarations occurred. In contrast, the total number of counties declared as FEDDs increased from 378 (Time Period I) to 973 (Time Period II), a statistically significant difference. The spatial distribution of declaration hazards (snow and ice) contributing to FEDDs changed between the two time periods, indicating a pattern not necessarily connected to the expected climatology of extreme Midwestern blizzards.”

Spatial Analysis of Air Pollution and Cancer Incidence Rates in Haifa Bay, Israel

In Environmental Science, Spatial Analysis on July 23, 2010 at 6:50 am

Science of the Total Environment, 2010, Jul 12. [Epub ahead of print]

Eitan O, Yuval, Barchana M, Dubnov J, Linn S, Carmel Y, and Broday DM

“The Israel National Cancer Registry reported in 2001 that cancer incidence rates in the Haifa area are roughly 20% above the national average. Since Haifa has been the major industrial center in Israel since 1930, concern has been raised that the elevated cancer rates may be associated with historically high air pollution levels. This work tests whether persistent spatial patterns of metrics of chronic exposure to air pollutants are associated with the observed patterns of cancer incidence rates. Risk metrics of chronic exposure to PM(10), emitted both by industry and traffic, and to SO(2), a marker of industrial emissions, was developed. Ward-based maps of standardized incidence rates of three prevalent cancers: Non-Hodgkin’s lymphoma, lung cancer and bladder cancer were also produced. Global clustering tests were employed to filter out those cancers that show sufficiently random spatial distribution to have a nil probability of being related to the spatial non-random risk maps. A Bayesian method was employed to assess possible associations between the morbidity and risk patterns, accounting for the ward-based socioeconomic status ranking. Lung cancer in males and bladder cancer in both genders showed non-random spatial patterns. No significant associations between the SO(2)-based risk maps and any of the cancers were found. Lung cancer in males was found to be associated with PM(10), with the relative risk associated with an increase of 1mug/m(3) of PM(10) being 12%. Special consideration of wards with expected rates <1 improved the results by decreasing the variance of the spatially correlated residual log-relative risk.”

A Comprehensive Framework for Exploratory Spatial Data Analysis: Moran Location and Variance Scatterplots

In GIS, Spatial Analysis, Visualization on July 22, 2010 at 2:57 pm

International Journal of Digital Earth, Volume 3, Issue 2 June 2010 , pages 157 – 186

J. G. Negreiros; M. T. Painho; F. J. Aguilar; and M. A. Aguilar

“A significant Geographic Information Science (GIS) issue is closely related to spatial autocorrelation, a burning question in the phase of information extraction from the statistical analysis of georeferenced data. At present, spatial autocorrelation presents two types of measures: continuous and discrete. Is it possible to use Moran’s I and the Moran scatterplot with continuous data? Is it possible to use the same methodology with discrete data? A particular and cumbersome problem is the choice of the spatial-neighborhood matrix (W) for points data. This paper addresses these issues by introducing the concept of covariogram contiguity, where each weight is based on the variogram model for that particular dataset: (1) the variogram, whose range equals the distance with the highest Moran I value, defines the weights for points separated by less than the estimated range and (2) weights equal zero for points widely separated from the variogram range considered. After the W matrix is computed, the Moran location scatterplot is created in an iterative process. In accordance with various lag distances, Moran’s I is presented as a good search factor for the optimal neighborhood area. Uncertainty/transition regions are also emphasized. At the same time, a new Exploratory Spatial Data Analysis (ESDA) tool is developed, the Moran variance scatterplot, since the conventional Moran scatterplot is not sensitive to neighbor variance. This computer-mapping framework allows the study of spatial patterns, outliers, changeover areas, and trends in an ESDA process. All these tools were implemented in a free web e-Learning program for quantitative geographers called SAKWeb© (or, in the near future, myGeooffice.org).”

The Digital Earth: 12 Years Later

In Climate Change, Environmental Science, GIS, Geography, Modeling, Spatial Analysis, Visualization on July 21, 2010 at 9:02 am

Vice President Al Gore delivered a forward-looking speech titled “The Digital Earth: Understanding our Planet in the 21st Century” at the California Science Center in Los Angeles on 31 January 1998.  Regardless of how you feel about Al Gore, every geospatial professional should read this once in a while – to both congratulate ourselves on how much progress we’ve made, and remind us there is still work to be done.

“A new wave of technological innovation is allowing us to capture, store, process and display an unprecedented amount of information about our planet and a wide variety of environmental and cultural phenomena. Much of this information will be “georeferenced” – that is, it will refer to some specific place on the Earth’s surface.

“I believe we need a “Digital Earth”. A multi-resolution, three-dimensional representation of the planet, into which we can embed vast quantities of geo-referenced data.”

You can read Gore’s complete speech here [PDF]

For a good overview of what’s happened in the last 12 years, see Digital Earth on Wikipedia

A Spatial Analysis System for Integrating Data, Methods and Models on Environmental Risks and Health Outcomes

In Environmental Science, GIScience, Modeling, Social Science, Spatial Analysis on July 20, 2010 at 6:58 am

Transactions in GIS, Volume 14 Issue s1, Pages 177 – 195

Chetan Tiwari and Gerard Rushton

“Integrating data on health outcomes with methods of disease mapping and spatially explicit models of environmental contaminants are important aspects of environmental health surveillance. In this article, we describe a modular, web-based spatial analysis system that uses GIS, spatial analysis methods and software services delivered over computer networks to achieve this end. The Environmental Health Surveillance System (EHSS) is a prototype system that is designed to serve three purposes: a secure environment for producing maps of disease outcomes from individual-level data while preserving privacy; an automated process of linking environmental data, environmental models, and GIS tasks like geocoding for the purposes of estimating individual exposures to environmental contaminants; and mechanisms to visualize the spatial patterns of disease outcomes via Web-based mapping interfaces and interactive tools like Google Earth.”

Multi-temporal Analysis for Mexico City Aquifer using a GIS-based on Measured Data

In GIS, Spatial Analysis, Temporal Analysis on July 19, 2010 at 1:02 pm

ISMAR7, 09-13 October 2010, Abu Dhabi

Rosío Ruiz and Gerardo Ruiz

“The growth of the population in Mexico City, demand increased amount of water day with day today for providing the vital fluid is resorted to the exploitation of sources, both internal and external, the aquifer of Mexico City, the dependency of groundwater extracted from wells makes it necessary to review the conditions of the aquifer for evolutionary in the aquifers conditions; these revisions are made from the depths of groundwater; measurements obtained values can infer the effect that brings with it the exploitation of this source and at the same time can implement actions to enable their recovery.

“The main objective of this paper is to introduce a system that enables storage of information, analysis and visualization of measurements of static, dynamic levels and specific flow, as well as behavior in the Geographic Information System to support a better understanding of the modeling of the aquifer and better decision making in the operation of the network of the Valley of Mexico wells GIS-based data measured.

“Presents a multi-temporal analysis of the evolution of groundwater until 2009 the aquifer of area Metropolitan of the Mexico City, for which the static and dynamic level of 225 wells measurement was made. Perform hydraulic balance of groundwater, determining degree of overexploitation. Check changes in the static levels of the aquifer system from policies. Start the historical record of dynamic measurements in wells in operation. Determine the behavior of the aquifer in recent years. Differentiate areas of greater exploitation of those recovering.”

Adaptive Cell Tower Location Using Geostatistics

In Modeling, Spatial Analysis, Statistics on July 19, 2010 at 10:51 am

Geographical Analysis, Volume 42 Issue 3, Pages 227 – 244, Published Online 01 July 2010

Mohan R. Akella, Eric Delmelle, Rajan Batta, Peter Rogerson, and Alan Blatt

“In this article, we address the problem of allocating an additional cell tower (or a set of towers) to an existing cellular network, maximizing the call completion probability. Our approach is derived from the adaptive spatial sampling problem using kriging, capitalizing on spatial correlation between cell phone signal strength data points and accounting for terrain morphology. Cell phone demand is reflected by population counts in the form of weights. The objective function, which is the weighted call completion probability, is highly nonlinear and complex (nondifferentiable and discontinuous). Sequential and simultaneous discrete optimization techniques are presented, and heuristics such as simulated annealing and Nelder–Mead are suggested to solve our problem. The adaptive spatial sampling problem is defined and related to the additional facility location problem. The approach is illustrated using data on cell phone call completion probability in a rural region of Erie County in western New York, and accounts for terrain variation using a line-of-sight approach. Finally, the computational results of sequential and simultaneous approaches are compared. Our model is also applicable to other facility location problems that aim to minimize the uncertainty associated with a customer visiting a new facility that has been added to an existing set of facilities.”

The Framework of a Geospatial Semantic Web-based Spatial Decision Support System for Digital Earth

In Environmental Science, Geography, Spatial Analysis on July 19, 2010 at 8:18 am

International Journal of Digital Earth, Volume 3, Issue 2 June 2010 , pages 111 – 134

Chuanrong Zhang; Tian Zhao; and Weidong Li

“While significant progress has been made to implement the Digital Earth vision, current implementation only makes it easy to integrate and share spatial data from distributed sources and has limited capabilities to integrate data and models for simulating social and physical processes. To achieve effectiveness of decision-making using Digital Earth for understanding the Earth and its systems, new infrastructures that provide capabilities of computational simulation are needed. This paper proposed a framework of geospatial semantic web-based interoperable spatial decision support systems (SDSSs) to expand capabilities of the currently implemented infrastructure of Digital Earth. Main technologies applied in the framework such as heterogeneous ontology integration, ontology-based catalog service, and web service composition were introduced. We proposed a partition-refinement algorithm for ontology matching and integration, and an algorithm for web service discovery and composition. The proposed interoperable SDSS enables decision-makers to reuse and integrate geospatial data and geoprocessing resources from heterogeneous sources across the Internet. Based on the proposed framework, a prototype to assist in protective boundary delimitation for Lunan Stone Forest conservation was implemented to demonstrate how ontology-based web services and the services-oriented architecture can contribute to the development of interoperable SDSSs in support of Digital Earth for decision-making.”

A Spatial Analysis of Fish Farming in the Context of ICZM in the Bay of Izmir-Turkey

In Environmental Science, GIS, Spatial Analysis on July 16, 2010 at 8:17 am

Coastal Management, Volume 38, Issue 4 July 2010 , pages 399 – 411

Guzel Yucel-Giera; Yalcin Arisoyb; and Idil Pazi

“Cage fish farming is one of the fastest growing food industries, both worldwide and in Turkey. There are growing concerns about the manner of resolving the competing claims for the use of limited coastline and water body space. Matters connected with the siting of fish farming increase the need for the integrated coastal zone planning of aquaculture. This should be undertaken in collusion with other coastal stakeholders and with the cooperation of the government ministries that promote and regulate aquaculture development. In this study the integration and coexistence of fish farms is evaluated in the context of other activities in Izmir Bay. This study shows how different terrestrial and marine activities interact with each other, and that certain areas are subject to layers of multiple usages. One of the major sea users of the Bay, for example, is the fishery sector, which utilizes 850.4 km2 of a total surface area of Izmir’s Bay of 960.4 km2. This overlaps with the 113.4 km2 that are used by marine transportation. Military zones encompass 63.1 km2 and fish farming utilizes only 1.23 km2. This study uses Geographic Information Systems (GIS) to build a spatial database that analyzes conflicting claims for integrating fish farming with other claimants. Clearly planned and properly managed fish farming development should be undertaken within a broader framework of integrated coastal zone management.”

Impact Assessment of the European Biofuel Directive on Land Use and Biodiversity

In Environmental Science, Green Technologies, Spatial Analysis on July 15, 2010 at 12:55 pm

Journal of Environmental Management, Volume 91, June 2010

Fritz Hellmann and Peter H Verburg

“This paper presents an assessment of the potential impact of the EUs biofuel directive on European land use and biodiversity. In a spatially explicit analysis, it is determined which ecologically valuable land use types are likely to be directly replaced by biofuel crops. In addition, it is determined which land use types may be indirectly replaced by biofuel crops through competition over land between biofuel and food crops. Four scenarios of land use change are analyzed for the period 2000-2030 while for each scenario two policy variants are analyzed respectively with and without implementation of the biofuel directive. The results indicate that the area of semi natural vegetation, forest and High Nature Value farmland directly replaced by biofuel crops is small in all scenarios and differs little between policy variants. The direct effects of the directive on European land use and biodiversity therefore are relatively minor. The indirect effects of the directive on European land use and biodiversity are much larger than its direct effects. The area semi natural vegetation is found to be 3-8% smaller in policy variants with the directive as compared to policy variants without the directive. In contrast, little difference is found between the policy variants with respect to the forest area. The results of this study show that the expected indirect effects of the directive on biodiversity are much greater than its direct effects. This suggests that indirect effects need to be taken explicitly into account in assessing the environmental effects of biofuel crop cultivation and designing sustainable pathways for implementing biofuel policies.”

Spatio-Temporal Analysis of Total Nitrate Concentrations Using Dynamic Statistical Models

In Environmental Science, Modeling, Spatial Analysis, Statistics, Temporal Analysis on July 15, 2010 at 7:00 am

Journal of the American Statistical Association, June 1, 2010, 105(490): 538-551

Sujit K. Ghosh, Prakash V. Bhave, Jerry M. Davis, and Hyeyoung Lee

“Atmospheric concentrations of total nitrate (TNO3), defined here as gas-phase nitric acid plus particle-phase nitrate, are difficult to simulate in numerical air quality models due to the presence of a variety of formation pathways and loss mechanisms, some of which are highly uncertain. The goal of this study is to estimate the relative importance of these different pathways across the Eastern United States by identifying empirical relationships that exist between TNO3 concentrations and a set of covariates (ammonium, sulfate, ozone, wind speed, relative humidity, and precipitation) measured from January 1997 to July 2004. We develop two dynamic statistical models to quantify these relationships. A major advantage of these models over typical linear regression models is that their regression coefficients can vary temporally. Results show that TNO3 is sensitive to ozone throughout the year, indicating an importance of daytime photochemical production of TNO3, especially in the Southeast. Sensitivity of TNO3 to residual ammonium (NH4+–2SO42−) is most pronounced during winter, indicating a seasonal importance of gas/particle partitioning that is accentuated in the Midwest. Using a number of physical and chemical explanations, confidence is established in the spatial and temporal patterns of several such empirical relationships. In the future, these relationships may be used quantitatively to improve our mechanistic understanding of TNO3 formation pathways and loss mechanisms in the atmosphere.”

Probabilistic Modelling of Rainfall Induced Landslide Hazard Assessment

In ESRI, Environmental Science, GIS, Spatial Analysis, Temporal Analysis on July 15, 2010 at 6:57 am

Hydrology and Earth System Sciences, 14, 1047–1061, 2010

S. Kawagoe, S. Kazama, and P. R. Sarukkalige

“To evaluate the frequency and distribution of landslides hazards over Japan, this study uses a probabilistic model based on multiple logistic regression analysis. Study particular concerns several important physical parameters such as hydraulic parameters, geographical parameters and the geological parameters which are considered to be influential in the occurrence of landslides. Sensitivity analysis confirmed that hydrological parameter (hydraulic gradient) is the most influential factor in the occurrence of landslides. Therefore, the hydraulic gradient is used as the main hydraulic parameter; dynamic factor which includes the effect of heavy rainfall and their return period. Using the constructed spatial data-sets, a multiple logistic regression model is applied and landslide hazard probability maps are produced showing the spatial-temporal distribution of landslide hazard probability over Japan. To represent the landslide hazard in different temporal scales, extreme precipitation in 5 years, 30 years, and 100 years return periods are used for the evaluation. The results show that the highest landslide hazard probability exists in the mountain ranges on the western side of Japan (Japan Sea side), including the Hida and Kiso, Iide and the Asahi mountainous range, the south side of Chugoku mountainous range, the south side of Kyusu mountainous and the Dewa mountainous range and the Hokuriku region. The developed landslide hazard probability maps in this study will assist authorities, policy makers and decision makers, who are responsible for infrastructural planning and development, as they can identify landslide-susceptible areas and thus decrease landslide damage through proper preparation.”

Concentrating Solar Power in China and India: A Spatial Analysis of Technical Potential and the Cost of Deployment

In Environmental Science, Green Technologies, Spatial Analysis on July 15, 2010 at 6:52 am

Center for Global Development, Working Paper 219

Kevin Ummel

“Coal power generation in China and India could double and triple, respectively, over the next 20 years, which would increase exposure to fuel price volatility, exacerbate local air pollution, and hasten global climate change. Moving to concentrating solar power (CSP), a growing source of utility-scale, pollution-free electricity, would help alleviate these problems, but its potential in Asia remains largely unexamined. In this working paper, Kevin Ummel uses high-resolution spatial data to identify areas suitable for CSP and estimates power generation and cost under various land-use scenarios.

“Total CSP potential in China is at least 16 times greater than current coal power output; in India, it is at least 3 times greater. A CSP expansion program could provide 20 percent of electricity in both countries by midcentury. Under conservative assumptions, the program will require subsidies of $340 billion in present dollars. Estimated costs are especially sensitive to the assumed rate of technological learning, making it especially important to form committed public policy and financing to reduce investment risk, encourage the expansion of manufacturing capacity, and achieve long-term cost reductions.”

The Power of Business Analyst Online Now Available on the iPhone

In ESRI, GIS, Spatial Analysis on July 14, 2010 at 10:32 am

Free BAO for iOS App Provides On-the-Go Access to Demographic Reports and Maps

The new, free BAO for iOS app, available for download from the Apple app store, provides access to 2010 demographic and business data and analysis from Esri Business Analyst Online (BAO)

on the go.

BAO delivers powerful market analyses through a Web browser. Users generate on-demand reports and maps to get a detailed, comprehensive view of the demographic makeup of various populations and their lifestyles and buying behaviors. This revealing information allows users to find their best locations, customers, and products/services. With the BAO for iOS app, they can now get this valuable information through an iPhone, iPad, or iPod touch.

The BAO for iOS app provides the demographic and market information needed to instantly evaluate an area on-site.

It helps answer three key questions about a location:

  • What types of people live there?
    Get a demographic and market snapshot of a location (e.g., population, age, income, education, homeownership, and consumer spending).
  • How do they differ from the people in another location?
    Compare the demographic and market data for two locations or one location versus the entire United States.
  • Is this a good location based on specified needs?
    Set the desired criteria and find out how the location measures up.

In addition, subscribers to the BAO Web application will soon be able to access the full set of BAO reports and maps through BAO for iOS. A subscription to BAO allows users to access even more data, such as market potential, retail marketplace, and consumer spending, along with more analysis functionality, such as the ability to customize drive times and rings and create color-coded maps.

For more information and to download the app, visit www.esri.com/baoforios.

[Source: ESRI press release]

Spatial Analysis of Biomass Supply: Economic and Environmental Impacts

In Environmental Science, Green Technologies, Spatial Analysis on July 14, 2010 at 7:46 am

ASA, CSSA, and SSSA International Annual Meetings
31 October – 03 November 2010
Long Beach, California USA

David Archer

“The EPIC simulation model is used with SSURGO soils, field location information, and a transportation cost model to analyze potential biomass supply for a West Central MN bioenergy plant. The simulation shows the relationship between biomass price, locations of where biomass production is profitable, and impacts on economic optimum cropping practices. Results show expansion of production away from the bioenergy plant as biomass price increases. Also, increasing biomass price tends to increase harvest intensity and change the optimum crop rotation near the bioenergy plant. These changes have important implications for the environmental impacts of biomass harvest, since changes in harvest intensity and crop rotation can have substantial effects of soil erosion, soil carbon, and nutrient and pesticide runoff and leaching.”

A Geographical Population Analysis of Dental Trauma in School-children Aged 12 and 15 in the City of Curitiba, Brazil

In GIS, Geography, Social Science, Spatial Analysis, Statistics on July 14, 2010 at 7:31 am

BMC Health Services Research, 2010, 10:203doi

Max L Carvalho, Samuel J Moyses, Roberto E Bueno, Silvia Shimakura, and Simone T Moyses

“Background: The study presents a geographical analysis of dental trauma in a population of 12 and 15 year-old school-children, in the city of Curitiba, Brazil (n = 1581), using a database obtained in the period 2005-2006. The main focus is to analyze dental trauma using a geographic information system as a tool for integrating social, environmental and epidemiological data.

“Methods: Geostatistical analysis of the database and thematic maps were generated showing the distribution of dental trauma cases according to Curitiba’s Health Districts and other variables of interest. Dental trauma spatial variation was assessed using a generalized additive model in order to identify and control the individual risk-factors and thus determine whether spatial variation is constant or not throughout the Health Districts and the place of residence of individuals. In addition, an analysis was made of the coverage of dental trauma cases taking the spatial distribution of Curitiba’s primary healthcare centres.

“Results: The overall prevalence of dental trauma was 37.1%, with 53.1% in males and 46.7% in females. The spatial analysis confirms the hypothesis that there is significant variation in the occurrence of dental trauma, considering the place of residence in the population studied (Monte Carlo test, p=0,006). Furthermore, 28.7% of cases had no coverage by the primary healthcare centres.

“Conclusions: The effect of the place of residence was highly significant in relation to the response variable. The delimitation of areas, as a basis for case density, enables the qualification of geographical territories where actions can be planned based on priority criteria. Promotion, control and rehabilitation actions, applied in regions of higher prevalence of dental trauma, can be more effective and efficient, thus providing healthcare refinement.”

Estimating a Payment Vehicle for Financing Nourishment of Residential Beaches using a Spatial-Lag Hedonic Property Price Model

In GIS, Modeling, Social Science, Spatial Analysis on July 13, 2010 at 11:07 am

Coastal Management, Volume 38, Issue 1 January 2010 , pages 65 – 75

O. Ashton Morgan and Stuart E. Hamilton

“Beach nourishment projects are common methods for coastal states to protect beaches and property from the natural erosive process. However, while the beneficiaries of beach nourishment tend to be local property owners and recreators, projects are typically funded at the state level. Based on the benefit principle, as local residents receive more of the erosion protection benefits of the nourishment projects, we estimate a value capture tax, designed to levy the financing burden in a manner that approximates the distribution of benefits. The benefits of nourishment projects to coastal property owners are estimated using the results from a spatial-lag hedonic model that controls for viewshed effects.”

Spatial and Temporal Changes in Access Rights to Shellfish Resources in British Columbia

In Environmental Science, GIS, Social Science, Spatial Analysis, Temporal Analysis on July 12, 2010 at 8:43 am

Coastal Management, 1521-0421, Volume 37, Issue 6, 2009, Pages 585 – 616

Alyssa Joyce and Rosaline Canessa

“Over the past decade, the shellfish and finfish aquaculture industry has expanded rapidly in coastal British Columbia (BC) Canada. Foreshore and nearshore shellfish and finfish aquaculture leaseholds are sited in close proximity or in direct competition with habitat for wild shellfish. As a result, some wild shellfish harvesters believe shellfish farms are significantly reducing access to beaches and estuarine areas for wild harvesting, or that salmon farms are contaminating wild shellfish stocks. In this article, Geographic Information Systems (GIS) are used to analyze spatial and temporal trends in the growth of shellfish and finfish aquaculture tenures in BC, while interviews with stakeholders in coastal communities are used to explore user conflicts and the implications of changing access rights on the distribution of marine resources. Qualitative and quantitative findings suggest that shellfish aquaculture provides significant economic opportunities for coastal communities, but that such development may hold increased risk of spatial conflicts over marine habitat as the aquaculture industry continues to grow.”

Video: Using Spatial Analysis to Prioritize Restoration and Facilitate Collaboration

In Environmental Science, GIS, Spatial Analysis, Video on July 8, 2010 at 1:46 pm

Bo Wilmer, Center for Landscape Analysis, Research Department, The Wilderness Society (TWS)

“With thousands of acres of forests in various stages of degradation, choosing the most appropriate areas to restore is a challenging feat. With limited resources and funding, land managers need a way to prioritize these restoration projects. This is where our TWS landscape ecologist Bo Wilmer comes in. He developed a GIS tool that not only helps identify areas for restoration but also better equip the decision-makers in explaining their selection rationale to the public in a simple, intuitive, and transparent framework.”

Where Are My Patients Coming From?

In Conferences, ESRI, GIS, Spatial Analysis on July 8, 2010 at 10:37 am

2010 ESRI Southwest Regional User Group Conference

Kim Dufour

“This presentation will focus on using ArcGIS Desktop to perform spider analyses to better understand geographic patterns in provider/patient relationships. Spider diagrams connect the location of providers with their patients with lines radiating out from the provider location. These analyses can be very useful to healthcare payers and providers for understanding differences in distances traveled for patients in urban and rural locations. For example, this information can be used by Medicare, Medicaid, or insurers to identify areas under-served by a particular type of physician. Further, they help us better understand how far patients may travel when a provider is highly specialized. In addition, these analyses can help us understand geographic patterns between attending physicians and the hospitals in which they treat patients. Spider diagrams are also relevant when looking for potential fraudulent behavior. For example, providers whose patients routinely travel 50 miles or more may be billing for services not rendered. Factors such as specialization and availability of care are critical in such an analysis. The use of ArcGIS provides analysts and executives with clear visualization of provider/patient relationships in order to improve the decision-making process. This presentation is geared for beginner-level users of ArcGIS Desktop and will include a demonstration of the geo-coding using the StreetMap North America data included with the ArcGIS installation disks. It will also include demonstration creating spider diagram.”

A Spatio-Temporal Analysis of Near Repeat Victimization in Japan

In Social Science, Spatial Analysis, Temporal Analysis on July 6, 2010 at 8:56 am

National Research Institute of Police Science, Japan

George Kikuchi, Mamoru Amemiya, Tomonori Saito, Takahito Shimada, and Yutaka Harada

“Recent research in the U.S., Europe, and Australia has consistently identified that the risk of victimization is temporally elevated in areas where crimes have occurred in the recent past. The phenomenon has been termed near repeat victimization. While near repeat victimization has been extensively studied for burglaries, the pattern has also been found for violent offenses such as shooting.

“Analysis of near repeat victimization, however, has caught limited attention among criminologists in Japan, where crime rates are drastically lower than in most western countries. It is quite possible that the volumes of crime may need to be sufficiently large for statistically significant near repeat victimization patterns to occur. On the other hand, if near repeat victimization can be identified in low crime nations such as Japan, such results can be insightful from both theoretical and practical viewpoints. From a practical viewpoint, in particular, the extents of spatial and temporal ranges to which near repeat victimizations are likely to occur can be useful for predictive and focused policing.

“The present study conducted a spatio-temporal analysis of crimes using data on crimes reported to the police in order to identify near repeat victimizations across five crime types (violent offense, purse-snatching, theft from vehicles, business burglary, and residential burglary) in Japan. Crime types were disaggregated in order to identify spatial and temporal ranges of near repeat victimizations which were expected to be crime specific.

“The results have confirmed the risk of near repeat victimization for all crime types, except for violent offenses. The statistically significant results for all property offenses are suggestive in terms of theoretical explanations of near repeat victimization. The paper concludes with a discussion of implications of the findings for both criminological theories and crime prevention activities by the police.”

  • View the presentation [PDF]

    • GIS Identifies Trends in Heart Disease, Cancer, and Diet in the U.S.

    In GIS, Social Science, Spatial Analysis, Statistics on July 6, 2010 at 8:20 am

    Nutrition & Food Science, Volume 39 Issue 1, 2009, pages 59 – 69

    P.B. Brevard and K.R. Brevard

    “Purpose – The purpose of this study is to explore relationships between cardiovascular disease (CVD), cancer (CA), and diet using Geographic Information Systems (GIS) mapping techniques to investigate spatial trends.

    “Design/methodology/approach – Databases containing CVD and CA deaths are listed by state in the USA; databases containing state food consumption statistics, therefore, were sought. Available databases indicating dietary patterns were used to create spatial maps of the USA using ArcGIS (ESRI, Redlands, CA, version 9.2), to visually show trends in relationships among CVD, CA, and diet. Correlations and linear regression were used to determine statistical relationships among variables.

    “Findings – Maps show visual relationships between CVD and CA death rates, and a statistically significant positive correlation (r=0.765; p=0.0005) was also found. Southeastern states have the highest death rates for both diseases. Negative correlations were found between CVD and CA deaths and household expenditure for nuts (r=-0.525; p=0.0005 and r=-0.526; p=0.0005, respectively), and CVD deaths and fruit and vegetable intake (r=-0.423; p=0.002). Household expenditure for nuts was a predictor of CVD (ß=-0.469, p=0.002) and CA (ß=-0.490, p=0.002) deaths.

    “Originality/value – These trends indicate a need for further research on diet and these diseases, and for state-wide dietary studies to facilitate research using GIS mapping. Food consumption patterns, especially nuts, may be related to CVD and CA death rates. Southeastern states should be targeted for nutrition intervention and education programs.”

    Maryland’s Priority Funding Area and the Spatial Pattern of the New Housing Development

    In Modeling, Social Science, Spatial Analysis on July 6, 2010 at 8:14 am

    Scottish Geographical Journal, 1751-665X, Volume 126, Issue 2, 2010, Pages 76 – 100

    Jungyul Sohn and Gerrit Knaap

    “This study attempts to examine whether new urban housing development has been effectively constrained within the Priority Funding Area (PFA) in Maryland, USA. More specifically, it adopts a propensity score approach to the analysis of panel data on housing starts in Maryland between 1998 and 2003, extracted from the MdProperty View Database. While many other relevant studies use features of local housing markets as the indicators of programme success, this empirical analysis can directly examine the number and the location of newly constructed houses for testing the efficacy of the programme thanks to the detailed information available from the Property View dataset. In order to avoid the endogeneity problem associated with designating PFA, probability of being PFA for each census tract is estimated using a probit model and is included in the panel regression model. The findings of the study suggest that residential parcel development continues to expand at the outside of the PFA in the Smart Growth era.”

    Using GIS to Investigate Spatial and Temporal Variations in Upland Rainfall

    In Climate Change, Environmental Science, GIS, GIScience, Spatial Analysis, Temporal Analysis on July 6, 2010 at 6:43 am

    Transactions in GIS, Volume 14 Issue 3, June 2010, p 265-282)

    Emma JS Ferranti, J Duncan Whyatt, Roger J Timmis, and Gemma Davies

    “A method is presented for conditional analysis of spatial and temporal (1961–2007) variations in rainfall under different synoptic situations and different geographic sub-regions, using Cumbria in NW England as a study area. A daily synoptic typing scheme, the Lamb Weather Catalogue, was applied to identify rainfall under three different weather types: south-westerly (SW), westerly (W) and cyclonic (C). Topographic descriptors developed using GIS were used to classify rain gauges into six geographic sub-regions: coastal, windward-lowland, windward-upland, leeward-upland, leeward-lowland, secondary upland. Examining temporal rainfall trends associated with different weather types, in different geographic sub-regions, reveals useful information on changes in rainfall processes. The total rainfall under SW and W weather types is increasing, particularly in upland regions. The increase in SW rainfall is driven by more frequent wet-days, whereas the increase in W rainfall is driven by increases in both wet-day frequency and yield per wet-day. The rainfall under C weather types is decreasing. Combining GIS and synoptic climatology gives insights into rainfall processes under a changing climate. The conditional analysis method can be applied at both local and regional scales, and its success is largely due to the ability of GIS to integrate, visualise, and efficiently model spatial data.”

    The Yield Gap of Global Grain Production: A Spatial Analysis

    In Social Science, Spatial Analysis on July 2, 2010 at 8:08 am

    Agricultural Systems, Volume 103, Issue 5, June 2010, Pages 316-326

    Kathleen Neumann, Peter H. Verburg, Elke Stehfest, and Christoph Müller

    “Global grain production has increased dramatically during the past 50 years, mainly as a consequence of intensified land management and introduction of new technologies. For the future, a strong increase in grain demand is expected, which may be fulfilled by further agricultural intensification rather than expansion of agricultural area. Little is known, however, about the global potential for intensification and its constraints. In the presented study, we analyze to what extent the available spatially explicit global biophysical and land management-related data are able to explain the yield gap of global grain production. We combined an econometric approach with spatial analysis to explore the maximum attainable yield, yield gap, and efficiencies of wheat, maize, and rice production. Results show that the actual grain yield in some regions is already approximating its maximum possible yields while other regions show large yield gaps and therefore tentative larger potential for intensification. Differences in grain production efficiencies are significantly correlated with irrigation, accessibility, market influence, agricultural labor, and slope. Results of regional analysis show, however, that the individual contribution of these factors to explaining production efficiencies strongly varies between world-regions.”

    Visualising Crime Clusters in a Space-time Cube: An Exploratory Data-analysis Approach Using Space-time Kernel Density Estimation and Scan Statistics

    In GIS, GIScience, Spatial Analysis, Statistics, Temporal Analysis on July 2, 2010 at 7:08 am

    Transactions in GIS, Volume 14 Issue 3, June 2010, Pages 219 – 377

    Tomoki Nakaya, Keiji Yano

    “For an effective interpretation of spatio-temporal patterns of crime clusters/hotspots, we explore the possibility of three-dimensional mapping of crime events in a space-time cube with the aid of space-time variants of kernel density estimation and scan statistics. Using the crime occurrence dataset of snatch-and-run offences in Kyoto City from 2003 to 2004, we confirm that the proposed methodology enables simultaneous visualisation of the geographical extent and duration of crime clusters, by which stable and transient space-time crime clusters can be intuitively differentiated. Also, the combined use of the two statistical techniques revealed temporal inter-cluster associations showing that transient clusters alternatively appeared in a pair of hotspot regions, suggesting a new type of “displacement” phenomenon of crime. Highlighting the complementary aspects of the two space-time statistical approaches, we conclude that combining these approaches in a space-time cube display is particularly valuable for a spatio-temporal exploratory data analysis of clusters to extract new knowledge of crime epidemiology from a data set of space-time crime events.”

    On Building and Fitting a Spatio-temporal Change-point Model for Settlement and Growth at Bourewa, Fiji Islands

    In GIS, Modeling, Social Science, Spatial Analysis, Temporal Analysis on June 30, 2010 at 8:10 am

    June 2010; Journal of the Royal Statistical Society: Series C (Applied Statistics) (in review)

    G. K. Nicholls and P. D. Nunn

    “The Bourewa beach site on the Rove Peninsula of Viti Levu is the earliest known human settlement in the Fiji Islands. How did the settlement at Bourewa develop in space and time? We have radiocarbon dates on sixty specimens, found in association with evidence for human presence, taken from pits across the site. Owing to the lack of diagnostic stratigraphy, there is no direct archaeological evidence for distinct phases of occupation through the period of interest. We give a spatio-temporal analysis of settlement at Bourewa in which the deposition rate for dated specimens plays an important role. Spatio-temporal mapping of radiocarbon date intensity is confounded by uneven post-depositional thinning. We assume that the confounding processes act in such a way that the absence of dates remains informative of zero rate for the original deposition process. We model and fit the onset-field, that is, we estimate for each location across the site the time at which deposition of datable specimens began. The temporal process generating our spatial onset-field is a model of the original settlement dynamics.”

    A Multicriteria Spatial Analysis of Erosion Risk into Small Watersheds in the Low Normandy Bocage (France) by ELECTRE III Method Coupled with a GIS

    In Environmental Science, GIS, Spatial Analysis on June 28, 2010 at 6:54 am

    International Journal of Multicriteria Decision Making, 2010 – Vol. 1, No.1 pp. 25 – 48

    Francis Macary, Dominique Ombredane, and Daniel Uny

    “In environmental risk analysis, many explanatory factors, often with highly complex interaction relationships, need to be taken into account. This is the case, for example, in the relation between agricultural practices and the quality of superficial aquatic ecosystems. Suspended solids are responsible for clogging salmonid spawning areas and hence for reductions in their populations. We studied the risks of erosion across two small watersheds in Normandy (France) on the scale of the agricultural plot – the level on which good practices can be applied. Plots were defined according to quantitative as well as qualitative criteria: connectivity to the stream, slope, plant cover, presence of embankments and erosion of the banks in the case of plots beside the river. By combining the ELECTRE III multicriteria analysis method to a geographical information system (GIS), it was possible to discriminate zones that present a risk with respect to particle emission and then to present the results in map form to provide decision-making aid for local actors.”

    Designing a Web Processing Service Application Profile for Spatial Analysis in Business Marketing

    In Spatial Analysis on June 24, 2010 at 8:00 am

    13th AGILE International Conference on Geographic Information Science, Guimarães, Portugal

    Walenciak Georg and  Zipf Alexander

    “This paper deals with the design of a Web Processing Service Application Profile for spatial analysis in business marketing. Since the possibilities of the Web Processing Service Specification 1.0 concerning application profiles are limited, we discuss methods how to enhance the current specification. This shall demonstrate how future Application Profiles might be developed. Therefore we present how a specific application domain can be examined in regard to the spatial analysis being used and how the results could be transferred to an application scheme. The application domain is taken from business analysis. Therefore, the basic requirements concerning spatial analysis in business marketing are being exposed and structured. To illustrate one example in more detail one method is analyzed and its structure is defined. Based on this results some general benefits and limits concerning an OGC Web Processing Service Application Profile are being identified.”

    A Spatial Analysis of Illinois Agricultural Cash Rents

    In GIS, Social Science, Spatial Analysis, Statistics on June 24, 2010 at 5:35 am

    University of Illinois at Urbana-Champaign M.S. Thesis, 2010

    Shannon M. Woodard

    “Following the commodity price shocks in 2007, anecdotal evidence shows that tenant farmers experienced large increases in cropland rental rates and input prices. However, it is unclear how residual profits (crop revenue less non-land costs) resulting from the price increases within this sector (if any) have been allocated among tenant farmers, landowners and input suppliers. This work provides statistical evidence regarding how increases in corn prices and the associated increases in profitability ultimately flow through to the rental market, and which participants benefit the most. The purpose of this paper is to help fill the gap in the existing academic literature with respect to how the recent price shocks affected the agricultural rental market. Using unique farm-level, longitudinal data from the Illinois Farm Bureau Farm Management (FBFM) office, a hedonic model of the determinants of Illinois’ cash rents per acre is constructed and the marginal contributions of parcel characteristics to the market price are derived. A novel spatial econometric panel estimation method is employed to model the spatial error structure and ensure consistent estimators of the model parameters. Lastly, the marginal benefits appropriated by each commodity production participant are estimated and the validity of Ricardian Rent Theory (RRT) is tested. The primary findings indicate that marginal output price increases have a significant effect on cash rents with strong spatial correlations detected in the data. The estimated effect of increasing prices on cropland rents is substantially larger at the farm level, in comparison to a county aggregated model using similar data. County level results find that marginal increases in the harvest futures price increases rents by around $24.00. Under the farm level analysis, this measure rises to over $41.00, perhaps implying that the aggregation process has a significant loss of information. Second, as would be predicted by land rent theories, we find substantiating evidence that both inter-county and intra-county soil productivity variations have considerable impacts on cash rent levels, in that rents are positively associated with higher soil quality. Third, we find that there is a risk premium embedded in the cash rental rate, in that parcels with a higher perceived yield risk result in a negative impact on the cash rent. This is expected given the likely risk aversion of tenant operators. Parcels within relatively rural areas as well as those operated by farmers with large scale operations also exhibit tendencies for higher rent levels, although this impact is rather minimal. Lastly, we find limited support for RRT with a majority of increased revenues due to output price increases accruing to the farmer. Tenant farmers capture 89% of the marginal increases in commodity prices while the landowner and input suppliers absorb only 3.3% and 7.7%, respectively. The relatively large amount that is captured by the tenant farmer may be a form of ‘compensation’ for bearing price risk. This would imply that tenant farmers cash renting cropland receive both a premium for yield risk as well as price risk.”

    Predictive Spatial Analysis of Marine Mammal Habitats

    In Environmental Science, Modeling, Spatial Analysis on June 23, 2010 at 6:49 am

    Report Number A326025, January 2010, 296 pages

    Andrew Read; Patrick Halpin; Benjamin Best; Ei Fujioka; Caroline Good; Lucie Hazen; Erin LaBrecque; Song Qian; Robert Schick; Duke University Beaufort NC Marine Lab

    “We developed a data management, statistical modeling and decision support system describing habitat use of marine mammals in the North Atlantic and Gulf of Mexico. Our objective was to make this information available in a comprehensive manner to environmental planners and decision makers in the Navy and elsewhere. The system uses data on the distribution of marine mammals from dedicated surveys contained in the online OBIS-SEAMAP marine data archive. We used these data to develop predictive habitat models for guilds of marine mammals in these two regions. We delivered model outputs in an online, flexible Spatial Decision Support System (SDSS). The SDSS is a browser-based, interactive mapping application that enables users to view model results with original survey effort and marine mammal observations. In total, we generated 33 models, representing 16 cetacean guilds, using environmental data from the JPL physical oceanographic data archive. Predictive maps for the likelihood of encounter with marine mammals comprise the results, along with estimates of standard errors.”

    Human Helminth Co-Infection: Analysis of Spatial Patterns and Risk Factors in a Brazilian Community

    In Environmental Science, Science, Social Science, Spatial Analysis, Statistics on June 23, 2010 at 5:52 am

    PLoS Neglected Tropical Diseases: 2(12), 2008

    Rachel L. Pullan1, Jeffrey M. Bethony, Stefan M. Geiger, Bonnie Cundill, Rodrigo Correa-Oliveira, Rupert J. Quinnell, and Simon Brooker

    “Background: Individuals living in areas endemic for helminths are commonly infected with multiple species. Despite increasing emphasis given to the potential health impacts of polyparasitism, few studies have investigated the relative importance of household and environmental factors on the risk of helminth co-infection. Here, we present an investigation of exposure-related risk factors as sources of heterogeneity in the distribution of co-infection with Necator americanus and Schistosoma mansoni in a region of southeastern Brazil.

    “Methodology: Cross-sectional parasitological and socio-economic data from a community-based household survey were combined with remotely sensed environmental data using a geographical information system. Geo-statistical methods were used to explore patterns of mono- and co-infection with N. americanus and S. mansoni in the region. Bayesian hierarchical models were then developed to identify risk factors for mono- and co-infection in relation to community-based survey data to assess their roles in explaining observed heterogeneity in mono and co-infection with these two helminth species.

    “Principal Findings: The majority of individuals had N. americanus (71.1%) and/or S. mansoni (50.3%) infection; 41.0% of individuals were co-infected with both helminths. Prevalence of co-infection with these two species varied substantially across the study area, and there was strong evidence of household clustering. Hierarchical multinomial models demonstrated that relative socio-economic status, household crowding, living in the eastern watershed and high Normalized Difference Vegetation Index (NDVI) were significantly associated with N. americanus and S. mansoni co-infection. These risk factors could, however, only account for an estimated 32% of variability between households.

    “Conclusions: Our results demonstrate that variability in risk of N. americanus and S. mansoni co-infection between households cannot be entirely explained by exposure-related risk factors, emphasizing the possible role of other household factors in the heterogeneous distribution of helminth co-infection. Untangling the relative contribution of intrinsic host factors from household and environmental determinants therefore remains critical to our understanding of helminth epidemiology.”

    Spatio-temporal Analysis on Nutritional Condition of Engraulis Anchoita Larvae: Its Relation with Hydrographical Features of Nursery Grounds and Food Availability

    In Environmental Science, Spatial Analysis, Temporal Analysis on June 21, 2010 at 8:46 am

    Tesis En Ciencias Marinas, Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, 2010

    M.V. Díaz

    “Nutritional condition studies allow the assessment of physiological state of each larva and thus, the establishment of favourable nursery areas which provide better survival and growth. In the present work, morphometrical, histological and biochemical techniques were employed to assess nutritional condition of anchovy, Engraulis anchoita, larvae captured in the Argentine Sea. Its results were complemented with oceanographic data and information about zooplankton abundances, both prey and predators of anchovy larvae. Anchovy larvae abundance and distribution would be mainly determined by physico-chemical variables. Even though no significant differences were found in larval nutritional condition among the studied areas, larval condition was slightly better in frontal areas characterized by mixed water masses. On the other hand, anchovy larvae condition seems to be favoured during seasons when larval abundances remain low. Probably, ocean conditions are almost always favourable for larval growth and survival during the whole year, but low or intermediate larval densities allow avoiding both intra and inter-specific competition. As only a small number of anchovy larvae were described as in starving condition, it can be assumed that E. anchoita, finds environmental conditions that favour its growth and survival. during all seasons in the studied area.”

    Spatial Analysis of Breast Cancer Incidence, Dietary Patterns, and Diet Cost in the UK

    In Science, Social Science, Spatial Analysis on June 21, 2010 at 8:12 am

    Faculty of Medicine and Health Graduate School, University of Leeds

    Supervisors: Professor J Cade, Dr K Edwards and Dr C Hulme

    Breast cancer is one of the more frequent cancers in developed countries (Stewart & Kleihues, 2003). The burden of cancer can most effectively be reduced by implementing lifestyle and environmental changes to prevent the disease, rather than through treatment reducing mortality (Danaei et al, 2005). Up to 30% of human cancers are probably related to diet and nutrition (Key et al, 2002).

    Energy dense diets are associated with lower diet quality and lower costs, and vice versa (Drewnoski et al, 2007). Research shows that low income households are associated with a high energy dense diet (Mendoza et al, 2006). Thus there may be an association between diet cost and breast cancer risk. UK studies have shown that there is a comparable rise in incidence of breast cancer across all socio-economic groups, thus retaining the disparity between affluent and deprived (Brown et al, 2007; Rowan, 2007).

    Accordingly the objectives of this study are as follows:

  • Describe, measure and map breast cancer incidence across England, using national cancer registry data and, separately, data from the UK Women’s Cohort study.
  • Describe, measure and map geographical variations in diet and nutrition, and dietary patterns, in England using data from the UK Women’s Cohort study.
  • Analyse the geographical relationship between breast cancer and diet, adjusting for potentially confounding factors.
  • Calculate the cost of diet for each cohort member and thus the cost of each spatial dietary pattern.
  • Examine the relationship between nutrient consumption, food intake and diet cost.
  • Assess relationship between diet cost and breast cancer risk in England.

    • This project will combine medical, social, and economic criteria to determine classifications of dietary patterns and diet cost, thus strengthening the existing evidence base. Data will be used from the UK Women’s Cohort Study (Cade et al, 2004). A novel aspect of data available from this study is an estimated cost of the diet. This is not available on any other similar UK Cohort.

    Funding Notes
    Applications are invited for a 3 year PhD Studentship commencing September/October 2010. The Studentship will attract an annual tax free stipend of £13.590 and tuition fees. Open to UK students and EU students meeting the ESRC residency criteria (available on the ESRC website).

    Interested applicants should hold a minimum of a relevant UK honours degree at 2.1 level or equivalent. Informal enquries – Dr Kimberley Edwards (telephone: 0113 343 8914 or email: k.l.edwards@leeds.ac.uk)

    To apply for this studentship applicants should submit; personal statement, CV (including details of two academic referees) and degree transcripts to Dr Kimberley Edwards (email: k.l.edwards@leeds.ac.uk).

    References

    • Brown SBF, Hole DJ, Cooke TG (2007). Breast cancer incidence trends in deprived and affluent Scottish women. Breast Cancer Research & Treatment 103(2): 233-8.
    • Cade JE, Burley VJ, Greenwood DC (2004). The UK Women’s Cohort Study: comparison of vegetarians, fish-eaters and meat-eaters. Public Health Nutr 7: 871–8
    • Danaei G, Vander Hoorn S, Lopez AD, Murray CJL, Ezzati M, the Comparative Risk Assessment collaborating group (cancers) (2005). Causes of cancer in the world: comparative risk assessment of nine behavioural and environmental risk factors. The Lancet, 366: 1784
    • Drewnowski A, Monsivais P, Maillot M, Darmon N (2007). Low-energy-density diets are associated with higher diet quality and higher diet costs in French adults. Journal of the American Dietetic Association 107(6): 1028-32.
    • Key T, Allen N, Spencer E, Travis R (2002). The effect of diet on risk of cancer. The Lancet, 360 (9336): 861-868
    • Mendoza JA, Drewnowski A, Cheadle A, Christakis DA (2006). Dietary energy density is associated with selected predictors of obesity in U.S. Children. Journal of Nutrition 136(5): 1318-22.
    • Rowan S, for the Office of National Statistics (2007). Trends in cancer incidence by deprivation, England and Wales, 1990–2002. Health Statistics Quarterly 36
    • Stewart BW & Kleihues P (Eds) (2003). WHO: World Cancer Report. IARC Press. Lyon

    Methodology for Spatial and Temporal Analysis of Drought using Large-scale Gridded Data

    In Climate Change, Environmental Science, Spatial Analysis, Statistics, Temporal Analysis on June 18, 2010 at 6:21 am

    Geophysical Research Abstracts, Vol. 12, EGU2010-12703-1, 2010

    Gerald A Corzo P, Marjolein H.J. van Huijgevoort, and Henny A.J. van Lanen

    “In recent years, there is an increased understanding of the importance of drought, in particular due to global change. For a good understanding of historic droughts, and to evaluate the impact of future global change scenarios, more advanced techniques to account for spatio-temporal variability are required. So far, methodologies to characterize spatio-temporal patterns of large-scale drought (e.g. global scale) are still limited. This explorative work presents methodological processes developed to analyze a gridded dataset with forcing data that has been compiled through the EU-FP6 WATCH project (0.5o, daily, 1958-2001). Two new methodologies are proposed: the Standardized Clustered Precipitation Index (SCPI), which quantifies monthly precipitation changes, and the Cluster Precipitation Distributions (CPDs) which consider the spatial reduction of continuous period without daily rain. Both methods are used to characterize meteorological drought. The SCPI methodology is an extension of the Standardized Precipitation Index (SPI) that incorporates a multivariate clustering analysis to determine the spatial changes of the index and the rate of change. The SPIs are calculated based on a monthly moving average of a specified length (e.g. 30 days), and their variability is calculated in k years to identify a change in the SPI levels. To determine this k-years change, a monthly spatial pattern of severity is calculated in the time frame defined in the calculation of the SPI. A second method is presented (i.e. CPD) to prepare for analysis of hydrological drought in a next phase of this research. CPD identifies spatial regions where probabilities of longer periods of non-precipitation events are present. These probability distributions, however, do not consider geographical positioning which may affect drought analysis of a particular region. Therefore, the probabilities of non-precipitation events are grouped using a clustering technique that allows for geo-referenced information. The two methodologies provide important information for principles that can be used to develop methods to evaluate meteorological and subsequently hydrological drought from different types of large-scale grid-based models (e.g. RCMs, LSHMs, GHMs).”

    Seasonal Rainfall Variability in Guinea Savanna, Nigeria: A GIS Approach

    In Climate Change, GIS, Spatial Analysis, Statistics, Temporal Analysis on June 17, 2010 at 9:04 am

    International Journal of Climate Change Strategies and Management, Volume: 1; Issue: 3; 2009

    Ayansina Ayanlade

    “Purpose – This paper aims to use geographical information systems kriging interpolation technique to examine and map the spatiotemporal variation in rainfall in Guinea Savanna of Nigeria.

    “Design/methodology/approach – Rainfall data, for the periods between 1970 and 2000, are collected from the archives of the Nigerian Meteorological Services, Oshodi Lagos. In this paper, rainfall is considered as the primary and input for crop yield. It is observed that the most important climatic element is rainfall; particularly inter-annual variation and the spatiotemporal distribution of rainfall. Three spatial interpolation methods are chosen for this research work: inverse distance weighting method and the spline (completely regularized) as the determinist methods; and ordinary kriging as the stochastic methods. In order to analyze the interpolation quality, an evaluation by cross validation has been carried out. Ordinary kriging method was discovered suitable for this paper because it allows the sharpest interpolation rainfall data and is the most representative.

    “Findings – The results of the analysis show that rainfall varies both in time and space. Rainfall variability is very high in most of Northern Guinea Savanna (e.g. Yola, Minna, and Ilorin) with values of coefficient of variation (CV) between 26 and 49 percent while in Southern Guinea Savanna, the CV is very low especially, in Enugu (9 percent), and Shaki (8 percent). These anomalies (such as decline in annual rainfall, change in the peak and retreat of rainfall and false start of rainfall) are detrimental to crop germination and yield, resulting in little or no harvest at the end of the season.

    “Originality/value – The paper concludes that geospatial techniques are powerful tools that should be explored further for realistic analysis of the effects of seasonal variability in rainfall.”

    Potential Biases due to Geocoding Error in Spatial Analyses of Official Data

    In GIS, Social Science, Spatial Analysis on June 15, 2010 at 6:37 am

    Health & Place, Volume 15, Issue 2, June 2009, Pages 562-567

    Geoff Hay, Kypros Kypri, Peter Whigham, and John Langley

    “Geospatial methods have been used extensively to examine associations between alcohol outlet density and various harms; however, the literature offers too little methodological detail to assess possible geocoding biases in these studies. We used New Zealand liquor licensing and crime data to assess geocoding error. For the year with the best data, 69% of offences could be accurately mapped (91% of those in urban areas, 38% in rural areas). There was considerable urban–rural variation in the accuracy and specificity of location data. If similar error exists in other jurisdictions, previous findings may be biased. Greater consideration should be given to the effects of data quality in geospatial studies, and geocoding methods should be reported explicitly.”

    Spatial Analysis of Trace Fossils for Paleogeographic Studies

    In Environmental Science, Spatial Analysis, Statistics on June 14, 2010 at 9:18 am

    13th AGILE International Conference on Geographic Information Science 2010, Guimarães, Portugal

    Paula Redweik, Joel Dinis, Edgar Barreira, Mário Cachão, Cristina Catita, Ana Santos, Eduardo Mayoral, Carlos M.da Silva, and Wilfried Linder

    “Understanding the spatial distribution of species is a fundamental issue in paleontology. Nevertheless, exhaustive quantitative descriptions of specimen distributions are rare. In this paper, a method is described for systematic acquiring and analyzing images of trace fossils of two species, Gastrochaenolites lapidicus and Gastrochaenolites torpedo, existing in Foz da Fonte (Sesimbra, Portugal) and investigate their spatial patterns. The procedures of field data acquisition and statistical analysis are described and the presented results are discussed. Emphasis is placed in close-range photogrammetry methods for data acquisition and spatial statistics for data analysis. Goals of the analysis are focused on the statistical description of the fossil species population, the investigation of some spatial relationship among groups of G.lapidicus of different dimensions, and finally the investigation of a preferential orientation of the G.torpedo population in order to draw paleogeographic/environmental conclusions. Feature extraction is done on the produced orthophotos of the site. The main results of this study revealed that both G.lapidicus and G.torpedo populations were significantly clustered during life. Furthermore, the preferential cluster location of different diameter classes of G.lapidicus on the surveyed block indicates the relative location and orientation of the paleoshore in this site 18 millions years ago.”

    An Enhanced Two-step Floating Catchment Area (E2SFCA) Method for Measuring Spatial Accessibility to Primary Care Physicians

    In Social Science, Spatial Analysis on June 14, 2010 at 5:52 am

    Health & Place, Volume 15, Issue 4, December 2009, Pages 1100-1107

    Wei Luo and Yi Qi

    “This paper presents an enhancement of the two-step floating catchment area (2SFCA) method for measuring spatial accessibility, addressing the problem of uniform access within the catchment by applying weights to different travel time zones to account for distance decay. The enhancement is proved to be another special case of the gravity model. When applying this enhanced 2SFCA (E2SFCA) to measure the spatial access to primary care physicians in a study area in northern Illinois, we find that it reveals spatial accessibility pattern that is more consistent with intuition and delineates more spatially explicit health professional shortage areas. It is easy to implement in GIS and straightforward to interpret.”

    Spatio-temporal Analysis in Environmental Health: Respiratory Medication in Relation to Air Pollution and Deprivation

    In Environmental Science, Science, Social Science, Spatial Analysis, Temporal Analysis on June 11, 2010 at 8:45 am

    Paper submitted for INSPIRE 2010

    Eleni Sofianopoulou, Stephen Rushton, and Tanja Pless-Mulloli

    “Numerous spatial health data are collected by Primary Health Care that is provided by General Practices (GPs) in England. However their utility in environmental epidemiology is limited because they are not linked to environmental datasets. A main cause to linkage complexity is related to the fact that there are no formal boundaries that depict GP service areas, as patients can register to any GP practice of their preference. A second cause is the dissimilar spatial units that the environmental and socioeconomic data are provided in. As a consequence a source of environmental health information is under-exploited. We aimed to define a spatial unit that depicts a GP service area and examine whether the prescribing of respiratory medication per GP is related to air quality and deprivation observed within GP service areas. The two most common chronic respiratory diseases are asthma and Chronic Obstructive Pulmonary Disease (COPD). Monitoring their prevalence, risk factors and determinants is an important public health task in developing and developed countries. In England, short-acting β2-agonists is the most often prescribed medication for asthma and COPD , 93% of which is represented by salbutamol. We aimed to investigate the monthly salbutamol prescribing rate in relation to Particulate matter (PM10), traffic flows and deprivation (income, education, employment). The aim of this study is quite timely as it covers the objectives of policies relevant to exploitation of spatial data and re-use of public sector data. This study both utilises existent spatial datasets as well as re-use information from the National Health System (NHS) and Local Authorities, in a neoteric way.”

    Stress and the Designed Environment

    In Design, Social Science, Spatial Analysis on June 11, 2010 at 5:41 am

    Journal of Social Issues, Volume 37 Issue 1, Pages 145 – 171, Published Online 14 Apr 2010

    Craig M. Zimring

    “This paper focuses on ways that the design of the physical environment affects important individual goals, such as appropriate levels of social interaction and wayfinding and spatial orientation. A preliminary framework is proposed that suggests that the design of the environment causes stress by affecting person-environment fit. Next, the role of the physical environment in the regulation of social interaction and in wayfinding and spatial orientation is discussed. Finally, several suggestions for future research are presented.”

    Spatial Clustering and the Temporal Mobility of Walking School Trips in the Greater Toronto Area, Canada

    In Social Science, Spatial Analysis, Temporal Analysis on June 10, 2010 at 1:35 pm

    Health & Place, Volume 16, Issue 4, July 2010, Pages 646-655

    Raktim Mitra, Ron N. Buliung, and Guy E.J. Faulkner

    “Interest in utilitarian sources of physical activity, such as walking to school, has emerged in response to the increased prevalence of sedentary behavior in children and youth. Public health practitioners and urban planners need to be able to survey and monitor walking practices in space and time, with a view to developing appropriate interventions. This study explored the prevalence of walking to and from school of 11–13 year olds in the Greater Toronto Area (GTA), Canada. The Getis–Ord (Gi*) local spatial statistic, Markov transition matrices, and logistic regressions were used to examine the spatial clustering of walking trips in the study area, and to document any temporal drift of places in and out of walking clusters. Findings demonstrate that walking tends to cluster within the urban and inner-suburban GTA, and in areas with low household income. Temporally persistent cluster membership was less likely within inner-suburban and outer-suburban places. The evidence suggests that interventions to increase active school transportation need to acknowledge spatial and temporal differences in walking behavior.”

    Spatial Distribution and Content of Soil Organic Matter in an Agricultural Field in Eastern Canada, as Estimated from Geostatistical Tools

    In Environmental Science, Spatial Analysis, Statistics on June 10, 2010 at 9:28 am

    Earth Surface Processes and Landforms, Volume 35, Issue 3, Date: 15 March 2010, Pages: 278-283

    Lionel Mabit and Claude Bernard

    “Soil erosion induces soil redistribution within the landscape and thus contributes to the spatial variability of soil quality. This study complements a previous experimentation initiated by the authors focusing on soil redistribution as a result of soil erosion, as indicated by caesium-137 (137Cs) measurements, in a small agricultural field in Canada.

    “The spatial variability of soil organic matter (SOM) was characterized using geostatistics, which consider the randomized and structured nature of spatial variables and the spatial distribution of the samples. The spatial correlation of SOM (in percentages) patterns in the topsoil was established taking into account the spatial structure present in the data. A significant autocorrelation and reliable variograms were found with a R2 0·9, thus demonstrating a strong spatial dependence.

    “Ordinary Kriging (OK) interpolation provided the best cross validation (r2 = 0·35). OK and inverse distance weighting power two (IDW2) interpolation approaches produced similar estimates of the total SOM content of the topsoil (0-20 cm) of the experimental field, i.e. 211 and 213 tonnes, respectively. However, the two approaches produced differences in the spatial distribution patterns and the relative magnitude of some SOM content classes.

    “The spatialization of SOM and soil redistribution variability – as evidenced by 137Cs measurements – is a first step towards the assessment of the impact of soil erosion on SOM losses to recommend conservation measures. “

    Relationship Between Neighborhood Socioeconomic Status and Food and Alcohol Access–An Ecological Study

    In Social Science, Spatial Analysis, Statistics on June 10, 2010 at 6:19 am

    American Public Health Association Annual Meeting and Expo

    Session: “Mapping and Spatial Analysis of the Food Environment”

    Monday, November 8, 2010: 9:30 a.m.

    Scott Shimotsu, Rhonda Jones-Webb, Richard F. MacLehose, and Toben F. Nelson

    “Purpose: The neighborhoods where people live can shape the dietary and alcohol choices they make. Poor neighborhoods tend to have fewer resources for promoting good health, but it is not know whether neighborhood access to food and alcohol are related, and whether the relationship between food and alcohol access differs by socioeconomic status. The purpose of this study is to examine whether access to supermarkets and grocery stores is associated with access to liquor stores and whether this relationship differs by neighborhood socioeconomic status.

    “Methods: Data for this study were drawn from the U.S. Census and InfoUSA Business Datasets (2002) which were linked by census tract areas. Neighborhoods were defined as census tracts within Hennepin County, Minnesota. Census 2000 was used to assess neighborhood socioeconomic status. InfoUSA data were used to estimate counts of 3318 food and liquor stores. Measures of socioeconomic position included education, employment status, median household income, and poverty level. Poisson models were used to estimate effects and included zero-inflated poisson models.

    “Results: Higher counts of liquor stores were positively associated with counts of supermarkets and grocery stores after adjusting for socioeconomic status (RR=1.36, 95% CI: 1.20, 1.55). Lower counts of supermarkets and grocery stores were associated with lower income neighborhoods (RR=0.98, 95% CI: 0.95, 0.99). The relationship between access to liquor stores and grocery stores did not vary by socioeconomic status (p=0.89).

    “Discussion: Food and liquor stores tend to cluster together in neighborhoods. Future studies should examine the mechanisms through which food and liquor stores co-occur.”

    Spatial Analysis of Leishmania Donovani Exposure in Humans and Domestic Animals in a Recent Kala Azar Focus in Nepal

    In Environmental Science, Spatial Analysis on June 9, 2010 at 11:34 am

    Parasitology, 2010 May 12:1-7

    Khanal B, Picado A, Bhattarai NR, VAN DER Auwera G, DAS ML, Ostyn B, Davies CR, Boelaert M, Dujardin JC, Rijal S.

    “Visceral leishmaniasis (VL) is a major public health problem in the Indian subcontinent where the Leishmania donovani transmission cycle is described as anthroponotic. However, the role of animals (in particular domestic animals) in the persistence and expansion of VL is still a matter of debate. We combined Direct Agglutination Test (DAT) results in humans and domestic animals with Geographic Information System technology (i.e. extraction maps and scan statistic) to evaluate the exposure to L. donovani on these 2 populations in a recent VL focus in Nepal. A Poisson regression model was used to assess the risk of infection in humans associated with, among other factors, the proportion of DAT-positive animals in the proximities of the household. The serological results showed that both humans and domestic animals were exposed to L. donovani. DAT-positive animals and humans were spatially clustered. The presence of serologically positive goats (IRR=9.71), past VL cases (IRR=2.62) and the proximity to a forest island dividing the study area (IRR=3.67) increased the risk of being DAT-positive in humans. Even if they are not a reservoir, domestic animals, and specially goats, may play a role in the distribution of L. donovani, in particular in this new VL focus.”

    Quote of the Day

    In Climate Change, Design, Environmental Science, Quotes, Spatial Analysis on June 9, 2010 at 10:32 am

    “It is not enough just to assess an installation’s impact on the environment; one must also assess the impact of a changing environment on the installation. “

    – Cleo Paskal, Columnist and Adjunct Professor, Global Change, SCMS, Kochi, India [source]

    Grocery Store Location in an Urban Multiethnic Community: Mapping the Relations to Food Access, Obesity and Diabetes in an Underserved Community

    In GIS, Social Science, Spatial Analysis on June 9, 2010 at 7:43 am

    American Public health Association Annual Meeting and Expo

    Session: “Mapping and Spatial Analysis of the Food Environment”

    Monday, November 8, 2010: 8:30 a.m.

    Millicent Fleming-Moran

    “Introduction: Social determinants of health include consumers’ ready access to affordable, nutritious food, including full-service groceries, but minority and high-poverty communities are less likely to have accessible national chain groceries. Indianapolis in 2008-09 was ranked among the top 25 foodhardship MSAs [19.9% families/past year].

    “Methods: Marion County, IN 2005 RDD survey of 4,787 respondents queried fruit and vegetable consumption, self-reported BMI and diabetes status of adults. These data, grocery inspection, and GIS census data allowed mapping analysis of the relations between high density poverty/minority areas and locations of full-service groceries per 1,000 population [with daily available wide variety of fresh produce, dairy and meat/poultry/fish items], convenience marts and licensed soup kitchens/food pantries. National chain stores were rare in high-poverty areas and most full service stores in poorer communities were locally and minority owned. The latter allowed over 94% of county adults to report access to fresh produce. However obesity and diabetes prevalence rates were greatest in areas served primarily by convenience stores and social-service/faith-based food pantries. These findings provide data for local nutrition-equity advocates, such as fiscal incentives for grocery placement; transportation strategies, local food co-ops and other mechanisms to increase community access to available grocery supplies.

    “Implications: Social costs of low grocery availability in high-poverty census tracts are borne not only in affected communities’ prevalence of obesity and diabetes, but also increases the likelihood of food insecurity in the broader population. “

    A Spatial Bayesian Approach to Weather Derivatives

    In Environmental Science, Spatial Analysis, Statistics on June 9, 2010 at 7:01 am

    Agricultural Finance Review, 2010, Volume 70, Issue 1, Pages 79 – 96

    Nicholas D. Paulson, Chad E. Hart, and Dermot J. Hayes

    “Purpose – While the demand for weather-based agricultural insurance in developed regions is limited, there exists significant potential for the use of weather indexes in developing areas. The purpose of this paper is to address the issue of historical data availability in designing actuarially sound weather-based instruments.

    “Design/methodology/approach – A Bayesian rainfall model utilizing spatial kriging and Markov chain Monte Carlo techniques is proposed to estimate rainfall histories from observed historical data. An example drought insurance policy is presented where the fair rates are calculated using Monte Carlo methods and a historical analysis is carried out to assess potential policy performance.

    “Findings – The applicability of the estimation method is validated using a rich data set from Iowa. Results from the historical analysis indicate that the systemic nature of weather risk can vary greatly over time, even in the relatively homogenous region of Iowa.

    “Originality/value – The paper shows that while the kriging method may be more complex than competing models, it also provides a richer set of results. Furthermore, while the application is specific to forage production in Iowa, the rainfall model could be generalized to other regions by incorporating additional climatic factors.”

    Changes in Croplands as a Result of Large Scale Mining and the Associated Impact on Food Security Studied Using Time-Series Landsat Images

    In Environmental Science, Imagery, Social Science, Spatial Analysis, Temporal Analysis on June 9, 2010 at 6:43 am

    Remote Sensing 2010, 2, 1463-1480

    Lubos Matejicek and Veronika Kopackova

    “Geographic information systems and satellite remote sensing information are emerging technologies in land-cover change assessment. They now provide an opportunity to gain insights into land-cover change properties through the spatio-temporal data capture over several decades. The time series of Landsat images covering the 1985–2009 period is used here to explore the impacts of surface mining and reclamation, which constitute a dominant force in land-cover changes in the northwestern regions of the Czech Republic. Advanced quantification of the extent of mining activities is important for assessing how these land-cover changes affect ecosystem services such as croplands. The images employed from 1985, 1988, 1990, 2000, 2002, 2003, 2004, 2005, 2006, 2007, 2008, and 2009 assist in mapping the extent of surface mines and mine reclamation for large surface mines in a few selected areas of interest. The image processing techniques are based on pixel-by-pixel calculation of the vegetation index, such as NDVI. The NDVI values are classified into the defined classes based on CORINE Land Cover 2000 data in a 3280 km2 strip of Landsat images. This distribution of NDVI values is used to estimate the land-cover classes in the local areas of interest (184 km2, 368 km2, 737 km2, and 1,474 km2). Thus, the approximate land-cover stability of the 3,280 km2 strip during the whole 1985–2009 period is used to explore land-cover disturbances in the local areas of surface mines. In the case of NDVI, it also includes variations, presumably caused by seasonal vegetation effects, and local meteorological conditions. However, the main trends related to mining activities during the long-term period can be clearly understood. As a result, other objectives can be explored in the 1985–2009 period, such as cropland changes to other land use classes, changes of cropland patterns, and their impacts on food security. The presented spatio-temporal modeling based on long time series from 12 satellite images provides considerable experience for processing NDVI in the framework of identification of land-cover classes and also, to a certain degree, cropland variability with its impact on food security.”

    Is the Spatial Distribution of Mankind’s Most Basic Economic Traits Determined by Climate and Soil Alone?

    In Environmental Science, GIS, Geography, Social Science, Spatial Analysis on June 8, 2010 at 10:06 am

    PLoS ONE 5(5): May 5, 2010

    Jan Beck and Andrea Sieber

    “Several authors, most prominently Jared Diamond (1997, Guns, Germs and Steel), have investigated biogeographic determinants of human history and civilization. The timing of the transition to an agricultural lifestyle, associated with steep population growth and consequent societal change, has been suggested to be affected by the availability of suitable organisms for domestication. These factors were shown to quantitatively explain some of the current global inequalities of economy and political power. Here, we advance this approach one step further by looking at climate and soil as sole determining factors.”

    Eigenplaces: Analysing Cities Using the Space – Time Structure of the Mobile Phone Network

    In Geography, Social Science, Spatial Analysis, Temporal Analysis on June 8, 2010 at 8:36 am

    Environment and Planning B: Planning and Design 2009, volume 36, pages 824 ^ 836

    Jonathan Reades, Francesco Calabrese, and Carlo Ratti

    “Several attempts have already been made to use telecommunications networks for urban research, but the datasets employed have typically been neither dynamic nor fine grained. Against this research backdrop the mobile phone network offers a compelling compromise between these extremes: it is both highly mobile and yet still localisable in space. Moreover, the mobile phone’s enormous and enthusiastic adoption across most socioeconomic strata makes it a uniquely useful tool for conducting large-scale, representative behavioural research. In this paper we attempt to connect telecoms usage data from Telecom Italia Mobile (TIM) to a geography of human activity derived from data on commercial premises advertised through Pagine Gialle, the Italian `Yellow Pages’. We then employ eigendecomposition–a process similar to factoring but suitable for this complex dataset–to identify and extract recurring patterns of mobile phone usage. The resulting eigenplaces support the computational and comparative analysis of space through the lens of telecommuniations usage and enhance our understanding of the city as a `space of flows’.”

    Characterization of Complex Fluvial Systems using Remote Sensing of Spatial and Temporal Water Level Variations in the Amazon, Congo, and Brahmaputra Rivers

    In Environmental Science, Imagery, Spatial Analysis, Temporal Analysis on June 7, 2010 at 11:53 am

    Earth Surface Processes and Landforms, Volume 35, Issue 3, Date: 15 March 2010, Pages: 294-304

    Hahn Chul Jung, James Hamski, Michael Durand, Doug Alsdorf, Faisal Hossain, Hyongki Lee, A. K. M. Azad Hossain, Khaled Hasan, Abu Saleh Khan, and A.K.M. Zeaul Hoque

    “The Surface Water and Ocean Topography (SWOT) satellite mission will provide global, space-based estimates of water elevation, its temporal change, and its spatial slope in fluvial environments, as well as across lakes, reservoirs, wetlands, and floodplains. This paper illustrates the utility of existing remote sensing measurements of water temporal changes and spatial slope to characterize two complex fluvial environments. First, repeat-pass interferometric SAR measurements from the Japanese Earth Resources Satellite are used to compare and contrast floodplain processes in the Amazon and Congo River basins. Measurements of temporal water level changes over the two areas reveal clearly different hydraulic processes at work. The Amazon is highly interconnected by floodplain channels, resulting in complex flow patterns. In contrast, the Congo does not show similar floodplain channels and the flow patterns are not well defined and have diffuse boundaries. During inundation, the Amazon floodplain often shows sharp hydraulic changes across floodplain channels. The Congo, however, does not show similar sharp changes during either infilling or evacuation. Second, Shuttle Radar Topography Mission measurements of water elevation are used to derive water slope over the braided Brahmaputra river system. In combination with in situ bathymetry measurements, water elevation and slope allow one to calculate discharge estimates within 2.3% accuracy. These two studies illustrate the utility of satellite-based measurements of water elevation for characterizing complex fluvial environments, and highlight the potential of SWOT measurements for fluvial hydrology.”

    The Spatial Structure of Autism in California, 1993–2001

    In GIS, Spatial Analysis on June 7, 2010 at 8:54 am

    Health & Place, Volume 16, Issue 3, May 2010, Pages 539-546

    Soumya Mazumdar, Marissa King, Ka-Yuet Liu, Noam Zerubavel, and Peter Bearman

    “This article identifies significant high-risk clusters of autism based on residence at birth in California for children born from 1993 to 2001. These clusters are geographically stable. Children born in a primary cluster are at four times greater risk for autism than children living in other parts of the state. This is comparable to the difference between males and females and twice the risk estimated for maternal age over 40. In every year roughly 3% of the new caseload of autism in California arises from the primary cluster we identify—a small zone 20 km by 50 km. We identify a set of secondary clusters that support the existence of the primary clusters. The identification of robust spatial clusters indicates that autism does not arise from a global treatment and indicates that important drivers of increased autism prevalence are located at the local level.”

    Ocean of Information: Fusing Aggregate & Individual Dynamics for Metropolitan Analysis

    In Geography, Social Science, Spatial Analysis, Temporal Analysis on June 7, 2010 at 8:37 am

    International Conference on Intelligent User Interfaces, Proceeding of the 14th international conference on Intelligent user interfaces, Hong Kong, China, 2010

    Mauro Martino, Francesco Calabrese, Giusy Di Lorenzo, Clio Andris, Liu Liang, and Carlo Ratti

    “In this paper, we propose a tool to explore human movement dynamics in a Metropolitan Area. By analyzing a mass of individual cell phone traces, we build a Human-City Interaction System for understanding urban mobility patterns at different user-controlled temporal and geographic scales. We solve the problems that are found in available tools for spatio-temporal analysis, by allowing seamless manipulability and introducing a simultaneous\multi-scale visualization of individual and aggregate flows. Our tool is built to support the exploration and discovery of urban mobility patterns and the daily interactions of millions of people. Moreover, we implement an intelligent algorithm to evaluate the level of mobility homophily of people moving from place to place.”

    Impact of the Spatial and Temporal Arrangement of Pastoral Use on Land Degradation around Animal Concentration Points

    In Environmental Science, Modeling, Spatial Analysis, Temporal Analysis on June 4, 2010 at 10:01 am

    Land Degradation & Development, Volume 21, Issue 3, Date: May/June 2010, Pages: 248-259

    T. Okayasu, T. Okuro, U. Jamsran, and K. Takeuchi

    “In mobile pastoral systems, the spatial movement of herders is tied to requirements such as water, markets and medical services, resulting in the concentration of livestock in particular areas and subsequent desertification in those areas. The spatial and temporal distributions of these requirements are subject to changes in external forces, such as political regimes and economic systems. To assess and counteract desertification requires an understanding of, and ability to predict, the spatial and temporal arrangements of such concentration points and how these arrangements cause or inhibit desertification. To this end we developed a model that explicitly simulates how animals and vegetation interact. The model has spatial settings for extensive pasture to represent the points at which animals concentrate. We found that the spatial dynamics of the interaction between animal behavior and vegetation were nonlinear and markedly affected the size of the area desertified, and that the distribution of grazing pressure was more important than total grazing pressure, which had only a limited influence on desertification. These findings indicate that application of the carrying capacity concept is not capable of preventing desertification in extensive pasture, even under equilibrium conditions. Therefore, explicit management of the spatial distribution of animals is essential to prevent desertification in extensively grazed rangelands.”

    Robust Geographically Weighted Regression: A Technique for Quantifying Spatial Relationships Between Freshwater Acidification Critical Loads and Catchment Attributes

    In Environmental Science, Spatial Analysis, Statistics on June 4, 2010 at 7:22 am

    Annals of the Association of American Geographers, Volume 100, Issue 2 April 2010 , pages 286 – 306

    Paul Harris; A. Stewart Fotheringham; Steve Juggins

    “Geographically weighted regression (GWR) is used to investigate spatial relationships between freshwater acidification critical load data and contextual catchment data across Great Britain. Although this analysis is important in developing a greater understanding of the critical load process, the study also examines the application of the GWR technique itself. In particular, and unlike many previous presentations of GWR, the steps taken in choosing a particular GWR model form are presented in detail. A further important advance here is that the calibration results of the chosen GWR model are scrutinized for robustness to outlying observations. With respect to the critical load process itself, the results of this study largely agree with those of earlier research, where relationships between critical load and catchment data can vary across space. The more sophisticated spatial statistical models used here, however, are shown to be more flexible and informative, allowing a clearer picture of process heterogeneities to be revealed.”

    Comparative Spatiotemporal Analysis of Fine Particulate Matter Pollution

    In Environmental Science, Spatial Analysis, Statistics, Temporal Analysis on June 3, 2010 at 8:52 am

    Environmetrics, Volume 21, Issue 3, Date: May – June 2010, Pages: 305-317

    W. Pang, G. Christakos, and J-F Wang

    “The prime focus of this work is the comparative investigation, theoretical and numerical, of spatiotemporal techniques used in air pollution studies. Space-time statistics techniques are classified on the basis of a set of criteria and the relative theoretical merits of each technique are discussed accordingly. The numerical comparison involves the applications of two representative techniques. For this purpose, the popular spatiotemporal epistemic knowledge synthesis and graphical user interface (SEKS-GUI) software of spatiotemporal statistics is used together with a dataset of PM2.5 daily measurements obtained at monitoring stations geographically distributed over the state of North Carolina, USA. The analysis offers valuable insight concerning the choice of an appropriate spatiotemporal technique in air pollution studies.”

    Distribution of Maternity Units and Spatial Access to Specialised Care for Women Delivering before 32 Weeks of Gestation in Europe

    In GIS, Spatial Analysis on June 2, 2010 at 7:53 am

    Health & Place, Volume 16, Issue 3, May 2010, Pages 531-538

    Hugo Pilkington, Béatrice Blondel, Emile Papiernik, Marina Cuttini, Hélène Charreire, Rolf F. Maier, Stavros Petrou, Evelyne Combier, Wolfgang Künzel, Gérard Bréart, and Jennifer Zeitlina

    “Survival and quality of life are improved for very preterm babies when delivery occurs in a maternity unit with on-site neonatal intensive care (level III unit). We investigated the impact of distance on the probability of delivering in such a unit for births before 32 weeks of gestation from 9 European regions with diverse perinatal health systems (the MOSAIC cohort). We analysed distances between women’s homes, and the nearest level III in population quartiles, adjusting for maternal and pregnancy characteristics. Living farther away from a level III reduced access to specialised care everywhere; in some regions women residing in the fourth quartile were half as likely to deliver in level III units as those in the first. To improve regionalized perinatal care the spatial location of level III units should be taken into account.”

    Agricultural Trade and Poverty in Chile: A Spatial Analysis of Product Tradability

    In Social Science, Spatial Analysis on June 2, 2010 at 6:33 am

    Agricultural Economics, Published Online: 26 May 2010

    David A. Fleming, David G. Abler, Stephan J. Goetz

    “Many questions have arisen about the relationship between international agricultural trade and poverty in developing countries. This article explores these questions by analyzing local agricultural tradability indices, which measure the degree to which commodities produced in a particular region are traded internationally. Data are examined for Chile, a middle-income country with a history of international agricultural trade over the last decades. Empirical results indicate that a higher agricultural tradability index is associated with lower poverty rates across Chilean comunas.”

    Archaeology Presentations at the 2010 ESRI International User Conference

    In Conferences, ESRI, GIS, Spatial Analysis on June 2, 2010 at 5:43 am

    GIS in Archaeological Site Identification and Investigation

    • Archaeological Site Identification and Investigation: Geospatial Methods and Techniques
    • GIS and Archaeological Survey, Investigation, and Reporting
    • Religious Artifact Visualization Environment: Tracking Artifacts Across the Ancient World

    GIS aids in Archaeology Spatial Analysis

    • The Umayyad Period in Jordan: ArcGIS as Story Teller
    • Delineation of Archaeological Site Looting Damage in Central Iraq
    • Agent Analyst and Broad Spectrum Archaeological Modeling in Senegal

    GIS in Archaeological Investigation in the Southwestern United States

    • Measuring Prehistoric Hopi Temporal Walking Distance Over a Terrain
    • Reburial Planning Efforts at the Joint Courts Complex Archaeological Project
    • Close-Range Photogrammetry Techniques at Joint Courts Complex Archaeological Project

    Vague Spatio-Thematic Query Processing: A Qualitative Approach to Spatial Closeness

    In GIS, GIScience, Spatial Analysis on June 1, 2010 at 10:06 am

    Transactions in GIS, Volume 14, Number 2, April 2010

    Rolf Grütter, Thomas Scharrenbach, and Bettina Waldvogel

    “In order to support the processing of qualitative spatial queries, spatial knowledge must be represented in a way that machines can make use of it. Ontologies typically represent thematic knowledge. Enhancing them with spatial knowledge is still a challenge. In this article, an implementation of the Region Connection Calculus (RCC) in the Web Ontology Language (OWL), augmented by DL-safe SWRL rules, is used to represent spatio-thematic knowledge. This involves partially ordered partitions, which are implemented by nominals and functional roles. Accordingly, a spatial division into administrative regions, rather than, for instance, a metric system, is used as a frame of reference for evaluating closeness. Hence, closeness is evaluated purely according to qualitative criteria. Colloquial descriptions typically involve qualitative concepts. The approach presented here is thus expected to align better with the way human beings deal with closeness than does a quantitative approach. To illustrate the approach, it is applied to the retrieval of documents from the database of the Datacenter Nature and Landscape (DNL).”

    Assessing a Drop Box Programme: A Spatial Analysis of Discarded Needles

    In Social Science, Spatial Analysis, Statistics on June 1, 2010 at 8:43 am

    International Journal of Drug Policy, Volume 21, Issue 3, Pages 208-214 (May 2010)

    Luc de Montigny, Anne Vernez Moudon, Barbara Leigh, and Kim Young

    “Background: Distributing sterile injection equipment to injection drug users is one of few proven ways of lowering the transmission rate of blood borne viruses. Distribution of equipment has also been linked to increased needle discarding, which is a public health risk for both injectors and their host communities. Drop boxes (anonymous and public-access sharps containers) are a promising and increasingly popular means of reducing unsafe disposal, yet there is little empirical research to support or guide their implementation.

    “Methods: Using a dataset containing the locations of 7274 discarded needles and syringes collected monthly in the non-park open spaces of a 2.5km2 neighbourhood of Montréal, Canada for a period of five years, we compared levels of discards before and after the installation of 12 drop boxes. We used quasi-Poisson regression to test the effects of drop boxes on monthly counts of collected discards for areas within a walking distance of 25, 50, 100 and 200m of a drop box. We adjusted for known time-dependent covariates linearly and unknown time-dependent covariates using a smoothing function.

    “Results: We found strong evidence of reduced discarding following the installation of drop boxes; drop boxes were associated with reductions of up to 98% (95% CI: 72–100%) and significant reductions for areas up to 200m from a drop box. Reductions were inversely proportional to walking distance from drop boxes. No measure of weather or use of needle exchange programmes (NEPs) had a consistent relationship with discard counts.

    “Conclusion: Our research suggests that IDUs changed their needle-disposal behaviour in response to increased safe disposal options. In addition to being relatively low-threshold, economical and rapid, drop boxes appear to be a highly effective intervention to reduce discarded needles.”

    Sleeping Sickness in Southeastern Uganda: A Spatio-Temporal Analysis of Disease Risk, 1970-2003

    In Environmental Science, Imagery, Spatial Analysis, Statistics, Temporal Analysis on June 1, 2010 at 7:28 am

    Vector Borne Zoonotic Diseases, 2010 May 19. [Epub ahead of print]

    Berrang-Ford L, Berke O, Sweeney S, and Abdelrahman L.

    “Sleeping sickness is a major threat to human health in sub-Saharan Africa. Southeastern Uganda has experienced a number of significant epidemics in the past 100 years, most recently from 1976 to 1989. Recent and continued spread of the disease has highlighted gaps in the ability of current research to explain and predict the distribution of infection. Vegetation cover and changes in vegetation may be important determinants of transmission and disease risk because of the habitat preferences of the tsetse fly vector. This study examines the determinants of sleeping sickness distribution and incidence in southeastern Uganda from 1970 to 2003, spanning the full epidemic region and cycle, and focusing in particular on vegetation cover and change. Sleeping sickness data were collected from records of the Ugandan Ministry of Health, individual sleeping sickness treatment centers, and interviews with public health officials. Vegetation data were acquired from satellite imagery for four dates spanning the epidemic period, 1973, 1986, 1995, and 2001. Zero-inflated regression models were used to model predictors of disease presence and magnitude. Correlations between disease incidence and the normalized difference vegetation index (NDVI) at the subcounty level were evaluated. Results indicate that sleeping sickness infection is predominantly associated with proximity to water and spatial location, while disease incidence is highest in subcounties with moderate to high NDVI. The vegetation density (NDVI) at which sleeping sickness incidence peaked differed throughout the study period. The optimal vegetation density capable of supporting sleeping sickness transmission may be lower than indicated by data from endemic regions, indicating increased potential for disease spread under suitable conditions.”

    Geospatial Database Organization and Spatial Decision Analysis for Biodiversity Databases in Web GIS Environment

    In Environmental Science, GIS, Spatial Analysis on June 1, 2010 at 7:13 am

    Geocarto International, Volume 25, Issue 1 February 2010, pages 3 – 23

    Harish Karnatak; Sameer Saran; Karamjit Bhatia; P. S. Roy

    “The spatial decision-making process in multi-user environment is a quite challenging and complex task in group decision-making environment. The effective database design and GIS analysis techniques are very important at the host organization level. The biodiversity conservation prioritization is one of the complex issues for the conservation authorities. Various ecological and socio-economic drivers govern the spatial distribution of biologically rich communities. These drivers are important inputs to the modelling process with different rank criteria and probabilistic weight in order to arrive at a decision-making process. In the present article, a new database design and decision analysis technique is proposed for the natural resource management and planning in Web geographic information systems environment. The study is demonstrated for the geospatial decision analysis with an output validation utility where the analytic hierarchy process is used to derive the eigen vectors with given multiple constraints and conflicting criteria and aims at selecting an optimal site for the biodiversity conservations.”

    The Socio-spatial Distribution of Alcohol Outlets in Glasgow City

    In Social Science, Spatial Analysis on May 28, 2010 at 8:01 am

    Health & Place, Volume 16, Issue 1, January 2010, Pages 167-172

    Anne Ellaway, Laura Macdonald, Alasdair Forsyth, and Sally Macintyre

    “Aims: The aim of this study was to examine the distribution of alcohol outlets by area deprivation across Glasgow, Scotland.

    “Methods: All alcohol outlets were mapped and density per 1000 residents and proximity to nearest outlet calculated across quintiles of area deprivation.

    “Results: The socio-spatial distribution of alcohol outlets varies by deprivation across Glasgow but not systematically. Some deprived areas contain the highest concentration while others in similar deprivation quintiles contain very few.

    “Conclusions: Considerations of the local context are important in examining access to alcohol but more research is also required on purchasing behaviour.”

    The Longevity Pattern in Emilia Romagna: A Spatio-temporal Analysis

    In Social Science, Spatial Analysis, Temporal Analysis on May 27, 2010 at 7:02 am

    Paper submitted to SIS 2010

    Giulia Roli, Rossella Miglio, Rosella Rettaroli, and Alessandra Samoggia

    “In this paper, we investigate the pattern of longevity in Emilia Romagna, a North-Eastern region of Italy, at a municipality level. We consider a modified version of Centenarian Rate in two different periods. Spatio-temporal modeling is used to tackle at both periods the random variations in the occurrence of long-lived individuals, due to the rareness of such events in small areas. This method allows to exploit the spatial proximity smoothing the observed data, as well as to control for the effects of a set of regressors. As a result, clusters of areas characterized by extreme indexes of longevity are well identified and the temporal evolution of the phenomenon can be depicted. In addition, we evaluate the effects of the structure of mortality on the cohort of long-lived subjects in the second period. A spatial analysis is carried out by including the territorial patterns of mortality in a longitudinal perspective. We control for the major causes of death in order to deepen the analysis of the observed geographical differences.”

    Obesity Remains an Economic Issue, Seattle Obesity Study Finds

    In GIS, Social Science, Spatial Analysis on May 26, 2010 at 7:06 am

    Ensuring access to healthy, affordable foods is a top priority in tackling the obesity epidemic in the United States. Over the course of the last six months, the Institute of Medicine, United States Department of Agriculture, The White House and First Lady Michelle Obama have taken an interest in improving access to affordable and nutritious foods. Here in Seattle, Adam Drewnowski, UW professor of epidemiology, and his team are tackling the same issue. Remember the “fat zip codes” that predicted obesity rates from a few years ago? Drewnowski and his team were the brains behind that, as well as last summer’s study which showed that grocery prices in Seattle varied greatly between one supermarket chain and another.

    Now, researchers at the UW Center for Public Health Nutrition, UW Urban Form Lab and the Nutritional Sciences Program in the School of Public Health are asking: “Who buys what foods, why, where, and for how much?”

    The answers might surprise you. Most studies have used distance to the nearest supermarket as the best predictor of whether people have good diets and better health. But Drewnowski and team say that’s not true. “Six out of seven people shopped for food outside their immediate neighborhood,” he said “The closest supermarket for most people was less than a mile away, but people chose the market that was more than three miles away.” Driving further to save money on groceries is common. For that reason, physical proximity to a supermarket may not, by itself, assure a healthy diet. “Money does matter,” Drewnowski said.

    Areas where access to healthy affordable foods is scarce have become known as “food deserts.” Seattle, however, is well-supplied with supermarkets, grocery stores, farmers markets and other vendors, said Drewnowski. “We do not see evidence of significant food deserts,” he said. In comparison with other areas in the state, public transportation is also prevalent and accessible, so people can take a bus to a supermarket or grocery store with relative ease.

    Researchers combined a telephone survey, modeled on the Centers for Disease Control and Prevention (CDC) Behavioral Risk Factors Surveillance System, with new geo-coding techniques and methods of spatial analysis for the new study.

    Economic access has also become a primary research focus in public health nutrition, including the work by Drewnowski and team. Supermarket chains have specific demographics–consumers differ by age, education, income, health, and even obesity rates. “The county-wide obesity rate in 2007 was 19.8 percent, but our research found that the obesity rate was only four percent among Whole Foods and PCC shoppers,” said Drewnowski. “Consumers who shop at most area supermarket chains have obesity rates at 25 percent and higher. Clearly, not all supermarkets are the same and economic access is determined by price.”

    UW researchers recently discussed the Seattle Obesity Study results at “Shopping for Health” conference, which brought together public health agencies, academicians, supermarket representatives and policymakers from Seattle, King County and Washington state. Additional findings include:

    • New ways to identify underserved areas (“food deserts”) in Washington state that are most in need of resources
    • New ways to identify healthy, affordable and sustainable foods
    • The Seattle Atlas, or SEATTLAS, of all food sources, including supermarkets, grocery stores, and fast food restaurants
    • Food purchases and expenditures, diet quality and weight/ obesity
    • Insights from similar studies conducted in New York City.

    “We plan to explore how local data can best be used in new initiatives to improve access to healthy, affordable foods in Seattle, King County and throughout Washington state,” said Drewnowski. “As part of the dialogue, it is extremely important that the food industry be part of the solution and we welcomed their presence at this recent gathering,” he said. “We hope to provide the local answer to the question that the federal government is trying to address. And we want to make sure our public health initiatives and programs are backed by research and science.”

    [Source: University of Washington press release]

    A CyberGIS Framework for the Synthesis of Cyberinfrastructure, GIS, and Spatial Analysis

    In GIS, Modeling, Spatial Analysis on May 26, 2010 at 7:01 am

    Annals of the Association of American Geographers, 19 May 2010

    Shaowen Wang

    “Cyberinfrastructure (CI) integrates distributed information and communication technologies for coordinated knowledge discovery. The purpose of this article is to develop a CyberGIS framework for the synthesis of CI, geographic information systems (GIS), and spatial analysis (broadly including spatial modeling). This framework focuses on enabling computationally intensive and collaborative geographic problem solving. The article describes new trends in the development and use of CyberGIS while illustrating particular CyberGIS components. Spatial middleware glues CyberGIS components and corresponding services while managing the complexity of generic CI middleware. Spatial middleware, tailored to GIS and spatial analysis, is developed to capture important spatial characteristics of problems through the spatially explicit representation of computing, data, and communication intensity (collectively termed computational intensity), which enables GIS and spatial analysis to locate, allocate, and use CI resources effectively and efficiently. A CyberGIS implementation—GISolve—is developed to systematically integrate CI capabilities, including high-performance and distributed computing, data management and visualization, and virtual organization support. Currently, GISolve is deployed on the National Science Foundation TeraGrid, a key element of the U.S. and worldwide CI. A case study, motivated by an application in which geographic patterns of the impact of global climate change on large-scale crop yields are examined in the United States, focuses on assessing the computational performance of GISolve on resolving the computational intensity of a widely used spatial interpolation analysis that is conducted in a collaborative fashion. Computational experiments demonstrate that GISolve achieves a high-performance, distributed, and collaborative CyberGIS implementation.”

    Luc Anselin becomes 1st Walter Isard Chair in ASU’s School of Geographical Sciences and Urban Planning

    In Education, GIS, Spatial Analysis on May 26, 2010 at 6:39 am

    Luc Anselin is the founding director of ASU's School of Geographical Sciences and Urban Planning, and the school's first Walter Isard Chair. (Photo by Dave Tevis)

    When ASU’s Luc Anselin received a prize in 2006 for innovative work in regional science, his friend and mentor Walter Isard, a pioneer in that field, remarked at a dinner celebration that “Luc is an independent thinker, very independent. One day he said: ‘I’m not going to do any more theory with you. I’m going to do econometrics.’ And, of course, that decision he made was the proper one.”

    Fast forward to today and Anselin, who is widely published on topics dealing with spatial and regional analysis, including a much cited book “Spatial Econometrics,” is the founding director of ASU’s School of Geographical Sciences and Urban Planning, and the school’s first Walter Isard Chair.

    The appointment was made by Elizabeth D. Capaldi, provost and executive vice president , who said: “Walter Isard is a leader in regional science, an early example of a new, interdisciplinary field of study to problems ranging from spatial economics to transportation to geographical information systems.

    “As a scholar, Dr. Isard was a leader and innovator and as such this named Chair in his honor is most appropriate for Dr. Anselin, who is a leader at ASU. Dr. Anselin reflects the same commitment to advance new ideas across intellectual boundaries and encourage new perspectives on problems or our urban and rural environments,” Capaldi said.

    Anselin, who joined ASU in July 2007, received his doctoral and master’s degrees in regional science from Cornell University. Isard, his graduate studies mentor, is an emeritus professor of economics and regional science at Cornell. When Anselin first came to Cornell to study with Isard, they both were engaged in pure theory.

    “Dr. Isard forced his students to think and especially to think spatially, well before this term gained traction in the mainstream social sciences,” Anselin noted. “He was always challenging his student to push the envelope and to come up with creative solutions.”

    Anselin, a Belgium native, added that “this was very different from the European tradition in which I was trained, but it was a refreshing experience that I now try to transfer to my own students.”

    At ASU, Anselin serves as director of the GeoDa Center for Geospatial Analysis and Computation, a research unit in the College of Liberal Arts and Sciences devoted to the development, implementation and application of state-of-the-art methods of geospatial analysis to policy issues in the social and environmental sciences. Anselin is one of the principal developers of the fields of spatial econometrics and is best known for his applications SpaceStat and GeoDa.

    “In my work, I took the spatial perspective to a very technical econometric area of application, which Dr. Isard never pursued, “Anselin said. “But, my initial interests in complexity and integrated modeling, especially including environmental aspects into economic models paralleled his, and, while I have not been active in this area for some years, I am now returning to it at ASU, working with colleagues in the GeoDa Center on regional models and include carbon footprint, energy and water, used together with the economics, while taking a spatially explicit approach.”

    Isard often found himself at the hub of a network of scholars from economics, city planning, geography, sociology, political science and other social science fields, according to Anselin, who has held appointments in those same areas.

    Being the Walter Isard Chair at ASU “is very humbling, but at the same time, it is an opportunity to stress the values he held: interdisciplinarity, creativity, and tolerance and appreciation for other points of view,” Anselin said. In addition to his work in economics and regional science, Isard also is credited as a founder of the disciplines of peace science. His current research interests are conflict management and regional economics and integrated multi-region and world ecologic-economic models.

    Anselin is a member of the National Academy of Sciences, as is Isard. “I am his only student to get elected to NAS. Dr. Isard was elected in 1985,” he said. Anselin also is a fellow in the Regional Science Association International. The association’s North American Regional Science Council presented Anselin with the William Alonso Memorial Prize in 2006 and the Walter Isard Award in 2005.

    “The field of regional science is more relevant in the U.S. as it has ever been,” said Anselin, citing the White House Aug. 11, 2009, memorandum on “Developing Place-Based Policies.”

    “In Europe, regional science has been very prominent in policymaking for years and is a very healthy academic field as well,” Anselin said. “My perspective is that computation is becoming ever more important and that is where we are positioning the GeoDa Center at ASU.”

    [Source: ASU press release]

    A Spatial Analysis of Land Use Change and Water Quality in Lake Biwa, Japan

    In Environmental Science, Spatial Analysis on May 26, 2010 at 6:09 am

    Poster prepared for presentation at the Agricultural & Applied Economics Association 2010 AAEA, CAES, & WAEA Joint Annual Meeting, Denver, Colorado, July 25-27, 2010

    Katsuya Tanaka and JunJie Wu

    “Lake Biwa (670.49 Km2 in surface area) is the largest lake in Japan, formed about 400,000 years ago (Shiga Prefectural Government, 2008). Due to its long history, Lake Biwa is known as one of the oldest twenty lakes in the World. Lake Biwa has a high biodiversity, with approximately 600 animal species and 500 kinds of plants, including 58 endemic species such as Biwa trout.

    “This lake is also a valuable water source for 14 million people in Kinki region including three major cities: Kyoto, Osaka, and Kobe. However, due to intensive agriculture and rapid urban development around Lake Biwa, water quality indicators such as chemical oxygen demand (COD) and total organic carbon (TCC) in the lake has declined significantly over the last 30 years.”

    The Potsdam Housing Market: A GIS-based Spatial Analysis using FOS

    In GIS, Social Science, Spatial Analysis on May 24, 2010 at 7:32 am

    REAL CORP 2010 Proceedings/Tagungsband, Vienna, 18-20 May 2010

    Harald Schernthanner and Hartmut Asche

    “Housing in Potsdam varies from flats in redeveloped prefabricated high-rise buildings to apartments in historical townhouses to condominiums in Germany’s first gated community. Increasing demographic development and a stagnant public housing sector generate potential for spatial conflicts. For the time being in-depth GIS-based spatial analysis of the housing market lacks. This article analyses spatial trends and distribution patterns of the Potsdam housing market, using geostatistical methods implemented in free opensource geographic information systems (FOS GIS). To assemble a spatially differentiated picture of the housing market, methods such as spatial interpolation techniques and spatial declustering are applied. The analysis presented here is based on a representative sample of recent housing market data from 2009. The study provides a basis for discussion of a generic approach to housing market analysis based on free opensource geoinformation systems.”

    Spatio-temporal Analysis of Vegetation Dynamics of Selected Successional Stages of Dry Acidic Grasslands: Experimental Studies and Model Simulations

    In Environmental Science, Modeling, Spatial Analysis, Temporal Analysis on May 21, 2010 at 7:40 am

    Dissertation, August 2009

    Marcel Austenfeld

    “A generic modeling environment for the analysis and simulation of spatio-temporal phenomena in ecosystems was developed. This framework was built upon a Rich Client Platform (RCP) which uses new concepts of extensibility and software architecture for sustainable development and provides a solid basis for an Integrated Development Environment (IDE) for ecological models. The integration of various statistical tools, imaging routines and several specialized drawing panels makes this environment particularly suitable for the analysis of the above mentioned spatio-temporal ecological processes.

    “Because of their comparatively low complexity, dry acidic grassland ecosystems have been repeatedly used for studying vegetation pattern formation and the underlying biotic interactions. In order to obtain an integrative view of the existing knowledge as well as to provide a possibility for further integrative analysis with the help of model simulations, the above described platform was used to develop an individual based Model structure for the investigation of long term effects of environmental changes on the stability of early successional stages of such dry acidic grasslands which are typically dominated by the two pioneer species Corynephorus canescens and Polytrichum piliferum. The model was validated with experimental data and the spatio-temporal patterns created by the model were in good accordance with the measured natural patterns.

    “The model was then used to analyze the effect of changes in temperature, nutrient supply and disturbance rate on the long term behavior of this ecosystem. The results showed an overall high stability of this system under different temperature and nutrient scenarios as long as an intermediate disturbance frequency is assured.

    “Finally, an experimental study on the effect of herbivory and competition on the Corynephorus canescens was conducted. In a controlled field experiment, the effects of the removal of various amounts of aboveground biomass on the above and belowground biomass allocation during the following regeneration phase was analyzed in the presence or absence of an intraspecific and interspecific competitor (Hieracium pilosella). The results show a rather high ability of C. canescens to compensate low to medium amounts of foliage loss (reflecting the typical natural herbivory induced by grasshoppers and rabbits) without significant changes in its competitive ability. Belowground, no biomass effects of foliage removal and/or competition could be detected. Because of these negligible effects, herbivory was not implemented in the above described model.”

    Application of Pattern Recognition and Adaptive DSP Methods for Spatio-temporal Analysis of Satellite Based Hydrological Datasets

    In GIScience, Imagery, Spatial Analysis, Temporal Analysis on May 20, 2010 at 11:51 am

    Dissertation, 2010

    Anish Chand Turlapaty

    “Data assimilation of satellite-based observations of hydrological variables with full numerical physics models can be used to downscale these observations from coarse to high resolution to improve microwave sensor-based soil moisture observations. Moreover, assimilation can also be used to predict related hydrological variables, e.g., precipitation products can be assimilated in a land information system to estimate soil moisture. High quality spatio-temporal observations of these processes are vital for a successful assimilation which in turn needs a detailed analysis and improvement. In this research, pattern recognition and adaptive signal processing methods are developed for the spatio-temporal analysis and enhancement of soil moisture and precipitation datasets. These methods are applied to accomplish the following tasks: (i) a consistency analysis of level-3 soil moisture data from the Advanced Microwave Scanning Radiometer – EOS (AMSR-E) against in-situ soil moisture measurements from the USDA Soil Climate Analysis Network (SCAN). This method performs a consistency assessment of the entire time series in relation to others and provides a spatial distribution of consistency levels. The methodology is based on a combination of wavelet-based feature extraction and oneclass support vector machines (SVM) classifier. Spatial distribution of consistency levels are presented as consistency maps for a region, including the states of Mississippi, Arkansas, and Louisiana. These results are well correlated with the spatial distributions of average soil moisture, and the cumulative counts of dense vegetation; (ii) a modified singular spectral analysis based interpolation scheme is developed and validated on a few geophysical data products including GODAE’s high resolution sea surface temperature (GHRSST). This method is later employed to fill the systematic gaps in level-3 AMSR-E soil moisture dataset; (iii) a combination of artificial neural networks and vector space transformation function is used to fuse several high resolution precipitation products (HRPP). The final merged product is statistically superior to any of the individual datasets over a seasonal period. The results have been tested against ground based measurements of rainfall over our study area and average accuracies obtained are 85% in the summer and 55% in the winter 2007.”

    Spatio-Temporal Transmission Patterns of Black-Band Disease in a Coral Community

    In Environmental Science, GIS, Spatial Analysis, Temporal Analysis on May 20, 2010 at 9:31 am

    PLoS ONE 4(4): e4993. doi:10.1371/journal.pone.0004993, 2009

    Assaf Zvuloni, Yael Artzy-Randrup, Lewi Stone, Esti Kramarsky-Winter, Roy Barkan, and Yossi Loya

    “Background: Transmission mechanisms of black-band disease (BBD) in coral reefs are poorly understood, although this disease is considered to be one of the most widespread and destructive coral infectious diseases. The major objective of this study was to assess transmission mechanisms of BBD in the field based on the spatio-temporal patterns of the disease.

    “Methodology/Principal Findings: 3,175 susceptible and infected corals were mapped over an area of 10×10 m in Eilat (northern Gulf of Aqaba, Red Sea) and the distribution of the disease was examined monthly throughout almost two full disease cycles (June 2006–December 2007). Spatial and spatio-temporal analyses were applied to infer the transmission pattern of the disease and to calculate key epidemiological parameters such as (basic reproduction number). We show that the prevalence of the disease is strongly associated with high water temperature. When water temperatures rise and disease prevalence increases, infected corals exhibit aggregated distributions on small spatial scales of up to 1.9 m. Additionally, newly-infected corals clearly appear in proximity to existing infected corals and in a few cases in direct contact with them. We also present and test a model of water-borne infection, indicating that the likelihood of a susceptible coral becoming infected is defined by its spatial location and by the relative spatial distribution of nearby infected corals found in the site.

    “Conclusions/Significance: Our results provide evidence that local transmission, but not necessarily by direct contact, is likely to be an important factor in the spread of the disease over the tested spatial scale. In the absence of potential disease vectors with limited mobility (e.g., snails, fireworms) in the studied site, water-borne infection is likely to be a significant transmission mechanism of BBD. Our suggested model of water-borne transmission supports this hypothesis. The spatio-temporal analysis also points out that infected corals surviving a disease season appear to play a major role in the re-introduction of the disease to the coral community in the following season.”

    Integrating Socio-Economic Data in Spatial Analysis: An Exposure Analysis Method for Planning Urban Risk Mitigation

    In Social Science, Spatial Analysis on May 20, 2010 at 6:56 am

    REAL CORP 2010 Proceedings/Tagungsband, Vienna, 18-20 May 2010

    Neysa Setiadi, Hannes Taubenböck, Sonja Raupp, Jörn Birkmann

    “For disaster risk management and risk-based urban planning, time-dependent knowledge on the spatial distribution of various social groups is of critical importance. However, in a highly dynamic urbanizing world data are mostly outdated, generalized, not area-wide, not reliable or even not existing. This paper explores the potential of interdisciplinary integration of social science and remote sensing to deal with the problem of area-wide and up-to-date information derivation of the spatial distribution of population, and especially the vulnerable groups. The integration of conventional socio-economic data (census and household survey data) with the structural information of the urban landscape extracted from remotely sensed data aims at assessing dynamic exposure of various social groups. The analysis was done for the case study in the tsunami and earthquake prone coastal city of Padang, West Sumatra, Indonesia. The information generated is particularly useful for giving an additional insight for urban planners, how land use and urban development shape the exposure of various social groups to natural hazards.”

    Late Reproduction Behaviour in Sardinia: Spatial Analysis Suggests Local Aptitude Towards Reproductive Longevity

    In Social Science, Spatial Analysis on May 20, 2010 at 6:31 am

    Evolution and Human Behavior, Volume 30, Issue 2, Pages 93-102 (March 2009)

    Paola Astolfi, Graziella Caselli, Ornella Fiorani, Rosa M. Lipsi, Antonella Lisa, and Stefania Tentoni

    “Evolution in human life-history traits is influenced by environmental factors and, when genetic components underlie the relations, by micro-evolutionary forces. Age at reproduction is largely influenced by the familial cultural context and socioeconomic level, besides the maternal well-being and genetic background. The Sardinian population is characterized by historico-geographical isolation and differentiates from Italian mainland and other European populations in bio-demographic and cultural characteristics, among which the tendency to delay maternity persisting through generations. In our study, we investigated whether, in Sardinia, areas of “reproductive longevity” exist, where a higher-than-average incidence of late maternities combines with a lower-than-average cost in terms of perinatal death. Data from the Italian Central Institute of Statistics regard all 1980–1996 Sardinian births. Using spatial analysis of late maternity (proportion of babies born to mothers aged ≥35 years) and associated perinatal mortality (proportion of babies stillborn and dead within 0–6 days born to mothers aged ≥35 years), we aimed at singling out areas where the indicators run high and low, respectively. The perinatal mortality cost associated with the advanced maternal age [odds ratios (95% CI)] was evaluated through multiple logistic regression models. We identified central inland excess areas qualified by higher incidence of late maternities (27% vs. 22% in nonexcess area) and lower cost in perinatal mortality [OR=1.38 (1.04–1.84) vs. OR=1.74 (1.55–1.96) in nonexcess area]. In these “reproductive longevity” areas, the inbreeding coefficient was 3.7-fold higher than in the nonexcess areas, suggesting possible population homozygosity in genetic factors affecting the trait. Further and deeper investigations on biological and environmental determinants could focus on these target areas.”

    Space-Time Issues in Water Resources

    In Conferences, ESRI, GIS, Spatial Analysis, Temporal Analysis on May 19, 2010 at 12:53 pm

    2010 ESRI International User Conference, San Diego, California

    This panel session will review current technology for space-time integration within water resources context. Through the discussion, involving the panel members and the session attendees, needs for future developments in this area will be addressed.

    This panel discussion will be held Thursday, July 15, 2010, 10:15 – 11:30 a.m. in Room 25 C

    Monitoring Spatial and Temporal Pattern of Paneveggio Forest (Northern Italy) from 1859 to 2006

    In Environmental Science, GIS, Imagery, Spatial Analysis, Temporal Analysis on May 19, 2010 at 7:32 am

    iForest 3: 72-80. [online 2010-05-17]

    C. Tattoni, M. Ciolli, F. Ferretti, and M.G. Cantiani

    “This paper presents the results of a forest cover analysis over a time span of 150 years in a protected area of Eastern Trentino (Northern Italy), Paneveggio Pale di S. Martino Nature Park. With the aid of Grass GIS two historical maps (1859 and 1936) and a set of aerial photographs taken from 1945 to 2006 have been analysed, orthorectified and classified with a supervised method, in order to derive a series of forest cover maps. Techniques applied and problems encountered in using heterogeneous material are discussed. The research shows that from 1859 to the present the increase of forest cover is about 25%, due to the reduced impact of forestry and farming. Timberline dynamics have also been considered; an average growth of about 1 m/year has been estimated for the last 150 years and the data have been compared with the timberline cartography and to field surveys. Timberline estimation for recent years appears to be affected mainly by lower human pressure while the relationship with climate changes is difficult to evaluate. Landscape metrics were used to quantify the changes in forest fragmentation and to identify three core areas that have remained unchanged over time. This case study fills a gap of knowledge about the history of forest cover in the area, shows how multi temporal analysis can support protected area management. This study has been requested by the Park managers, a sign t that landscape planners are becoming aware of past landscape importance.”

    Assessing Floodplain Forests: Using Flow Modeling and Remote Sensing to Determine the Best Places for Conservation

    In Environmental Science, GIS, Imagery, Modeling, Spatial Analysis on May 18, 2010 at 8:41 am

    Natural Areas Journal, Volume 30, Number 1 – January 2010

    Mark G. Anderson, Charles E. Ferree, Arlene P. Olivero, and Feng Zhao

    “Mature and diverse floodplain forests are among the world’s most diminished ecosystems and conservationists need a rapid method to identify the best remaining examples of these systems. Because large rivers and their dynamics bind the floodplain together, the method must go beyond simple inventory of remnant patches to evaluate flood processes and identify constraints in the surrounding watersheds. We develop such a method for a three million hectare watershed in New England using a combination of data types to evaluate key attributes of floodplain systems. Riparian and floodplain communities were modeled using a GIS analysis of river valley topography and riverine processes, and floodplain forest occurrences were identified in a classification and regression (CART) analysis. Current flooding was verified using overlays of remotely sensed imagery of spring and fall water levels. We evaluated the intactness of the floodplain occurrences using ratios of upstream dam storage to annual runoff, the length of the connected stream network, and the naturalness of surrounding land cover. Field-assigned ranks of forest quality were correlated with the occurrence size, percent verified flooding, and percent natural cover. Predicted quality ranks reinforced the importance of these factors. Results indicate that the twenty top-ranking streams collectively contain 75 high quality areas suitable for floodplain forest restoration and conservation. Independent verification of these areas strongly corroborated our results.”

    A Multi-Varient Non-Statistical Model For Applied Spatial Analysis

    In Modeling, Spatial Analysis on May 18, 2010 at 6:54 am

    Paper presented at the annual meeting of the ASC Annual Meeting, Philadelphia, PA, Nov 04, 2009

    Harvey Morley

    “Many techniques associated with spatial analysis are still in their infancy. Others have existed for centuries. In the sixth century B.C. the Sun Zi Bing Fa, a military treatise on the conduct of war was written by Chinese general Sun Tzu. In it he specifically identifies the need to review and carefully analyze the variables associated with six types of terrain prior to launching an offensive. On a more contemporary basis public health map based spatial analysis was used in the early 19th century, prior to the allocation of scarce resources (including law enforcement), to identify vectors associated with a cholera outbreak, prior to allocating resources for its containment. This paper explores the use of non statistical spatial mapping as tool for developing planning models for law enforcement resource allocation.”

    Innovative Spatial Data Analysis and Visualization Supports Impact Assessments of Federal Lands

    In Environmental Science, GIS, Spatial Analysis, Visualization on May 18, 2010 at 6:24 am

    “Argonne National Laboratory’s extensive experience and technical capabilities in using spatial models and data to analyze, visualize, and model regional environmental and socioeconomic characteristics are used to support impact assessments for proposed energy developments on Federal lands.”

    Investigating Idiosyncrasy: Toward a Comprehensive Methodology of Visual Exploration and Analysis for Humanities Scholarship

    In Education, Social Science, Spatial Analysis, Visualization on May 17, 2010 at 10:13 am

    New Technologies and Interdisciplinary Research on Religion: 2010 Center for Geographic Analysis (CGA) Conference, Harvard University

    “Interpretation is at the heart of all humanities scholarship.

    “Scholars seek to characterize complex webs of idiosyncratic structure in historical and social systems.

    “This structure arises within and across spatial, temporal, and relational dimensions and scales.

    “But, most existing visualization approaches target the methodological norms of the sciences rather than the humanities.”

    Monitoring GIS Analysis and Simulations of Natural and Anthropogenic Digital Terrain Change Impacts on Water and Sediment Transport in the Agricultural Farms

    In Environmental Science, GIS, Spatial Analysis, Temporal Analysis on May 17, 2010 at 7:49 am

    ISPRS Archives XXXVIII-8/W3 Workshop Proceedings: Impact of Climate Change on Agriculture

    Mahmoud Reza Delavara and Nasser Najibi

    “The research effort focused on the acquisition of new knowledge about the complex interactions that occur between natural processes and anthropogenic activities to improve current understanding of topographic and land cover change impact on landscape processes. The method has been developed for a comprehensive spatio-temporal analysis of sand dune evolution. First, a set of features that can be used as indicators of dune evolution was identified and methods based on surface analysis using principles of differential geometry developed. Specific thresholds for extraction of the features such as dune crests, ridges, slip faces and active dune areas were introduced. The proposed methodology can be used to assist quantifying various aspects of complex evolution of a sand dune field that included rotation, translation and deflation, evolution of new slip faces and transformation from crescent to parabolic dunes. Complex interactions between human impacts and natural processes were identified: the impact of a large number of visitors freely moving over the dune has proven to be minimal, on the other hand, the naturally expanding vegetation and urban development surrounding the dune that reduced the sand supply had a major impact. It appears that the combination of climate change and indirect human activities have more significant impact than the direct interaction. Quantification of dune evolution provided critical information for park management and selected results of the research will be included in the visitor’s center. The developed methodology is general and can be applied to other areas that include migrating sands providing valuable information for management of such areas and a range of additional applications.”

    The Geography of Criminal Law

    In Geography, Social Science, Spatial Analysis on May 14, 2010 at 7:40 am

    Cardozo Law Review, Vol. 31, No. 3, 2010, Drexel University Earle Mack School of Law Research Paper No. 1570599

    Adam Benforado

    “When Westerners explain the causes of actions or outcomes in the criminal law context, they demonstrate a strong tendency to overestimate the importance of dispositional factors, like thinking, preferring, and willing, and underestimate the impact of interior and exterior situational factors, including environmental, historical, and social forces, as well as affective states, knowledge structures, motives, and other unseen aspects of our cognitive frameworks and processes. One of the situational factors that we are particularly likely to overlook is physical space – that is, landscapes, places, natures, boundaries, and spatialities. Our shortsightedness comes at a great cost. Spatial concerns shape legal structures, order interactions, and influence behavior.

    “To understand these dynamics, this Article establishes the foundation for a new spatial analysis of criminal law. By casting a wide net and capturing data across a diverse set of fields, this Article uncovers unappreciated but vital parallels, connections, and patterns concerning the ways in which physical space – and the meanings that we attach to spatial elements – affect (1) the proximate decision to commit a crime, (2) the likelihood a given person will become a criminal, (3) the experience of victimization, (4) the way in which policing is conducted, (5) what a crime is and how it is prosecuted, and (6) the consequences of being convicted.

    “As the first Article in a broader project, this systematic spatial analysis provides the basis for future work dedicated to understanding the origins of our criminal system and assessing whether our current legal structures – from the laws on the books to the practices of police officers to our approaches to punishment – align with our societal needs and values, and, thus, whether the structures we have in place ought to be changed. Instead of building its normative conclusions on geographical analysis alone, the project employs the lens of the mind sciences – including social psychology, social cognition, evolutionary psychology, and related fields – to investigate and explain identified spatial dynamics. This research offers the best hope for unlocking, among other concerns, why our justice system has focused on physically isolating criminals from society; why laws are frequently structured around protecting the physical boundaries of the body, home, and community; why more police shootings occur in certain areas than others; and why we have spatially-embedded laws that become inoperative when an individual leaves a jurisdiction. “

    Spatial Analysis of Selected Manufacturing and Service Sectors in China’s Economy using County Employment Data for 1990 and 2000

    In Geography, Social Science, Spatial Analysis on May 14, 2010 at 7:34 am

    Regional Studies, 1360-0591, First published on 25 February 2010

    Dean M. Hanink ; Avraham Y. Ebenstein ;Robert G. Cromley

    “This paper provides a comparative analysis of the spatial distribution of employment in forty-one economic sectors in China in 1990 and in 2000. Sectors are approximately split between manufacturing and services. Spatial distributions of employment by sector are analysed at the county level, and relative sectoral specialization at the county level is also considered. Manufacturing and service clusters are identified in both years using factor analysis, and the resulting factor scores are used in mapping their spatial extent. In general, geographical concentration in Chinese manufacturing accelerated between 1990 and 2000, while services became more spatially uniform in their distribution.”

    Spatio-temporal Analysis of Plant Pests in a Greenhouse using a Bayesian Approach

    In Environmental Science, Spatial Analysis, Statistics, Temporal Analysis on May 13, 2010 at 6:08 am

    Agricultural and Forest Entomology, Published Online 10 May 2010

    Christine Poncet, Valérie Lemesle, Ludovic Mailleret, Alexandre Bout, Roger Boll and Joelle Vaglio

    “The present study aimed to propose a method that can improve our understanding of pest outbreaks and spatio-temporal development in greenhouse crops.  The experiment was carried out in a greenhouse rose crop grown under integrated pest management (IPM) for 21 months.  The main pests observed were powdery mildew, two-spotted spider mites and western flower thrips.  A quick visual sampling method was established to provide continuous monitoring of overall crop health.  A Bayesian inferential approach was then used to analyse temporal and spatial heterogeneity in the occurrence of pests.  Interactions between pest dynamics and properties of spatial evolutions were exhibited revealing the influence of biotic and abiotic factors on crop health.  In the context of IPM, this information could be used to improve monitoring strategies by identifying periods or locations at risk.  It could also facilitate the implementation of the whole IPM procedure through identification of key factors that have a negative impact on overall crop health.”

    Got Results? Spatial Regression or Other Methods for the Analyses of Crime-Social Disorganization Covariates

    In Social Science, Spatial Analysis, Statistics on May 12, 2010 at 9:09 am

    Paper presented at The American Society of Criminology Annual Meeting, Philadelphia Marriott Downtown, Philadelphia, PA, Nov 04, 2009 . 2010-05-11

    MoonSun Kim and Seongmin Park

    “It is well known that crime rates are higher in socially disorganized areas. Numerous literature has examined the covariates between crime rates and community variables with such different statistical methods as OLS and HLM. These previous approach, however, has not paid enough attention to address the spatial autocorrelation in their analyses while it might exist due to the proximity of spatial locations of the units.

    “This study is designed to examine any differences between spatial regression we will use and other traditional methods by using crme data in a city and census information. Crime specific analyses will be provided with census block group as a unit of analysis.”

    Social Disorganization and Crisis Intervention: A Spatial Analysis

    In Conferences, GIS, Social Science, Spatial Analysis on May 11, 2010 at 6:38 am

    Paper presented at The American Society of Criminology Annual Meeting, Philadelphia Marriott Downtown, Philadelphia, PA, 04 November 2009

    Cindy Stewart

    “Responding to Watson, et al’s (2008) hypotheses related to social disorganization and police intervention with persons in mental health crisis, this study utilizes spatial analysis to address whether Crisis Intervention Team (CIT) responses vary across geographic areas. GIS mapping is utilized to test whether factors of social disorganization play a role in crisis intervention outcomes.”

    GIS-aided Evaluation of Evapotranspiration at Multiple Spatial and Temporal Climate Patterns using Geoindicators

    In Environmental Science, GIS, Spatial Analysis, Statistics, Temporal Analysis on May 10, 2010 at 8:20 am

    Ecological Indicators, Article in Press, 2010

    Nazzareno Diodatoa, Michele Ceccarelli, and Gianni Bellocchic

    “Multivariate spatial statistics techniques can be efficiently applied to generate fine spatial patterns of climate data in presence of an appropriate multivariate spatial structure over ungauged mountainous basins. However, they can become unsuitable when the data available over complex regions are sparse and affected by discordant spatial scales in primary and (colocated)-auxiliary variables. This is the case of actual evapotranspiration (AET). Combining GIS and geoindicators (e.g., topographical and vegetational indices), we proposed an upscaling procedure to overcome this problem, transforming a preliminary-smoothed macro-scale pattern (AET grid-data), into a local-scale pattern.

    “The procedure was applied to a cropland test site at Mediterranean sub-regional basin scale (Tammaro, South Italy) to develop a climatological baseline estimation of AET refined at slope scale. After the upscaling, the most frequent estimated AET values were about 550 mm yr−1 (with quasi-normal distribution), while underestimations were observed in the preliminary, smoothed map (positively skewed distribution with mean 460 mm yr−1). The upscaling allowed the influence of the topographic factor to emerge, with a wider range of values (about 300–900 mm yr−1) being estimated and substantially not visible in the smoothed pattern. A temporal climate pattern of soil water depletion in the growing season was also shown as reflected in the increase of AET flux in the period 1991–2008 in comparison to the precedent climate (1961–1990).”

    Spatial Analysis of Hospitalization for Heart Diseases in Vale do Paraíba

    In Science, Spatial Analysis on May 10, 2010 at 7:16 am

    Arquivos Brasileiros de Cardiologia, 2010 Apr 30

    Soares PA and Nascimento LF

    “Ischemic heart diseases (IHD) are important causes of death in the Vale do Paraíba paulista. To identify patterns of spatial distribution of hospitalizations for acute myocardial infarction (AMI) and IHD in the Vale do Paraíba paulista. This was an ecological study using exploratory spatial analysis of hospitalization data for acute myocardial infarction and ischemic heart disease in the Vale do Paraíba between 2004 and 2005. The statistical analysis used spatial georeferenced databases of 35 municipalities and spatial statistics routines. The admission data were obtained from the Portal Datasus of the Ministry of Health. The variables were the number of admissions for males and females aged over 30 years. To evaluate the spatial dependence we used the autocorrelation coefficients of Global Moran and Local Moran’s index. We also analyzed the correlations between variables, using the TerraView program. The level of significance was 5%. Among 6,287 admissions, the rates were 161.66/100 thousand. Of the total of 35 municipalities, 31.4% had rates above average. The coefficient of Moran (global) showed a statistical significance. Local indexes showed clusters, indicating a cluster of 9 municipalities in which there was spatial dependence with their own dynamics. In the mid Vale do Paraíba paulista, the spatial analysis identified spatial clusters of hospitalizations due to acute myocardial infarction and ischemic heart disease, allowing intervention to reduce rates.”

    Spatial and Temporal Analysis of a Phytophthora Megakarya Epidemic in a Plantation in the Centre of Cameroon

    In Spatial Analysis, Temporal Analysis on May 10, 2010 at 6:33 am

    2009. In : Towards rational cocoa production and efficient use for a sustainable word coca economy : 16th International Cocoa Resarch Conference, 2009-11-16/2009-11-21, Bali, Indonésie.

    Ten Hoopen G.M., Sounigo O., Babin R., Yédé M., Dikwe G., and Cilas C..

    “Black pod rot of cocoa caused by Phytophthora megakarya causes significant losses in Cameroon. Studying the spatial and temporal disease dynamics of P. megakarya provides useful information on the mechanisms of dispersal and the physiological and biological factors that are important for its spread and ultimately its management. Therefore, we studied the spatial and temporal development of a P. megakarya epidemic in a plantation in the Centre region of Cameroon over two production seasons. A map was made of a cocoa plantation of 2.61 ha, containing a total of 2536 cocoa trees and 438 neighbor/shade trees. Each cocoa and neighbor tree was assigned x and y coordinates by projecting the plantation map onto an orthonormal grid. From a total of 421 cocoa trees located throughout the plantation, production and pod rot data were collected weekly. Subsequently, for both production seasons, the spatial relation between the numbers of rotten pods harvested from the observed cocoa trees was analyzed by semivariogram analysis. Block kriging was used as an interpolation method. Analysis of the semivariograms revealed a spatial dependence of pod rot distribution. In all cases where the theoretical model fitted well to the actual data the semivariogram was exponential. The estimated dispersion range of P. megakarya varied from 2.7 to 6.9 m in 2006 (mean 5.1, SD 0.56 m) and 3.3 to 6.9 m in 2007 (mean 5.6, SD 0.94 m). Kriging maps revealed the simultaneous appearance of multiple infection points throughout the plantation at distances larger than the dispersion range. Infection hot spots were located at similar locations for both years. Based on these results, we hypothesize that primary inoculum is the main determinant for the spatial and temporal development of an epidemic at the plantation level and that secondary inoculum is mainly responsible for the within-tree temporal development of an epidemic. Therefore, more attention should be given to reducing primary inoculum levels of P. megakarya in order to improve control efficacy.”

    The Value of Good Neighbors: A Spatial Analysis of the California and Washington Wine Industries

    In GIS, Social Science, Spatial Analysis, Statistics on May 7, 2010 at 7:23 am

    Selected Paper prepared for presentation at the Agricultural & Applied Economics Association 2010 AAEA,CAES, & WAEA Joint Annual Meeting, Denver, Colorado, July 25-27, 2010

    Nan Yang, Jill J. McCluskey, and Michael Brady

    “The fact that wineries tend to cluster in certain sub-regions can be partially explained by the terroir of those areas. However, a gap in our understanding of the spatial relationships among wineries remains. In this article, winery-level data with geographic information system (GIS) coordinates are utilized to examine the spatial relationships among neighboring wineries. Spatial effects for the California and Washington wine industries are assessed by performing clustering tests based on wine prices and tasting scores. A spatial lag model is then estimated to test the hypothesis that there are positive effects from neighbors when analyzing the hedonic price equations. The regression results indicate that there exists strong and positive neighbor effect.”

    Agent-based Models and the Spatial Sciences

    In GIS, Modeling, Spatial Analysis on May 7, 2010 at 6:57 am

    Geography Compass, Volume 4 Issue 5, Pages 428 – 448, Published Online 04 May 2010

    Paul M. Torrens

    “Agent-based models (ABMs) are used in the spatial sciences as building-blocks for computer simulation. ABMs have a range of advantageous attributes, not least of which is their flexibility in representing dynamic and highly adaptive physical or human phenomena. ABMs facilitate the exploration of ideas about the myriad of ways that geographical systems develop, behave, interact and evolve, often supporting experimentation with geographical systems in ways that are simply not possible in the real world. Indeed, in many cases, ABMs are developed from the bottom up, pedagogically, as a tool in building theory. Geographers’ work with ABMs has helped to strengthen existing ties with related disciplines such as computer science and informatics, ecology, sustainability science, economics, anthropology, political science and the earth sciences. Primarily because of the value placed on spatial science and behavioral geography in agent-based modeling, work of this kind is helping to infuse geographical perspectives and ‘spatial thinking’ into these fields. This article reviews the development of agent-based modeling in the spatial sciences, its current uses and applications in physical and human geography and potential future trends in its research and development.”

    Regional Housing Price Cycles: A Spatio-temporal Analysis Using US State-Level Data

    In Social Science, Spatial Analysis, Statistics, Temporal Analysis on May 7, 2010 at 6:51 am

    Regional Studies, Published Online 23 April 2010

    Todd H. Kuethe and Valerien O. Pede

    “A study is presented of the effects of macroeconomic shocks on housing prices in the Western United States using quarterly state-level data from 1988:1 to 2007:4. The study contributes to the existing literature by explicitly incorporating locational spillovers through a spatial econometric adaptation of vector autoregression (SpVAR). The results suggest these spillovers may Granger cause housing price movements in a large number of cases. SpVAR provides additional insights through impulse response functions that demonstrate the effects of macroeconomic events in different neighbouring locations. In addition, it is demonstrated that including spatial information leads to significantly lower mean-square forecast errors.”

    An Assessment of Land Conservation Patterns in Maine Based on Spatial Analysis of Ecological and Socioeconomic Indicators

    In Environmental Science, GIS, Spatial Analysis on May 5, 2010 at 8:38 am

    Environmental Management, Published Online 06 April 2010

    Cronan, C., Lilieholm, R., Tremblay, J., and Glidden, T.

    “Given the nature of modern conservation acquisitions, which often result from gifts and opportunistic purchases of full or partial property rights, there is a risk that the resulting mosaic of conserved resources may not represent a coherent set of public values and benefits. With different public and private entities engaged in land conservation, one would further expect that each organization would apply separate goals and criteria to the selection and acquisition of its conservation portfolio. This set of circumstances raises an important question: what is the aggregate outcome of this land conservation process? Retrospective assessments provide a means of reviewing cumulative historical decisions and elucidating lessons for improving future conservation strategies. This study used GIS-based spatial analysis to examine the relationships of private and public conservation lands in Maine to a variety of landscape metrics in order to determine the degree to which these lands represent core ecological and socioeconomic values that are meaningful to a wide cross-section of citizens. Results revealed that the gains of past conservation efforts in Maine are counter-balanced to some extent by apparent gaps in the existing fabric of conservation holdings. Conservation lands capture a representative sample of diverse habitat, provide a large measure of protection for multiple conservation values and indicators, and offer an unusual mix of outdoor recreational opportunities for residents and visitors alike. Yet, the majority of parcels are relatively small and isolated, and thus do not provide contiguous habitat blocks that offset ongoing processes of landscape fragmentation. Furthermore, the majority of area associated with many of the ecological metrics examined in this report is located outside the boundaries of current conservation holdings. The under-represented metrics identified in this investigation can be viewed as potential targets for new strategic conservation initiatives.”

    Spatial Analysis of Tuberculosis in an Urban West African Setting: Is There Evidence of Clustering?

    In GIS, Science, Spatial Analysis, Statistics on May 4, 2010 at 8:30 am

    Tropical Medicine & International Health, 2010 Apr 8. [Epub ahead of print]

    Touray K, Adetifa IM, Jallow A, Rigby J, Jeffries D, Cheung YB, Donkor S, Adegbola RA, and Hill PC.

    “Summary: Objectives To describe the pattern of tuberculosis (TB) occurrence in Greater Banjul, The Gambia with Geographical Information Systems (GIS) and Spatial Scan Statistics (SaTScan) and to determine whether there is significant TB case clustering.

    “Methods:  In Greater Banjul, where 80% of all Gambian TB cases arise, all patients with TB registered at chest clinics between March 2007 and February 2008 were asked to participate. Demographic, clinical characteristics and GPS co-ordinates for the residence of each consenting TB case were recorded. A spatial scan statistic was used to identify purely spatial and space-time clusters of tuberculosis among permanent residents.

    “Results: Of 1145 recruited patients with TB, 84% were permanent residents with 88% living in 37 settlements that had complete maps available down to settlement level. Significant high- and low-rate spatial and space-time clusters were identified in two districts. The most likely cluster of high rate from both the purely spatial analysis and the retrospective space-time analysis were from the same geographical area. A significant secondary cluster was also identified in one of the densely populated areas of the study region.

    “Conclusions:  There is evidence of significant clustering of TB cases in Greater Banjul, The Gambia. Systematic use of cluster detection techniques for regular TB surveillance in The Gambia may aid effective deployment of resources. However, passive case detection dictates that community-based active case detection and risk factor surveys would help confirm the presence of true clusters and their causes.”

    Confidence Maps: a Tool to Evaluate Archaeological Data’s Relevance in Spatial Analysis

    In Social Science, Spatial Analysis on May 3, 2010 at 8:18 am

    Layers of Perception, Proceedings of the 35th International Conference on Computer Applications and Quantitative Methods in Archaeology (CAA), Berlin, Germany, April 2–6, 2007

    Krištof Oštir, Žiga Kokalj, Laure Saligny, Florian Tolle, and Laure Nuninger, with the collaboration of Françoise Pennors and Klemen Zakšek

    “Inventory data used in archaeology is often incomplete and heterogeneous. In the framework of the ArchaeDyn program, a method has been proposed to evaluate heterogeneity in archaeological inventories. The purpose of this work is to create a validation tool to interpret the results. This tool is called a “confidence map” and is produced by combining representation and reliability maps. The first step consists of generating representation maps to describe the clustering of archaeological items. The second step is based on reliability maps. Data providers are asked to define and outline the level of reliability of their data. Then the representation and reliability layers are combined using map algebra. The resulting maps allow for the comparison and analysis of data confidence.”

    Event Detection from Flickr Data through Wavelet-based Spatial Analysis

    In Spatial Analysis, Temporal Analysis on May 3, 2010 at 7:54 am

    Proceeding of the 18th ACM conference on Information and Knowledge Management

    Ling Chen and Abhishek Roy

    “Detecting events from web resources has attracted increasing research interests in recent years. Our focus in this paper is to detect events from photos on Flickr, an Internet image community website. The results can be used to facilitate user searching and browsing photos by events. The problem is challenging considering: (1) Flickr data is noisy, because there are photos unrelated to real-world events; (2) It is not easy to capture the content of photos. This paper presents our effort in detecting events from Flickr photos by exploiting the tags supplied by users to annotate photos. In particular, the temporal and locational distributions of tag usage are analyzed in the first place, where a wavelet transform is employed to suppress noise. Then, we identify tags related with events, and further distinguish between tags of aperiodic events and those of periodic events. Afterwards, event-related tags are clustered such that each cluster, representing an event, consists of tags with similar temporal and locational distribution patterns as well as with similar associated photos. Finally, for each tag cluster, photos corresponding to the represented event are extracted. We evaluate the performance of our approach using a set of real data collected from Flickr. The experimental results demonstrate that our approach is effective in detecting events from the Flickr photo collection.”

    Religion and Economic Change over a Century: Linking Diverse Historical Data

    In GIS, Social Science, Spatial Analysis on May 3, 2010 at 7:38 am

    New Technologies and Interdisciplinary Research on Religion: 2010 Center for Geographic Analysis (CGA) Conference, Harvard University

    Video: Pedestrian Spatial Analysis

    In Modeling, Spatial Analysis, Video on April 30, 2010 at 6:55 am

    “Spatial Analysis can be used pre simulation to estimate areas of highest probability of conflict or most wear and tear in the pedestrian space. Space utilisation values can be queried using the Spatial Metrics Tool within the Urban Analytics Framework (UAF) during or after simulation to see the actual effect of the available free space on the movement of agents. This tool is used to highlight where excessive density or high spatial utilisation values indicate a potential for crushing and injury as the crowd moves through the model.”

    Spatio-temporal Analysis of Forests under Different Management Regimes using Landsat and IRS Images

    In Environmental Science, Imagery, Spatial Analysis, Temporal Analysis on April 29, 2010 at 9:13 am

    Institute for Social and Economic Change, Bangalore, Working paper 213, 2009

    “Following the empirical study, cloud-free satellite data were used to study the forests in multi-temporal dimensions. Use of remote sensing data with visual observation/ground truth data is an advanced tool to study and understand the development patterns of the forests. Based on the vegetation index and land cover map a sound development has been observed in the community conserved forest (CCF) in comparison to other forests of the region. Community-based conservation would contribute to new conservation approaches that facilitate achieving the goal of sustainable landscape development in the mountains of the Indian Himalayan region.”

    Evapotranspiration and Water Use Efficiency in a Chesapeake Bay Wetland under Carbon Dioxide Enrichment

    In Climate Change, Environmental Science, Spatial Analysis, Temporal Analysis on April 29, 2010 at 9:03 am

    Global Change Biology, Volume 16 Issue 1 , Pages 234-245 (January 2010)

    IAHONG LI, JOHN E. ERICKSON, GARY PERESTA, and BERT G. DRAKE

    “Wetlands evapotranspire more water than other ecosystems, including agricultural, forest and grassland ecosystems. However, the effects of elevated atmospheric carbon dioxide (CO2) concentration (Ca) on wetland evapotranspiration (ET) are largely unknown. Here, we present data on 12 years of measurements of ET, net ecosystem CO2 exchange (NEE), and ecosystem water use efficiency (EWUE, i.e. NEE/ET) at 13:00–15:00 hours in July and August for a Scirpus olneyi (C3 sedge) community and a Spartina patens (C4 grass) community exposed to ambient and elevated (ambient+340 μmol mol−1) Ca in a Chesapeake Bay wetland. Although a decrease in stomatal conductance at elevated Ca in the S. olneyi community was counteracted by an increase in leaf area index (LAI) to some extend, ET was still reduced by 19% on average over 12 years. In the S. patens community, LAI was not affected by elevated Ca and the reduction of ET was 34%, larger than in the S. olneyi community. For both communities, the relative reduction in ET by elevated Ca was directly proportional to precipitation due to a larger reduction in stomatal conductance in the control plants as precipitation decreased. NEE was stimulated about 36% at elevated Ca in the S. olneyi community but was not significantly affected by elevated Ca in S. patens community. A negative correlation between salinity and precipitation observed in the field indicated that precipitation affected ET through altered salinity and interacted with growth Ca. This proposed mechanism was supported by a greenhouse study that showed a greater Ca effect on ET in controlled low salinity conditions compared with high salinity. In spite of the differences between the two communities in their responses to elevated Ca, EWUE was increased about 83% by elevated Ca in both the S. olneyi and S. patens communities. These findings suggest that rising Ca could have significant impacts on the hydrologic cycles of coastal wetlands.”

    Spatial and Temporal Analysis of Drought and Summer Precipitation in Nepal under Climate Change

    In Climate Change, Spatial Analysis, Temporal Analysis on April 29, 2010 at 6:31 am

    IOP Conference Series: Earth and Environmental Science, Volume 6, Session 29, 2009

    Madan Sigdel and M. Ikeda

    “Agricultural production and water resources in Nepal are highly influenced by precipitation for an entire year. In addition to dominant rainfall during summer monsoon over Nepal (SMRN), drought indices, which were normalized with the mean rainfall, were analyzed in association with large-scale atmospheric patterns using various statistical analyses. The indices at 3-month and 12-month represent agricultural and hydrological time scales, respectively. A dominant oscillation in SMRN exists in the range of 2.5–2.8 years indicating El Nino and Southern Oscillation (ENSO): i.e., less rain over eastern and central Nepal during El Nino. The analyses of horizontal patterns of moisture transport regressed on the SMRN revealed that the SMRN variability is more closely related with the moisture flux in a near-surface layer from Bay of Bengal under influences of ENSO rather than the moisture flux from the Arabian Sea. The 12-month drought index is basically equivalent with SMRN. On the other hand, the 3-month index additionally exhibits less rain in winter over western Nepal associated with weak westerly. Therefore, higher probability of the drought risk is suggested for agricultural production in western Nepal. While Indian Ocean Dipole was also investigated, its influence on Nepal is limited. These results suggest to us to prepare more appropriate mitigation methods for high risk of drought under climate change in different ways between western Nepal and the other regions.”

    Spatial-temporal Analysis of Moving Polygons

    In Environmental Science, Spatial Analysis, Temporal Analysis on April 28, 2010 at 11:48 am

    Colin John Robertson, Masters thesis

    “There are few methods available for the spatial-temporal analysis of polygon data. This research develops a new method for spatial-temporal analysis of moving polygons (STAMP). Using an event-based framework, polygons from neighboring time periods are related by spatial overlap and proximity. The proximity spatial relation is defined by an application specific distance threshold. STAMP is demonstrated in the spatial-temporal analysis of a wildfire burning over small spatial and temporal scales, and in the spatial-temporal analysis of mountain pine beetle (Dendroctonus ponderosae Coleoptera: Hopkins) movement patterns over large spatial and temporal scales. The mountain pine beetle analysis found that short range movement patterns of mountain pine beetles occurred at different beetle population levels. Spot proliferation occurred most when beetle presence was increasing slowly, perhaps moving into new areas for the first time. When beetle presence increased rapidly, local expansion, or spot growth, was a more common movement pattern. In the Pine Pass study area. long range dispersal markedly extended the northeast border of the mountain pine beetle range.”

    Pond-based Survey of Amphibians in a Saxon Cultural Landscape from Transylvania (Romania)

    In Environmental Science, GIS, Spatial Analysis, Temporal Analysis on April 28, 2010 at 8:16 am

    Italian Journal of Zoology, Volume 77, Issue 1 March 2010 , pages 61 – 70

    T. Hartel; K. Oumlllerer; D. Cogabrevelniceanu; Sz. Nemes; C. I. Moga; and L. Demeter

    “Habitat-based inventories provide critical reference data that are essential to track changes in amphibian communities and their habitats. We present the results of a pond inventory in a cultural landscape from central Romania. The presence/absence of amphibians was assessed through multiple-year surveys during the breeding season and larval development. Ten amphibian species and a species complex were identified: Triturus cristatus, T. vulgaris, Bombina variegata, Bufo bufo, B. viridis, Rana dalmatina, R. temporaria, R. arvalis, Hyla arborea, Pelobates fuscus and the R. esculenta complex. The species richness is larger in the permanent ponds than in the temporary ones. Rana dalmatina, B. bufo and the R. esculenta complex are the most frequent in the permanent ponds, while Bombina variegata and R. temporaria were the most common in temporary ponds. The scarcity of B. viridis and R. arvalis is explained by the lack of available habitats. Our data allow a more complex analysis of the spatial and temporal determinants of amphibian habitat use in this cultural landscape, and provide a consistent baseline for future surveys and monitoring programmes.”

    • More information

    Spatial and Temporal Ecology of Scots Pine ectomycorrhizas

    In Environmental Science, GIS, Spatial Analysis, Temporal Analysis on April 28, 2010 at 5:41 am

    New Phytologist, Volume 186 Issue 3, Pages 755 – 768, Published Online 25 Feb 2010

    Brian J. Pickles, David R. Genney, Jacqueline M. Potts, Jack J. Lennon, Ian C. Anderson, and Ian J. Alexander

    “Spatial analysis was used to explore the distribution of individual species in an ectomycorrhizal (ECM) fungal community to address: whether mycorrhizas of individual ECM fungal species were patchily distributed, and at what scale; and what the causes of this patchiness might be. Ectomycorrhizas were extracted from spatially explicit samples of the surface organic horizons of a pine plantation. The number of mycorrhizas of each ECM fungal species was recorded using morphotyping combined with internal transcribed spacer (ITS) sequencing. Semivariograms, kriging and cluster analyses were used to determine both the extent and scale of spatial autocorrelation in species abundances, potential interactions between species, and change over time. The mycorrhizas of some, but not all, ECM fungal species were patchily distributed and the size of patches differed between species. The relative abundance of individual ECM fungal species and the position of patches of ectomycorrhizas changed between years. Spatial and temporal analysis revealed a dynamic ECM fungal community with many interspecific interactions taking place, despite the homogeneity of the host community. The spatial pattern of mycorrhizas was influenced by the underlying distribution of fine roots, but local root density was in turn influenced by the presence of specific fungal species.”

    Spatial Distribution and Partitioning of Polychlorinated Biphenyls in Tokyo Bay, Japan

    In Environmental Science, Spatial Analysis on April 27, 2010 at 6:52 am

    Journal of Environmental Monitoring, 2010, 12, 838

    Jun Kobayashi, Shigeko Serizawa, Takeo Sakurai, Yoshitaka Imaizumi, Noriyuki Suzuki, and Toshihiro Horiguch

    “Spatial distributions and partitioning of polychlorinated biphenyls (PCBs) in Tokyo Bay, Japan, were evaluated by measuring the concentrations of all 209 PCB congeners in surface and bottom waters and bottom sediment at 10 locations. The dissolved + particulate summed congener concentrations (PCB [sum of the concentrations of all 209 PCB congeners]) in surface and bottom waters ranged from 120 to 1100 pg L-1 (median 250 pg L-1) and from 83 to 910 pg L-1 (median 230 pg L-1), respectively. The concentrations did not statistically differ between the two layers, possibly because of vertical mixing of the water column. PCB concentrations in sediment ranged from 2.7 to 110 ng g-1-dry weight. The highest PCB concentrations in both water and sediment were found at stations in the northern bay. Logarithms of field-observed organic carbon-normalized partition coefficients (KOC) increased linearly as the log octanol–water partition coefficients (KOW) increased, up to a log KOW of about 6.5, and then decreased for log KOW > 6.5 (mostly hexa- and hepta-chlorinated biphenyls). Furthermore, log KOC values of congeners having log KOW < 6.5 were higher by about 1 than values predicted by a published empirically derived equation, suggesting that application of KOC values determined in laboratory experiments with soil or sediment samples to fate prediction models may result in overestimation by about one order of magnitude of the concentrations of PCBs with log KOW < 6.5 in the dissolved phase in the water column.”

    A Fuzzy Set Based Approach for Integration of Thematic Maps for Landslide Susceptibility Zonation

    In Environmental Science, GIS, Modeling, Spatial Analysis on April 26, 2010 at 10:11 am

    Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, Volume 3, Issue 1, 2009, Pages 30 – 43

    D. P. Kanungo, M. K. Arora, S. Sarkar, and R. P. Gupta

    “Spatial prediction of landslides is termed landslide susceptibility zonation (LSZ). In this study, an objective weighting approach based on fuzzy concepts is used for LSZ in a part of the Darjeeling Himalayas. Relevant thematic layers pertaining to landslide causative factors have been generated using remote sensing and geographic information system (GIS) techniques. The membership values for each category of thematic layers have been determined using the cosine amplitude fuzzy similarity method and are used as ratings. The integration of these ratings led to the generation of LSZ map. The integration of different ratings to generate an LSZ map has been performed using a fuzzy gamma operator apart from the arithmetic overlay approach. The process is based on determination of combined rating known as the landslide susceptibility index (LSI) for all the pixels using the fuzzy gamma operator and classification using the success rate curve method to prepare the LSZ map. The results indicate that as the gamma value increases, the accuracy of the LSZ map also increases. It is observed that the LSZ map produced by the fuzzy algebraic sum has reflected a more real situation in terms of landslides in the study area.”

    Space–Time Geostatistics for Geography: A Case Study of Radiation Monitoring Across Parts of Germany

    In Environmental Science, GIS, Geography, Spatial Analysis, Statistics, Temporal Analysis on April 26, 2010 at 7:32 am

    Geographical Analysis, Volume 42 Issue 2, Pages 161 – 179, Published Online 13 Apr 2010

    Gerard B. M. Heuvelink and Daniel A. Griffith

    “Many branches within geography deal with variables that vary not only in space but also in time. Therefore, conventional geostatistics needs to be extended with methods that estimate and quantify spatiotemporal variation and use it in spatiotemporal interpolation and stochastic simulation. This article briefly summarizes the main concepts of space–time geostatistics. Kriging in space and time can be done in much the same way as it is in a purely spatial setting. The main difficulties are in defining a realistic stochastic model that is assumed to have generated data and in characterizing and estimating the space–time correlation of that model. This article uses a model-based geostatistical approach to characterize space–time variability. The space–time variable of interest is treated as a sum of independent stationary spatial, temporal, and spatiotemporal components, which leads to a sum-metric space–time variogram model. Methods are illustrated with a case study of space–time interpolation of monthly averages of detected background radiation for a 5-year period in four German states.”

    Spatial Distributions of Multiple Plant Species Affect Herbivore Foraging Selectivity

    In Environmental Science, Spatial Analysis on April 26, 2010 at 7:02 am

    Oikos, Volume 119, Issue 2, Date: February 2010, Pages: 401-408

    Ling Wang, Deli Wang, Yuguang Bai, Guitong Jiang, Jushan Liu, Yue Huang, and Yexing Li

    “Spatial distribution of food resources is an important factor determining herbivore foraging. Previous studies have demonstrated that clumped distribution of preferred species increases its consumption by herbivores in single- or two-species systems. However, the potential impact of distribution pattern of less preferred species on foraging was ignored. In natural grasslands with high species diversity and complexity, the spatial distribution of preferred species impacts on herbivore foraging may be strongly correlated with the distribution of less preferred species.

    “Our aims were to determine the effect of distribution of both preferred and other plant species on herbivore foraging under conditions close to a native, multi-species foraging environment, and conceptualize the relationships between spatial distribution of food resources and herbivore consumption. We hypothesized that random distribution of non-preferred species reduces herbivore consumption of preferred species because the dispersion of less preferred species likely disturbs herbivore foraging. We conducted an experiment using three species with five combinations of clumped and random distribution patterns. Three species Lathyrus quinquenervius, Phragmites australis and Leymus chinensis, were of high, intermediate and low preferences by sheep, respectively. Results showed that distribution of low preferred species, but not that of high preferred one, affected the consumption of preferred species. Sheep obtained higher consumption of high preferred species when low preferred species followed a clumped distribution than a random distribution. Distance between aggregations of high and low preferred species did not affect sheep foraging. It was concluded that the effects of spatial distribution of preferred species on its consumption are dependent on herbivore foraging strategy, and sheep can consume more preferred species when there is a consistent spatial pattern between preferred species and the entire food resource, and that the random dispersion of low preferred species in grassland may reduce herbivore consumption of high preferred species, thus minimizing selective grazing.”

    Predicting and Mapping Malaria under Climate Change Scenarios: The Potential Redistribution of Malaria Vectors in Africa

    In Climate Change, GIS, Science, Spatial Analysis on April 23, 2010 at 10:15 am

    Malaria Journal, 9:111, 23 April 2010

    Henri EZ Tonnang, Richard YM Kangalawe, Pius Z Yanda

    “Background: Malaria is rampant in Africa and causes untold mortality and morbidity. Vector-borne diseases are climate sensitive and this has raised considerable concern over the implications of climate change on future disease risk. The problem of malaria vectors (Anopheles mosquitoes) shifting from their traditional locations to invade new zones is an important concern. The vision of this study was to exploit the sets of information previously generated by entomologists, e.g. on geographical range of vectors and malaria distribution, to build models that will enable prediction and mapping the potential redistribution of Anopheles mosquitoes in Africa.

    “Methods: The development of the modelling tool was carried out through calibration of CLIMEX parameters. The model helped estimate the potential geographical distribution and seasonal abundance of the species in relation to climatic factors. These included temperature, rainfall and relative humidity, which characterized the living environment for Anopheles mosquitoes. The same parameters were used in determining the ecoclimatic index (EI). The EI values were exported to a GIS package for special analysis and proper mapping of the potential future distribution of Anopheles gambiae and Anophles arabiensis within the African continent under three climate change scenarios.

    “Results: These results have shown that shifts in these species boundaries southward and eastward of Africa may occur rather than jumps into quite different climatic environments. In the absence of adequate control, these predictions are crucial in understanding the possible future geographical range of the vectors and the disease, which could facilitate planning for various adaptation options.

    “Conclusion: Thus, the outputs from this study will be helpful at various levels of decision making, for example, in setting up of an early warning and sustainable strategies for climate change and climate change adaptation for malaria vectors control programmes in Africa. “

    Geographically and Temporally Weighted Regression for Modeling Spatio-Temporal Variation in House Prices

    In GIS, Modeling, Social Science, Spatial Analysis, Statistics, Temporal Analysis on April 23, 2010 at 9:41 am

    International Journal of Geographical Information Science, Volume 24, Issue 3 March 2010 , pages 383 – 401

    Bo Huang; Bo Wu; Michael Barry

    “By incorporating temporal effects into the geographically weighted regression (GWR) model, an extended GWR model, geographically and temporally weighted regression (GTWR), has been developed to deal with both spatial and temporal nonstationarity simultaneously in real estate market data. Unlike the standard GWR model, GTWR integrates both temporal and spatial information in the weighting matrices to capture spatial and temporal heterogeneity. The GTWR design embodies a local weighting scheme wherein GWR and temporally weighted regression (TWR) become special cases of GTWR. In order to test its improved performance, GTWR was compared with global ordinary least squares, TWR, and GWR in terms of goodness-of-fit and other statistical measures using a case study of residential housing sales in the city of Calgary, Canada, from 2002 to 2004. The results showed that there were substantial benefits in modeling both spatial and temporal nonstationarity simultaneously. In the test sample, the TWR, GWR, and GTWR models, respectively, reduced absolute errors by 3.5%, 31.5%, and 46.4% relative to a global ordinary least squares model. More impressively, the GTWR model demonstrated a better goodness-of-fit (0.9282) than the TWR model (0.7794) and the GWR model (0.8897). McNamara’s test supported the hypothesis that the improvements made by GTWR over the TWR and GWR models are statistically significant for the sample data.”

    Addressing Issues in Sparseness, Ecological Bias and Formulation of the Adjacency Matrix in Bayesian Spatio-temporal Analysis of Disease Counts

    In GIScience, Spatial Analysis, Temporal Analysis on April 22, 2010 at 10:14 am

    Arul Earnest, PhD thesis, 2010

    “The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.”

    Efficient Evaluation of Continuous Spatio-temporal Queries on Moving Objects with Uncertain Velocity

    In GIScience, Spatial Analysis, Temporal Analysis on April 21, 2010 at 9:14 am

    GeoInformatica, Volume 14, Number 2 / April, 2010

    Yuan-Ko Huang and Chiang Lee

    “Continuous Range (CR) query and Continuous K-Nearest Neighbor (CKNN) query are two important types of spatio-temporal queries. Given a time interval [t s , t e ] and a moving query object q, a CR query is to find the moving objects whose Euclidean distances to q are within a user-given distance at each time instant within [t s , t e ]. A CKNN query is to retrieve the K-Nearest Neighbors (KNNs) of this query object q at each time instant within [t s , t e ]. In this paper, we investigate how to process these spatio-temporal queries efficiently under the situation that the velocity of each object is not fixed. This uncertainty on the velocity of object inevitably results in high complexity in processing spatio-temporal queries. We will discuss the complications incurred by this uncertainty and propose two algorithms, namely the Possibility-based possible within objects searching algorithm and the Possibility-based possible KNN searching algorithm, for the CR query and the CKNN query, respectively. A Possibility-based model is designed accordingly to quantify the possibility of each object being the result of a CR query or a CKNN query. Comprehensive experiments are performed to demonstrate the effectiveness and the efficiency of the proposed approaches.”

    Multidimensional Map Algebra: Design and Implementation of a Spatio-Temporal GIS Processing Language

    In GIS, GIScience, Spatial Analysis, Temporal Analysis on April 21, 2010 at 7:19 am

    Transactions in GIS, Volume 14 Issue 1, Pages 1 – 21, Published Online 17 Jan 2010

    Jeremy Mennis

    “Due to the increasing volume of spatio-temporal data generated from remote sensing, sensor networks and computational simulation, there is a need for a generic, domain-independent framework for spatio-temporal data analysis. This research presents a generic set of data processing and manipulation tools for spatio-temporal raster data called multidimensional map algebra (MMA). MMA is an extension of conventional map algebra that operates not only on data that are two-dimensional in space but also on data that are: (1) one-dimensional in time; (2) both two-dimensional in space and one-dimensional in time; (3) three-dimensional in space; and (4) both three-dimensional in space and one-dimensional in time. MMA data types, neighborhoods, lags, and functions are presented, including rules for combining data types of different dimensionality within local, focal, and zonal functions. A prototype implementation in JAVA is provided as a demonstration and syntax specification for the functions. Challenges to continued development of MMA include performance and efficiency issues for processing very large multidimensional data sets.”

    Fuzzy Spatio-temporal Relations Analysis

    In GIScience, Spatial Analysis, Temporal Analysis on April 21, 2010 at 7:07 am

    7th International Conference on Information Technology: New Generations ITNG 2010, Las Vegas, Nevada

    Nadeem SALAMAT and El-hadi ZAHZAH

    “There are different families of Spatio-temporal relations such as same-place same-time, same-place different-times, for road networks like overtake, derive beside and many others. These relations describe the relative positions of objects in a spatial scene. In existing techniques, these relations are defined qualitatively. Due to imprecise knowledge information and compensation power to small errors, fuzzy methods are becoming more important.

    “In this paper, fuzzy spatio-temporal relations same-place different-time and different-place different time are introduced. To define these relations, histograms of fuzzy Allen relations and fuzzy dissimilarity measure are used.”

    Association between Residences in U.S. Northern Latitudes and Rheumatoid Arthritis: A Spatial Analysis of the Nurses’ Health Study

    In Spatial Analysis on April 21, 2010 at 6:55 am

    Environmental Health Perspectives, available online 25 March 2010

    Verónica M. Vieira, Jaime E. Hart, Thomas F. Webster, Janice Weinberg, Robin Puett, Francine Laden, Karen H. Costenbader, and Elizabeth W. Karlson

    “Background: The etiology of rheumatoid arthritis (RA) remains largely unknown although epidemiologic studies suggest genetic and environmental factors may play a role. Geographic variation in incident RA has been observed at the regional level.

    “Objective: Spatial analyses are a useful tool for confirming existing exposure hypotheses or generating new ones. To explore further the association between location and RA risk, we analyzed individual level data from U.S. women in the Nurses’ Health Study, a nationwide cohort study.

    “Methods: Participants included 461 incident RA cases and 9,220 controls with geocoded addresses followed from 1988-2002. We examined spatial variation using addresses at baseline in 1988 and at time of case diagnosis/censoring of controls. Generalized additive models were used to predict a continuous risk surface, smoothing on longitude and latitude while adjusting for known risk factors. Permutation tests were conducted to test for the overall importance of location and identify areas of statistically significant risk relative to the whole study area.

    Results: A statistically significant area of increased RA risk was identified in the northeast U.S. (p-value=0.034). Risk was generally higher at northern latitudes and increased slightly using nurses’ 1988 locations compared to locations at time of diagnosis/censoring. Crude and adjusted models produced similar results.

    “Conclusions: Spatial analyses suggest women living in higher latitudes may be at greater risk for RA. Further, RA risk may be greater for locations occurring earlier in residential histories. These results illustrate the usefulness of GAM methods in generating hypotheses for future investigation and supporting existing hypotheses.”

    Spatial Analysis Reveals Differences in Soil Microbial Community Interactions between Adjacent Coniferous Forest and Clearcut Ecosystems

    In Environmental Science, Spatial Analysis on April 21, 2010 at 6:46 am

    Soil Biology and Biochemistry, Article in Press, 2010

    Daniel L. Mummey, Jeffrey T. Clarke, Callie A. Cole, Benjamin G. O’Connor, James E. Gannon, and Phillip W. Ramsey

    “Knowledge of how forest management influences soil microbial community interactions is necessary for complete understanding of forest ecology. In this study, soil microbial communities, vegetation characteristics and soil physical and chemical properties were examined across a rectangular 4.57 × 36.58 m sample grid spanning adjacent coniferous forest and clearcut areas. Based on analysis of soil extracted phospholipid fatty acids, total microbial biomass, fungi and Gram-negative bacteria were found to be significantly reduced in soil of the clearcut area relative to the forest. Concurrent with changes in microbial communities, soil macroaggregate stability was reduced in the clearcut area, while no significant differences in soil pH and organic matter content were found. Variography indicated that the range at which spatial autocorrelation between samples was evident (patch size) was greater for all microbial groups analyzed in the clearcut area. Overall, less spatial structure could be resolved in the forest. Variance decomposition using principal coordinates of neighbor matrices spatial variables indicated that soil aggregate stability and vegetation characteristics accounted for significant microbial community spatial variation in analyses that included the entire plot. When clearcut and forest areas were analyzed separately, different environmental variables (pH in the forest area and soil organic matter in the clearcut) were found to account for variation in soil microbial communities, but little of this variation could be ascribed to spatial interactions. Most microbial variation explained by different components of microbial communities occurred at spatial scales other than those analyzed. Fungi accounted for over 50% of the variation in bacteria of the forest area but less than 11% in the clearcut. Conversely, AMF accounted for significant variation in clearcut area, but not forest, bacteria. These results indicate broadly disparate controls on soil microbial community composition in the two systems. We present multiple lines of evidence pointing toward shifts in fungi functional groups as a salient mechanism responsible for qualitative, quantitative and spatial distribution differences in soil microbial communities.”

    Remote Sensing of the Urban Heat Island Effect across Biomes in the Continental USA

    In Environmental Science, Imagery, Spatial Analysis on April 21, 2010 at 6:29 am

    Remote Sensing of Environment, Volume 114, Issue 3, 15 March 2010, Pages 504-513

    Imhoff, M.L., Zhang, P., Wolfe, R.E. and Bounoua, L.

    “Impervious surface area (ISA) from the Landsat TM-based NLCD 2001 dataset and land surface temperature (LST) from MODIS averaged over three annual cycles (2003–2005) are used in a spatial analysis to assess the urban heat island (UHI) skin temperature amplitude and its relationship to development intensity, size, and ecological setting for 38 of the most populous cities in the continental United States. Development intensity zones based on %ISA are defined for each urban area emanating outward from the urban core to the non-urban rural areas nearby and used to stratify sampling for land surface temperatures and NDVI. Sampling is further constrained by biome and elevation to insure objective intercomparisons between zones and between cities in different biomes permitting the definition of hierarchically ordered zones that are consistent across urban areas in different ecological setting and across scales.

    “We find that ecological context significantly influences the amplitude of summer daytime UHI (urban–rural temperature difference) the largest (8 °C average) observed for cities built in biomes dominated by temperate broadleaf and mixed forest. For all cities combined, ISA is the primary driver for increase in temperature explaining 70% of the total variance in LST. On a yearly average, urban areas are substantially warmer than the non-urban fringe by 2.9 °C, except for urban areas in biomes with arid and semiarid climates. The average amplitude of the UHI is remarkably asymmetric with a 4.3 °C temperature difference in summer and only 1.3 °C in winter. In desert environments, the LST’s response to ISA presents an uncharacteristic “U-shaped” horizontal gradient decreasing from the urban core to the outskirts of the city and then increasing again in the suburban to the rural zones. UHI’s calculated for these cities point to a possible heat sink effect. These observational results show that the urban heat island amplitude both increases with city size and is seasonally asymmetric for a large number of cities across most biomes. The implications are that for urban areas developed within forested ecosystems the summertime UHI can be quite high relative to the wintertime UHI suggesting that the residential energy consumption required for summer cooling is likely to increase with urban growth within those biomes.”

    Spatializing Social Networks: Using Social Network Analysis to Investigate Geographies of Gang Rivalry, Territoriality, and Violence in Los Angeles

    In Geography, Social Science, Spatial Analysis on April 20, 2010 at 7:12 am

    Annals of the Association of American Geographers, 1467-8306, Volume 100, Issue 2, First published 2010, Pages 307 – 326

    Steven M. Radil; Colin Flint; and George E. Tita

    “Social network analysis is an increasingly prominent set of techniques used in a number of social sciences, but the use of the techniques of social network analysis in geography has been challenged because of a perceived lack of geographic nuance or consideration of spatialities of context in social networks. The concept of social position and the associated technique of structural equivalence in social network analysis are explored as a means to integrate two different kinds of embeddedness: relative location in geographic space and structural position in network space. Using spatialized network data, this article compares the geography of rivalry relations that connect territorially based criminal street gangs in a section of Los Angeles with a geography of the location of gang-related violence. The technique of structural equivalence uses the two different spatialities of embeddedness to identify gangs that are similarly embedded in the territorial geography and positioned in the rivalry network, which aids in understanding the overall context of gang violence. The technique demonstrated here has promise beyond this one study of gang crime as it operationalizes spatialities of embeddedness in a way that allows simultaneous systematic evaluation of the way in which social actors’ positions in network relationships and spatial settings provide constraints on and possibilities for their behavior.”

    Scale-dependent Environmental Variables Affecting Red Squirrel (Sciurus vulgaris meridionalis) Distribution

    In Environmental Science, GIS, Spatial Analysis on April 20, 2010 at 6:42 am

    Italian Journal of Zoology, Volume 77, Issue 1 March 2010 , pages 92 – 101

    P. C. Rima; M. Cagnin; G. Aloise; D. Preatoni; and L. A. Wauters

    “We investigated the effects of habitat fragmentation on the endemic subspecies of red squirrel Sciurus vulgaris meridionalis in the Pollino National Park, Calabria, Southern Italy. Presence/absence of squirrels was monitored using drey (nest) counts in 51 1-ha census plots. Squirrel dreys were found in 16 plots (31%). Patch size was not correlated to squirrel presence. Squirrels were found in patches ranging from 3.19 to 6051 ha. Small-scale forest structure significantly affected the probability of occurrence. The proportion of conifers and average tree height positively predict squirrel presence; furthermore, nest density was positively correlated with high tree species diversity and the proportion of deciduous oaks (Quercus cerris, Q. ilex). Also at the home-range scale the proportion of conifer forest and oak-dominated deciduous forests positively predicted squirrel presence (200-300 m radius). At the even larger scale, corresponding with potential dispersal distances (3000 m radius), landscape parameters indicating a lower degree of fragmentation and proportion of oak seemed to favour squirrel presence. Our results emphasize that multi-scale analyses can enhance our understanding of red squirrel distribution, and that their distribution and abundance were mainly determined by forest structure components, such as food availability, at the home-range scale. We underline the importance of protection, and eventually increasing conifer and deciduous oak woods range in the Pollino National Park for the management and conservation of endemic Calabrian red squirrels.”

    Data Analysis of Spatio-Temporal Sensor Data as a Contribution to the Model Analysis for Water Resources

    In Environmental Science, Modeling, Spatial Analysis, Temporal Analysis on April 20, 2010 at 6:13 am

    BALWOIS 2010, Ohrid, Republic of Macedonia – 25, 29 May 2010

    Sanja Veleva, Kosta Mitreski

    “The quality of the information is measured by its accuracy and its relevance over time. Therefore, the process of data analysis of the sensor eco-data is of a great importance to the detection and prediction of the eco-hydrology phenomena. The existing models for data mining do not relate to the continuously changing characteristics of the sensor eco-data. Furthermore, most of the monitoring systems are based on event alert services, which do not answer to the continuous variations of the measured parameters. Our approach embeds the nature of system characteristics into one dynamic model for data mining of continuously changing spatio-temporal characteristics of one eco-hydrology system. The continuously gathered sensor eco-data from the region of Lake Prespa consisted of 320 water samples, among them 224 from the lake gauging stations and 96 from the river gauging stations. Considering the recommendations from the Water Framework Directive (WFD), the sensor eco-data were grouped into three types: physical, chemical and biological, corresponding to their aspect of water quality. All of these types convey the same class definition in the form of value, spatial and temporal information. To define our sensor data mining model we contribute to three segments: outlier analysis, pattern analysis, and prediction analysis. The suggested sensor data analysis model should be of a useful asset in obtaining knowledge for certain aquatic phenomena.”

    Spatial Synchrony in Intertidal Benthic Algal Biomass in Temperate Coastal and Estuarine Ecosystems

    In Climate Change, Environmental Science, Spatial Analysis on April 20, 2010 at 6:00 am

    Ecosystems, Volume 13, Number 2 / March, 2010

    Daphne van der Wal, Annette Wielemaker-van den Dool and Peter M. J. Herman

    “Microphytobenthos plays a vital role in estuarine and coastal carbon cycling and food webs. Yet, the role of exogenous factors, and thus the effects of climate change, in regulating microphytobenthic biomass is poorly understood. We aimed to unravel the mechanisms structuring microphytobenthic biomass both within and across ecosystems. The spatiotemporal distribution of the biomass of intertidal benthic algae (dominated by diatoms) was estimated with an unprecedented spatial extent from time-series of Normalized Differential Vegetation Index (NDVI) derived from a 6-year period of daily Aqua MODIS 250-m images of seven temperate, mostly turbid, estuarine and coastal ecosystems. These NDVI time-series were related to meteorological and environmental conditions. Intertidal benthic algal biomass varied seasonally in all ecosystems, in parallel with meteorology and water quality. Seasonal variation was more pronounced in mud than in sand. Interannual variation in biomass was small, but synchronized year-to-year biomass fluctuations occurred in a number of disjointed ecosystems. Air temperature explained interannual fluctuations in biomass in a number of sites, but the synchrony was mainly driven by the wind/wave climate: high wind velocities reduced microphytobenthic biomass, either through increased resuspension or reduced emersion duration. Spatial variation in biomass was largely explained by emersion duration and mud content, both within and across ecosystems. The results imply that effects on microphytobenthic standing stock can be anticipated when the position in the tidal frame is altered, for example due to sea level rise. Increased storminess will also result in a large-scale decrease of biomass.”

    Spatial Analysis of Residential Break and Enter

    In Social Science, Spatial Analysis on April 19, 2010 at 7:53 am

    Timothy R. Mots, PhD thesis

    “This study explores three separate, but inter-related aspects of residential break and enter. The study, located in the Capital Regional District of Victoria, British Columbia, Canada, offers a unique environment for this type of research with its thirteen municipalities, four municipal and one national police force confined geographically by sea on three sides and wilderness on the fourth. The first part of this research identifies spatial and temporal patterns of residential break and enters at the regional level and the municipal level. The results showed that patterns existed at the municipal level, but changed at the regional level. There was evidence that some of the patterns at the municipal level persisted over time. Temporally, break and enter is predominately an afternoon occurrence. No other consistent pattern was found daily, monthly, nor seasonally over the course of the study period. The second part of the study examines police perceptions about the location of residential break and enters high activity areas or ‘hot spots’. Police perceptions were compared to actual hot spots to determine the degree of agreement. The research also explored the concordance between police perceptions of hot spot locations. The results indicated that police hot spots did not conform to actual hot spots; furthermore, there was only limited agreement amongst police on hot spot locations. The third part of the study examined burglar’s use of space. Burglars were asked a number of questions to establish their geographical knowledge of the region. Information was obtained on the location of their offences, routes taken to offence sites, method of transportation, trip start location, motivation behind the offence, and purpose of the trip. The findings indicate that offenders commit the majority of their crimes within areas they know. The subjects in the study were motivated by the need for money, mainly to purchase drugs. The majority of Offence trips were initiated with the sole purpose of committing a burglary. Most journey to crimes emanated from the offenders’ residence. Travel was restricted not so much by distance, instead by their knowledge of the region or by the necessity to obtain money for drugs.”

    Spatial Analysis of the Health Risks Associated with Solid Waste Incineration: A Preliminary Analysis

    In Environmental Science, Spatial Analysis on April 19, 2010 at 7:15 am

    Revista Brasileira de Epidemiologia, 2010, vol.13, n.1, pp. 3-10

    Nelson GOUVEIA and Rogério Ruscitto do PRADO

    “OBJECTIVES: to examine if emissions from the Vergueiro solid waste incinerator are associated with an increased risk of cancer in the population in its vicinity. METHODS: the area under influence of this incinerator was delimited by a 7 km radius from its geocoded centroid. Deaths of city residents in administrative districts inside this area due to cancer of lung, liver, larynx, non-Hodgkin’s lymphoma in adults, leukemia, and all sites combined in children, in the 1998 to 2002 period, were selected and geocoded. The studied area was divided into 7 concentric rings delimited by a radius of 1 to 7 km from the incinerator. The analysis of the relationship between residential proximity to the incinerator and mortality due to cancer was based on the comparison of observed and expected cases, using the Stone test for decline in risk with distance from the incinerator. RESULTS: the area studied comprised 1,599,532 inhabitants, of which 92,894 were children less than 5 years old and 634,993 were adults over 40 years old. No spatial gradient in risk was observed for any outcome in relation to distance from the incinerator. CONCLUSION: although no excess risk for the selected cancers were observed, emissions of incinerators still operating and their possible health effects should be monitored. The study of the spatial distribution of health events in areas around point sources of air pollution can become a methodological option for surveillance activities.”

    Revista Brasileira de Epidemiologia

    A Second Hydrocarbon Boom Threatens the Peruvian Amazon: Trends, Projections, and Policy Implications

    In Environmental Science, GIS, Social Science, Spatial Analysis on April 19, 2010 at 6:41 am

    Environmental Research Letters, Volume 5, Number 1, 2010

    Matt Finer and Martí Orta-Martínez

    ‘The Peruvian Amazon is home to extraordinary biological and cultural diversity, and vast swaths of this mega-diverse region remain largely intact. Recent analysis indicates, however, that the rapid proliferation of oil and gas exploration zones now threatens the region’s biodiversity, indigenous peoples, and wilderness areas. To better elucidate this dynamic situation, we analyzed official Peruvian government hydrocarbon information and generated a quantitative analysis of the past, present, and future of oil and gas activities in the Peruvian Amazon. We document an extensive hydrocarbon history for the region—over 104 000 km of seismic lines and 679 exploratory and production wells—highlighted by a major exploration boom in the early 1970s. We show that an unprecedented 48.6% of the Peruvian Amazon has been recently covered by oil and gas concessions, up from just 7.1% in 2003. These oil and gas concessions overlap 17.1% of the Peruvian Amazon protected area system and over half of all titled indigenous lands. Moreover, we found that up to 72% of the Peruvian Amazon has been zoned for hydrocarbon activities (concessions plus technical evaluation agreements and proposed concessions) in the past two years, and over 84% at some point during the past 40 years. We project that the recent rapid proliferation of hydrocarbon zones will lead to a second exploration boom, characterized by over 20 000 km of new seismic testing and construction of over 180 new exploratory wells in remote, intact, and sensitive forest areas. As the Peruvian Amazon oil frontier rapidly expands, we conclude that a rigorous policy debate is urgently needed in order to avoid the major environmental impacts associated with the first exploration boom of the 1970s and to minimize the social conflict that recently led to deadly encounters between indigenous protesters and government forces.’”

    International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2010), 2-5 Nov 2010, San Jose

    In Conferences, GIS, GIScience, Spatial Analysis, Visualization on April 16, 2010 at 8:21 am

    18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
    (ACM SIGSPATIAL GIS 2010)

    2-5 November 2010, San Jose, California

    “The ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2010 (ACM SIGSPATIAL GIS 2010) is the eighteenth event in a series of symposia and workshops that began in 1993 with the aim of bringing together researchers, developers, users, and practitioners carrying out research and development in novel systems based on geo-spatial data and knowledge, and fostering interdisciplinary discussions and research in all aspects of geographic information systems. The conference provides a forum for original research contributions covering all conceptual, design, and implementation aspects of GIS ranging from applications, user interfaces, and visualization to storage management and indexing issues. This conference is the premier annual event of the ACM Special Interest Group on Spatial Information (ACM SIGSPATIAL). Researchers, students, and practitioners are invited to submit their contributions to ACM SIGSPATIAL GIS 2010.”

    Spatial Interpolation in Wireless Sensor Networks: Localized Algorithms for Variogram Modeling and Kriging

    In Modeling, Spatial Analysis, Statistics on April 14, 2010 at 10:03 am

    GeoInformatica, Volume 14, Number 1 / January, 2010

    Muhammad Umer, Lars Kulik and Egemen Tanin

    “Wireless sensor networks (WSNs) are rapidly emerging as the prominent technology for monitoring physical phenomena. However, large scale WSNs are known to suffer from coverage holes, i.e., large regions of deployment area where no sensing coverage can be provided. Such holes are the result of hardware failures, extensive costs for redeployment or the hostility of deployment areas. Coverage holes can adversely affect the accurate representation of natural phenomena that are monitored by a WSN. In this work, we propose to exploit the spatial correlation of physical phenomena to make monitoring systems more resilient to coverage holes. We show that a phenomenon can be interpolated inside a coverage hole with a high level of accuracy from the available nodal data given a model of its spatial correlation. However, due to energy limitations of sensor nodes it is imperative to perform this interpolation in an energy efficient manner that minimizes communication among nodes. In this paper, we present highly energy efficient methods for spatial interpolation in WSNs. First, we build a correlation model of the phenomenon being monitored in a distributed manner. Then, a purely localized and distributed spatial interpolation scheme based on Kriging interpolates the phenomenon inside coverage holes. We test the cost and accuracy of our scheme with extensive simulations and show that it is significantly more energy efficient than global interpolations and remarkably more accurate than simple averaging.”

    Spatial Risk Assessment of Livestock Exposure to Pumas in Patagonia, Argentina

    In Environmental Science, GIS, Modeling, Spatial Analysis on April 14, 2010 at 8:06 am

    Ecography, Volume 32, Issue 5, Date: October 2009, Pages: 807-817

    W. Daniel Kissling, Néstor Fernández, José M. Paruelo

    “Livestock predation and associated human-carnivore conflicts are increasing worldwide and require the development of methods and concepts for risk assessment and conflict management. Here we use knowledge on habitat preference and distribution of pumas and provide a first assessment of the spatial risk of livestock to puma depredation in Patagonian ranches, Argentina. In an initial step, we developed a rule-based habitat model in a Geographic Information System (GIS) to predict the distribution of puma habitat at a regional scale in Patagonia. We then used empirically derived puma occurrence records from Patagonian ranches 1) to test our regional habitat predictions, and 2) to evaluate if paddock characteristics (vegetation cover, topography, and distance to roads) contribute to explain puma occurrences within ranches. Finally, we simulated three livestock management scenarios differing in their spatial and seasonal allocation of livestock to paddocks, and compared the likelihood of livestock exposure to pumas among scenarios. At a regional scale, 22% of the study region was predicted to be suitable for puma home ranges. The greatest uncertainty in these predictions resulted from assumptions on woody vegetation cover requirements at the home range scale. Within ranches, puma occurrences were positively associated with paddock topography, woody vegetation cover on paddocks, and proximity to predicted regional puma habitat. Comparing the risk of predation by puma among simulated livestock management scenarios implied that rotating livestock during seasons may help to reduce the likelihood of livestock exposure to pumas. Our results show the usefulness of rule-based habitat models for describing broad-scale carnivore distributions and for aiding risk assessments to mitigate conflicts between predators and human activities.”

    Spatial and Temporal Analysis of Recent Climatological Data in Tanzania

    In Environmental Science, Spatial Analysis, Statistics, Temporal Analysis on April 14, 2010 at 7:44 am

    Journal of Geography and Regional Planning, Vol. 3(3), pp. 044-065, March 2010

    Ladislaus B. Chang’a, Pius Z. Yanda, and James Ngana

    “Recent climate variability over Tanzania is evaluated through the analysis of spatial and temporal distributions of meteorological variables including rainfall, relative humidity (RH), maximum temperature (Tmax) and minimum temperature (Tmin) in an annual and seasonal time scale for 30 years (1971 – 2000) at 45 meteorological stations for rainfall and 27 stations for Tmax, Tmin and RH. Statistical parameters including mean (ME), coefficient of variation (CV) and skewness (SK) are computed and analyzed. These parameters are mapped using Surfer software. Seasonal contribution of each of the four seasons (JF, MAM, JJAS and OND) is assessed. It has been found that, for most of the bimodal areas, nearly 50% of the annual rainfall is contributed by MAM season. In all four seasons, rainfall, in most of the stations is characterized by a slight asymmetrical distribution with stronger spatial and temporal variability. Tmax, Tmin and RH however, exhibit a near normal distribution with significantly less variability.”

    International Variations in Life Expectancy: A Spatio-temporal Analysis

    In Social Science, Spatial Analysis, Temporal Analysis on April 14, 2010 at 7:38 am

    Tijdschrift voor Economische en Sociale Geografie, 2010, vol. 101, issue 1, pages 73-90

    Min Hua Jen, Ron Johnston, Kelvyn Jones, Richard Harris, and Axel Gandy

    “Life expectancy at birth has increased substantially at the global scale over recent decades, but the improvements have not been experienced equally across all countries – in large part reflecting changes in economic and social situations. To identify the spatial variations in life expectancy at birth across a large number of countries over a 33-year period, this paper provides an expository account of a developing modelling methodology for the analysis of spatio-temporal trajectories. It identifies broad patterns of change and simultaneously examines between- and within-country variation to assess the degree to which patterns of life expectancy are becoming more or less similar at national and sub-national scales.”

    Analysis of Syntactic and Semantic Features for Fine-grained Event–Spatial Understanding in Outbreak News Reports

    In GIScience, Science, Social Science, Spatial Analysis on April 14, 2010 at 7:22 am

    Journal of Biomedical Semantics, 2010, 1:3 (31 March 2010)

    Hutchatai Chanlekha and Nigel Collier

    “Background: Previous studies have suggested that epidemiological reasoning needs a fine-grained modelling of events, especially their spatial and temporal attributes. While the temporal analysis of events has been intensively studied, far less attention has been paid to their spatial analysis. This article aims at filling the gap concerning automatic event-spatial attribute analysis in order to support health surveillance and epidemiological reasoning.

    “Results: In this work, we propose a methodology that provides a detailed analysis on each event reported in news articles to recover the most specific locations where it occurs. Various features for recognizing spatial attributes of the events were studied and incorporated into the models which were trained by several machine learning techniques. The best performance for spatial attribute recognition is very promising; 85.9% F-score (86.75% precision / 85.1% recall).

    “Conclusions: We extended our work on event-spatial attribute recognition by focusing on machine learning techniques, which are CRF, SVM, and Decision tree. Our approach avoided the costly development of an external knowledge base by employing the feature sources that can be acquired locally from the analyzed document. The results showed that the CRF model performed the best. Our study indicated that the nearest location and previous event location are the most important features for the CRF and SVM model, while the location extracted from the verb’s subject is the most important to the Decision tree model.”

    Environmental Risk Mapping of canine leishmaniasis in France

    In Environmental Science, Modeling, Spatial Analysis on April 13, 2010 at 8:47 am

    Parasites & Vectors, 2010, 3:31doi:10.1186/1756-3305-3-31

    Lise Chamaille, Annelise Tran, Anne Meunier, Gilles Bourdoiseau, Paul Ready, and Jean-Pierre Dedet

    “Background: Canine leishmaniasis (CanL) is a zoonotic disease caused by Leishmania infantum, a Trypanosomatid protozoan transmitted by phlebotomine sandflies. Leishmaniasis is endemic in southern France, but the influences of environmental and climatic factors on its maintenance and emergence remain poorly understood. From a retrospective database, including all the studies reporting prevalence or incidence of CanL in France between 1965 and 2007, we performed a spatial analysis in order to i) map the reported cases in France, and ii) produce an environment-based map of the areas at risk for CanL. We performed a Principal Component Analysis (PCA) followed by a Hierarchical Ascendant Classification (HAC) to assess if the locations of CanL could be grouped according to environmental variables related to climate, forest cover, and human and dog densities. For each group, the potential distribution of CanL in France was mapped using a species niche modelling approach (Maxent model).

    “Results: Results revealed the existence of two spatial groups of CanL cases. The first group is located in the Cevennes region (southern Massif Central), at altitudes of 200-1000 m above sea level, characterized by relatively low winter temperatures (1.9degrees C average), 1042 mm average annual rainfall and much forest cover. The second group is located on the Mediterranean coastal plain, characterized by higher temperatures, lower rainfall and less forest cover. These two groups may correspond to the environments favoured by the two sandfly vectors in France, Phlebotomus ariasi and Phlebotomus perniciosus respectively. Our niche modelling of these two eco-epidemiological patterns was based on environmental variables and led to the first risk map for CanL in France.

    “Conclusion: Results show how an ecological approach can help to improve our understanding of the spatial distribution of CanL in France.”

    Spatio-temporal Analysis and Modeling of Short-term Wind Power Forecast Errors

    In Environmental Science, Green Technologies, Modeling, Spatial Analysis, Temporal Analysis on April 13, 2010 at 6:52 am

    Wind Energy, Published Online 12 Apr 2010

    Julija Tastu, Pierre Pinson, Ewelina Kotwa, Henrik Madsen, and Henrik Aa. Nielsen

    “Forecasts of wind power production are increasingly being used in various management tasks. So far, such forecasts and related uncertainty information have usually been generated individually for a given site of interest (either a wind farm or a group of wind farms), without properly accounting for the spatio-temporal dependencies observed in the wind generation field. However, it is intuitively expected that, owing to the inertia of meteorological forecasting systems, a forecast error made at a given point in space and time will be related to forecast errors at other points in space in the following period. The existence of such underlying correlation patterns is demonstrated and analyzed in this paper, considering the case-study of western Denmark. The effects of prevailing wind speed and direction on autocorrelation and cross-correlation patterns are thoroughly described. For a flat terrain region of small size like western Denmark, significant correlation between the various zones is observed for time delays up to 5 h. Wind direction is shown to play a crucial role, while the effect of wind speed is more complex. Nonlinear models permitting capture of the interdependence structure of wind power forecast errors are proposed, and their ability to mimic this structure is discussed. The best performing model is shown to explain 54% of the variations of the forecast errors observed for the individual forecasts used today. Even though focus is on 1-h-ahead forecast errors and on western Denmark only, the methodology proposed may be similarly tested on the cases of further look-ahead times, larger areas, or more complex topographies. Such generalization may not be straightforward. While the results presented here comprise a first step only, the revealed error propagation principles may be seen as a basis for future related work.”

    Geospatial Analysis of HIV-related Social Stigma: A Study of Tested Females across Mandals of Andhra Pradesh in India

    In GIS, Social Science, Spatial Analysis on April 13, 2010 at 6:34 am

    International Journal of Health Geographics, 2010, 9:18

    Rashmi Kandwal,Ellen-Wien Augustijn, Alfred Stein, Gianluca Miscione, Pradeep Garg, and Rahul Garg

    “Background: In Geographical Information Systems issues of scale are of an increasing interest in storing health data and using these in policy support. National and international policies on treating HIV (Human Immunodeficiency Virus) positive women in India are based on case counts at Voluntary Counseling and Testing Centers (VCTCs). In this study, carried out in the Indian state of Andhra Pradesh, these centers are located in subdistricts called mandals, serving for both registration and health facility policies. This study hypothesizes that people may move to a mandal different than their place of residence for being tested for reasons of stigma. Counts of a single mandal therefore may include cases from inside and outside a mandal. HIV counts were analyzed on the presence of outside cases and the most likely explanations for movement. Counts of women being tested on a practitioners’ referral (REFs) and those directly walking-in at testing centers (DWs) were compared and with counts of pregnant women.

    “Results: At the mandal level incidence among REFs is on the average higher than among DWs. For both groups incidence is higher in the South-Eastern coastal zones, being an area with a dense highway network and active port business. A pattern on the incidence maps was statistically confirmed by a cluster analysis. A spatial regression analysis to explain the differences in incidence among pregnant women and REFs shows a negative relation with the number of facilities and a positive relation with the number of roads in a mandal. Differences in incidence among pregnant women and DWs are explained by the same variables, and by a negative relation with the number of neighboring mandals. Based on the assumption that pregnant women are tested in their home mandal, this provides a clear indication that women move for testing as well as clues for explanations why.

    “Conclusions: The spatial analysis shows that women in India move towards a different mandal for getting tested on HIV. Given the scale of study and different types of movements involved, it is difficult to say where they move to and what the precise effect is on HIV registration. Better recording the addresses of tested women may help to relate HIV incidence to population present within a mandal. This in turn may lead to a better incidence count and therefore add to more reliable policy making, e.g. for locating or expanding health facilities.”

    A Spatio-temporal Modelling Framework for Assessing the Fluctuations of Avalanche Occurrence Resulting from Climate Change

    In Climate Change, Environmental Science, Modeling, Spatial Analysis, Statistics, Temporal Analysis on April 12, 2010 at 12:33 pm

    Application to 60 Years of Data in the Northern French Alps

    Climatic Change, published online 25 November 2009

    Nicolas Eckert, E. Parent, R. Kies, and H. Baya1

    “Based on a previous township-scale model, a spatio-temporal framework is proposed to study the fluctuations of avalanche occurrence possibly resulting from climate change. The regional annual component is isolated from the total variability using a two-factor nonlinear analysis of variance. Moreover, relying on a Conditional AutoRegressive sub-model for the spatial effects, the structured time trend is distinguished from the random noise with different time series sub-models including autocorrelative, periodic and change-point models. The hierarchical structure obtained takes into account the uncertainty related to the estimation of the annual component for the quantification of the time trend. Bayesian inference is performed using Monte Carlo simulations. This allows a comparison of the different time series models and the prediction of future activity in an explicit unsteady context. Application to the northern French Alps illustrates the information provided by the model’s different components, mainly the spatial and temporal terms as well as the spatio-temporal fluctuation of the relative risk. For instance, it shows no strong modifications in mean avalanche activity or in the number of winters of low or high activity over the last 60 years. This suggests that climate change has recently had little impact on the avalanching rhythm in this region. However, significant temporal patterns are highlighted: a complex combination of abrupt changes and pseudo-periodic cycles of approximately 15 years. For anticipating the future response of snow avalanches to climate change, correlating them with fluctuations of the constraining climatic factors is now necessary.”

    The Evolution of the Epidemic of Charcoal-Burning Suicide in Taiwan: A Spatial and Temporal Analysis

    In ESRI, GIS, Social Science, Spatial Analysis, Temporal Analysis on April 9, 2010 at 7:30 am

    PLoS Medicine, 2010, Volume 7 (1): e1000212

    Shu-Sen Chang, David Gunnell, Benedict W. Wheeler, Paul Yip, and Jonathan A. C. Sterne

    “Background: An epidemic of carbon monoxide poisoning suicide by burning barbecue charcoal has occurred in East Asia in the last decade. We investigated the spatial and temporal evolution of the epidemic to assess its impact on the epidemiology of suicide in Taiwan.

    “Methods and Findings: Age-standardised rates of suicide and undetermined death by charcoal burning were mapped across townships (median population aged 15 y or over = 27,000) in Taiwan for the periods 1999–2001, 2002–2004, and 2005–2007. Smoothed standardised mortality ratios of charcoal-burning and non-charcoal-burning suicide and undetermined death across townships were estimated using Bayesian hierarchical models. Trends in overall and method-specific rates were compared between urban and rural areas for the period 1991–2007. The epidemic of charcoal-burning suicide in Taiwan emerged more prominently in urban than rural areas, without a single point of origin, and rates of charcoal-burning suicide remained highest in the metropolitan regions throughout the epidemic. The rural excess in overall suicide rates prior to 1998 diminished as rates of charcoal-burning suicide increased to a greater extent in urban than rural areas.

    “Conclusions:  The charcoal-burning epidemic has altered the geography of suicide in Taiwan. The observed pattern and its changes in the past decade suggest that widespread media coverage of this suicide method and easy access to barbecue charcoal may have contributed to the epidemic. Prevention strategies targeted at these factors, such as introducing and enforcing guidelines on media reporting and restricting access to charcoal, may help tackle the increase of charcoal-burning suicides.”

    Land Use Dynamic Simulator (LUDAS): A Multi-agent System Model for Simulating Spatio-temporal Dynamics of Coupled Human-landscape System

    In Modeling, Spatial Analysis, Temporal Analysis on April 9, 2010 at 7:23 am

    Ecological Informatics, In Press, Accepted Manuscript, Available online 13 February 2010

    Quang Bao Le, Soo Jin Park, Paul L.G. Vlek

    “Assessment of future socio-ecological consequences of land-use policies is useful for supporting decisions about what and where to invest for the best overall environmental and developmental outcomes. However, the task faces a great challenge due to the inherent complexity of coupled human-landscape systems and the long-term perspective required for sustainability assessment. Multi-agent system models have been recognised to be well suited to express the co-evolutions of the human and landscape systems in response to policy interventions. This paper applies the Land Use Dynamics Simulator (LUDAS) framework presented by Le et al. [Ecological Informatics 3 (2008) 135] to a mountain watershed in central Vietnam for supporting the design of land-use policies that enhance environmental and socio-economical benefits in long term. With an exploratory modelling strategy for complex integrated systems, our purpose is to assess relative impacts of policy interventions by measuring the long-term landscape and community divergences (compared with a baseline) driven from the widest plausible range of options for a given policy. Model’s tests include empirical verification and validation of sub-models, rational evaluation of coupled model’s structure, and behaviour tests using sensitivity/uncertainty analyses. We design experiments of replicated simulations for relevant policy factors in the study region that include (i) forest protection zoning, (ii) agricultural extension and (iii) agrochemical subsidies. As expected, the stronger human-environment interactions the performance indicators involve, the more uncertain the indicators are. Similar to the findings globally summarised by Liu et al. [Science 317 (2007) 1513], time lags between the implementation of land-use policies and the appearance of socio-ecological consequences are observed in our case. Long-term legacies are found in the responses of the total cropping area, farm size and income distribution to changes in forest protection zoning, implying that impact assessment of nature conservation policies on rural livelihoods must be considered in multiple decades. Our comparative assessment of alternative future socio-ecological scenarios shows that it is challenging to attain better either household income or forest conservation by straightforward expanding the current agricultural extensions and subsidy schemes without improving the qualities of the services. The results also suggest that the policy intervention that strengthens the enforcement of forest protection in the critical areas of the watershed and simultaneously create incentives and opportunities for agricultural production in the less critical areas will likely promote forest restoration and community income in long run. We also discuss limitations of the simulation model and recommend future directions for model development.”

    Quantifying Aggregated Uncertainty in Plasmodium falciparum Malaria Prevalence and Populations at Risk via Efficient Space-Time Geostatistical Joint Simulation

    In Spatial Analysis, Statistics, Temporal Analysis on April 9, 2010 at 6:58 am

    PLoS Computational Biology 2010 6(4): e1000724. doi:10.1371/journal.pcbi.1000724

    Peter W. Gething, Anand P. Patil, and Simon I. Hay

    “Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty—the fidelity of predictions at each mapped pixel—but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.”

    Rock Glacier Activity in the South Shetland Islands: DINSAR, Ground-truth and GIS Analysis. Methodology and First Results

    In Environmental Science, GIS, Spatial Analysis on April 9, 2010 at 6:40 am

    Paper accepted for presentation at the 2010 European Space Agency Living Planet Symposium, Bergen, Norway, 28 June to 2 July 2010:

    Jorge, Marco; Vieira, Gonçalo; Catalão, João; Ramos, Miguel

    “Rock glaciers are distinct lobate or tongue-shaped bodies of permafrost that flow in response to the deformation of the ice within. Rock glaciers are relatively rare in oceanic environments so that their study is particularly important and relevant in maritime Antarctic (Serrano & Lopez-Martinez, 2000). Furthermore, being located in a region where the climate warming is particularly strong, the South Shetlands archipelago is a privileged place for investigation on the response of permafrost degradation and deformation rates to the climatic forcing. The ice-free coastal zones where the rock glaciers occur show mean annual air temperatures slightly below 0°C, making this region one of the best places on Earth to study the response of rock glaciers to climate change.

    “In the South Shetlands, the field work logistics are complex, mainly due to the limitations on transport, harsh weather conditions, but also accouting for the environmental impact restrictions imposed by the Antarctic Treaty. Therefore, the use of active remote sensing systems is an excellent way to monitor the deformation of the terrain where rock glaciers occur. Serrano & Lopez-Martinez (2000) have surveyed most of the rock glaciers in the archipelago, but data on movement rates is still lacking. Differential interferometry of SAR images (DINSAR) from ERS 1-2 and ENVISAT sensors allow to monitor the activity of rock glaciers parsimoniously (good spatial resolution and measurement accuracy in a large area), in a way that no other technique would permit.

    “Our approach focuses on different timescales of activity reflecting distinct climatic controls. “Permanent Scatterers pixels” identified in long temporal series of interferometric SAR images will be used to obtain the inter-annual movement rates of the rock glaciers. Interferograms with temporal baselines from 1 day (tandem pairs) to 1 year will allow to explore the DINSAR signal of each rock glacier. Following the methodology proposed by Lambiel et al. (2009), a classification of all features according to the rate of activity will be made. The specific physical conditions of the study area, the small dimensions of the features being monitored and large differences in rates of activity (i.e., the very distinct DINSAR signals) demand a preliminary focus on the specificity of the DINSAR analysis, a task whose results we will present in the 2010 ESA conference. Field test sites will be installed in Livingston and King George islands in order to obtain ground truth for validation and complement DINSAR results. Hurd rock glacier, in Livingston Island will be the main target of one-year interval detailed geodetic ground surveys using DGPS and Total Laser Station measurements.

    “The high rates of geomorphic dynamics of the periglacial terrain provides an opportunity to perform an innovative spatial analysis using the DINSAR deformation grid. Ground deformation data will be analysed using empiro-statistical techniques accouting for different independent variables (e.g., bivariate analysis – informative value and GLM – logistic regression), such as: i) detailed geomorphological surveys; ii) geographical variables derived from the DEM; iii) and field data from monitoring sites maintained by our group, such as weather stations, shallow and deep boreholes for permafrost monitoring, active layer thickness (CALM sites) and snow mantle thickness. The deformation grid is a clear dependent variable, with no problems of multicollinearity with the variables assumed and inputted in the models as explanatory-independent variables, that can be used in two distinct but related levels of analysis: i) the relationship between the classified geomorphic features (geomorphological mapping) and the movement of the terrain; ii) the influence of the geographical factors on the terrain deformation. By combining i and ii we should reach a better level of knowledge on periglacial dynamics.”

    Bioenergy and Land Use: A Spatial-agent Dynamic Model of Energy Crop Production in Illinois

    In Environmental Science, GIS, Modeling, Social Science, Spatial Analysis on April 8, 2010 at 7:42 am

    International Journal of Environment and Pollution, 2009 – Vol. 39, No.1/2

    Jurgen Scheffran and Todd BenDor

    “To reduce dependence on foreign oil and natural gas and address concerns about climate change, the USA is increasingly developing renewable, domestic energy sources, notably biomass for the production of ethanol and biodiesel. Illinois, as one of the farming states of the Midwest, has significant potential to produce bioenergy crops. Land requirements place these crops in competition with traditional agricultural uses. To understand this interaction, this study examines the spatial and economic conditions for introducing bioenergy crops into the landscape in Illinois, which varies in soil quality and climatic conditions, and therefore in the profitability of various land uses. We use a spatial dynamic model to represent the decisions of individual farmer agents who select crops to increase their income. With this dynamic, evolutionary game approach we study the changing spatial arrangement of four key crops (corn, soybeans, miscanthus and switchgrass) which is influenced by decision rules, demands, prices, subsidies and carbon credits as well as the location of ethanol plants and transportation patterns. With a growing demand for biofuels farmers adjust their priorities towards productive bioenergy crops such as switchgrass and miscanthus which result in new land-use patterns across Illinois.”

    Temporal-Spatial Analysis of Guatemala’s Religious Competition and Affiliation

    In ESRI, GIS, Social Science, Spatial Analysis, Temporal Analysis on April 8, 2010 at 6:57 am

    Poster by Rachel M. McCleary, Jeff Blossom, and Jose Pesina, Harvard University

    “Since the late 1800’s, Protestant – particularly Evangelical and Pentecostal – churches have been competing with the once-monopolistic Roman Catholic Church. This study examines religious competition of Protestants with Roman Catholicism using data from the ledgers of the dance workshops (morerias).

    “The dances in Guatemala are directly related to Roman Catholicism, for example, they are performed on a town’s saint’s day. Data in the ledgers beginning in 1900 until 2009 permit an analysis of where the dances continue to be or are no longer being performed. Using data on religious affiliation in Guatemala combined with the ledger data allows a spatial analysis of where the Evangelicals are gaining converts.

    “Village and moreria locations were georeferenced using historic paper and digital maps of Guatemala. Cartographically the dance ledgers provide a very rich dataset that can be depicted by geography, time, magnitude of dances, and directionally by dance sites and morerias. The background for the maps is a shaded relief image made from a digital elevation model intended to depict the rugged and varying terrain of Guatemala.”

    The Spatial and Temporal Variability of Groundwater Recharge in a Forested Basin in Northern Wisconsin

    In Environmental Science, GIS, Spatial Analysis, Temporal Analysis on April 8, 2010 at 6:48 am

    Hydrological Processes, Volume 24, Issue 4, Date: 15 February 2010, Pages: 383-392

    W. R. Dripps, K. R. Bradbury

    “Recharge varies spatially and temporally as it depends on a wide variety of factors (e.g. vegetation, precipitation, climate, topography, geology, and soil type), making it one of the most difficult, complex, and uncertain hydrologic parameters to quantify. Despite its inherent variability, groundwater modellers, planners, and policy makers often ignore recharge variability and assume a single average recharge value for an entire watershed. Relatively few attempts have been made to quantify or incorporate spatial and temporal recharge variability into water resource planning or groundwater modelling efforts. In this study, a simple, daily soil-water balance model was developed and used to estimate the spatial and temporal distribution of groundwater recharge of the Trout Lake basin of northern Wisconsin for 1996-2000 as a means to quantify recharge variability. For the 5 years of study, annual recharge varied spatially by as much as 18 cm across the basin; vegetation was the predominant control on this variability. Recharge also varied temporally with a threefold annual difference over the 5-year period. Intra-annually, recharge was limited to a few isolated events each year and exhibited a distinct seasonal pattern. The results suggest that ignoring recharge variability may not only be inappropriate, but also, depending on the application, may invalidate model results and predictions for regional and local water budget calculations, water resource management, nutrient cycling, and contaminant transport studies. Recharge is spatially and temporally variable, and should be modelled as such.”

    Grid-based Distribution Model for Simulating Runoff and Soil Erosion from a Large-scale River Basin

    In Environmental Science, GIS, Modeling, Spatial Analysis on April 7, 2010 at 9:13 am

    Hydrological Processes, Volume 24 Issue 5, Pages 641 – 653

    Guoqiang Wang, H. A. P. Hapuarachchi,, Kuniyoshi Takeuchi, Hiroshi Ishidaira

    “Grid-based modelling is an effective approach for handling the spatial heterogeneity of basin characteristics, such as land use, soil, rainfall and topographical information. In this study, the grid-based block-wise use of TOPMODEL together with the Muskingum-Cunge (BTOPMC) model (block-wise use of TOPMODEL together with the Muskingum-Cunge) was improved by using an erosion module to estimate soil erosion and sediment outflow during storm events. Instead of representing a grid using a single erosion type, the model accounts for the erosion caused by both raindrop detachment in the sheet area as well as concentrated flow detachment in the channel area. The sediment transport process is simulated at the assumed river channel networks, which avoids the problems that are caused by the difference between the channel widths in the upstream and downstream areas. This also enables the model to be applicable in simulating soil erosion and sediment outflow from a large river basin. Geographic information system (GIS) techniques have been utilized in the model to delineate the river network and extract the basin information from the digital elevation model (DEM) data. Through a case study in China’s Lushi basin, the improved BTOPMC model got an average Nash-Sutcliffe (NS) efficiency of about 86·1% in discharge simulations and an average NS efficiency of about 75% in sediment outflow simulations. Overall, the results show a satisfactory accuracy for all of the selected events. Moreover, by analysing the spatial distribution of soil erosion or deposition, the erosion-prone areas can be identified and prioritized. “

    China’s Spatial-temporal Pattern of Population and Energy

    In Environmental Science, Geography, Social Science, Spatial Analysis, Temporal Analysis on April 6, 2010 at 8:00 am

    International Journal of Global Energy Issues, 2009 – Vol. 31

    Xiao-Wei Ma

    “Irregular development among regions is one of the fundamental realities of China, especially in social and economic progress. Moreover, there is no exception in the development of population and energy. In this paper, we explore the characteristics of the seven most prominent patterns of regional population–energy development distribution. Furthermore, analysis is made of problems associated with sustainable population–energy development. The concluding section identifies policy implications for sustainable regional population–energy development.”

    Algorithms for constrained k-nearest neighbor queries over moving object trajectories

    In GIScience, Spatial Analysis, Temporal Analysis on April 5, 2010 at 12:19 pm

    GeoInformatica, Volume 14, Number 2 / April, 2010

    Yunjun Gao, Baihua Zheng, Gencai Chen, and Qing Li

    “An important query for spatio-temporal databases is to find nearest trajectories of moving objects. Existing work on this topic focuses on the closest trajectories in the whole data space. In this paper, we introduce and solve constrained k-nearest neighbor (CkNN) queries and historical continuous CkNN (HCCkNN) queries on R-tree-like structures storing historical information about moving object trajectories. Given a trajectory set D, a query object (point or trajectory) q, a temporal extent T, and a constrained region CR, (i) a CkNN query over trajectories retrieves from D within T, the k (≥ 1) trajectories that lie closest to q and intersect (or are enclosed by) CR; and (ii) an HCCkNN query on trajectories retrieves the constrained k nearest neighbors (CkNNs) of q at any time instance of T. We propose a suite of algorithms for processing CkNN queries and HCCkNN queries respectively, with different properties and advantages. In particular, we thoroughly investigate two types of CkNN queries, i.e., CkNNP and CkNNT, which are defined with respect to stationary query points and moving query trajectories, respectively; and two types of HCCkNN queries, namely, HCCkNNP and HCCkNNT, which are continuous counterparts of CkNNP and CkNNT, respectively. Our methods utilize an existing data-partitioning index for trajectory data (i.e., TB-tree) to achieve low I/O and CPU cost. Extensive experiments with both real and synthetic datasets demonstrate the performance of the proposed algorithms in terms of efficiency and scalability.”

    Can Payments for Watershed Services Help Finance Biodiversity Conservation? A Spatial Analysis of Highland Guatemala

    In Environmental Science, Social Science, Spatial Analysis on April 5, 2010 at 8:04 am

    Journal of Natural Resources Policy Research, Volume 2, Issue 1 January 2010 , pages 7 – 24

    Stefano Pagiola, Wei Zhang, and Ale Colom

    “Payments for environmental services (PES) are a promising mechanism for conservation. PES could either provide additional funding for protected areas, pay land users to conserve biodiversity outside protected areas, or both. PES require a secure long-term source of financing to work effectively. Obtaining payments directly for biodiversity conservation is difficult, however. In most cases, water users are the most likely source, either directly or indirectly. Thus the potential for PES to help conserve biodiversity depends, in a large measure, on the degree to which areas of interest for conservation of water services overlap with areas of interest for conservation of biodiversity. This paper examines the extent of such an overlap in the case of highland Guatemala. The results show that this potential varies substantially within the country, with some biodiversity conservation priority areas having very good potential for receiving payments, and others little or none. Overall, about a quarter of all biodiversity conservation priority areas have potential for receiving payments. Thus PES are far from being a silver bullet for biodiversity conservation, but they can make a meaningful contribution to this objective.”

    Spatial Analysis of Three Agrichemicals in Groundwater of Isfahan using GS+

    In Environmental Science, Spatial Analysis, Statistics on April 5, 2010 at 6:44 am

    Iranian Journal of Environmental Health Science & Engineering, 2010, Vol. 7, No. 1, pp. 71-80

    M. M. Amin, A. Ebrahimi, M. Hajian, N. Iranpanah, and B. Bina

    “The purpose of this study was to undertake a spatial analysis of total organic carbon, electrical conductivity and nitrate, in order to produce a pollution dispersion and prediction map for the investigated area in the province of Isfahan in Iran. The groundwater samples were collected from a zone as a pilot study area of 80 km2, including 25 water wells, based on the criteria of vulnerability assessment projects, that is, about one well per 3 km2, during four seasons in 2008-09. In order to make any inferences about the areas that did not have well data, a statistical relationship between explanatory total organic carbon, electrical conductivity and nitrate variables related to well coordination was developed. The probability of the presence of elevated levels of the three compounds in the groundwater was predicted using the best-fit variogram model. According to spatial analysis, the highest R2=0.789 achieved was related to electrical conductivity and followed the exponential model with 0.266 for NO3- (spherical model) and 0.322 for total organic carbon (exponential model) in the spring 2009. This showed the high confidence level for electrical conductivity dataset and forecasted trends. The results of the spatial analysis demonstrated that the transfer trends of electrical conductivity in the groundwater resources followed the route of groundwater movement in all seasons. However, for nitrate and total organic carbon, a definite trend was not obtained and pollution dispersion depended on many parameters.”

    ITA Face a Dedicated WEBGIS for Added Value Information Delivery

    In Environmental Science, GIS, Spatial Analysis on April 5, 2010 at 5:57 am

    Paper accepted for presentation at the 2010 European Space Agency Living Planet Symposium, Bergen, Norway, 28 June to 2 July 2010:

    Massimo, Musacchio; Buongiorno, Fabrizia; Doumaz, Fawzi

    “The main goal of the geophysical cluster within SAFER project is to define, develop and demonstrate tools and products, based on the EO data, to support the risk management decision procedures. This is achieved through the generation of specific products created by using EO data and the dissemination of the information to the end-users in a form suitable for decision making.

    “The SAFER project will provide support to the crisis risk management activities (Volcanoes and Earthquakes) in Europe and on Demand outside Europe. For this reason the set of products, that has been selected in the preparatory phase, cover the needs related to crisis phase of the volcanic and earthquakes risk. The facility will be provided with geophysical features selected in order to use it into specific areas, in Italy and in France for volcanoes and Italy and Romania fpr Earthquakes.

    “The following main objectivies are foreseen, 1) a data handling tool supporting the reception, acceptance and preprocessing of the input data, 2) a web-GIS Analysis tool supporting the analysis and long term monitoring of the products (including an MMI with the end-user, 3)processing module supporting the generation of the products and their the storage in a local DB.”

    River Channel Migration: A Remote Sensing and GIS Analysis

    In ESRI, Environmental Science, GIS, Imagery, Spatial Analysis on April 2, 2010 at 6:56 am

    Paper accepted for presentation at the 2010 European Space Agency Living Planet Symposium, Bergen, Norway, 28 June to 2 July 2010:

    Islam, Md. Tariqul

    “Remote sensing and geographic information system provide tools for quantitative and qualitative river morphological analysis. Bangladesh is a riverine, flood prone country and, the Padma and the Jamuna are two of major three rivers in the country. The aim of this research is to monitor the channel migration of the Padma and the Jamuna rivers since 1977 to 2004 using remote sensing and GIS. The Landsat images were processed using PCI Geomatica and ArcGIS 9.3 was used for GIS analysis. The Landsat images were visualized and identified nine locations to investigate the channel migration. The images were classified into two broad categories, i.e. water and non-water body. ArcGIS 9.3 was used to transfer these classified images into GIS layers. A standard measurement tool of ArcGIS was applied to measure the movement of river channel based on initial river channel in 1977. General trend of the Padma and the Jamuna River channel migration at locations A, B, C, D, F, G, H and I towards north, northeast and southwest eventually, north, northeast, east, east, west and west respectively. The confluence point of the Padma and Jamuna (at location E) migrated toward southeast with high rate. During 1977-2004, it migrated about 9000m toward southeast. Trend of migration of the confluence point was faster than any other locations in the channel of the Padma River.”

    Spatial Assessment of Groundwater Demand in Northwest Bangladesh

    In Environmental Science, GIS, Social Science, Spatial Analysis on April 2, 2010 at 6:27 am

    International Journal of Water, 2010 – Vol. 5, No.3 pp. 267 – 283

    Shamsuddin Shahid

    “Spatial assessment of groundwater demand has been carried out as a part of sustainable water resources management in Northwest Bangladesh. ASTER images are synthesised for extracting the extent of irrigated land. The Penman–Monteith method is used for the calculation of reference evapotranspiration from climate data. Soil information is used for the estimation of water requirement for land preparation and seepage loss. The domestic water demand is calculated from population census data. The study shows that the irrigation water demand in the study area varies between 839 mm and 1212 mm, which amounts to about 96.5% of total groundwater demand.”

    Mapping Rurality: Analysis of Rural Structure in Turkey

    In ESRI, GIS, Geography, Social Science, Spatial Analysis on April 1, 2010 at 12:42 pm

    International Journal of Agricultural Resources, Governance and Ecology, 2009 – Vol. 8, No.2/3/4 pp. 130 – 157

    Aliye Ahu Gulumser, Tuzin Baycan-Levent, and Peter Nijkamp

    “The aim of this study is to describe the rural structure of Turkey on the basis of various rural indicators. The data and information used for evaluation of rurality are based mainly on the Turkish Statistical Institute (TURKSTAT) data. Factor analysis, one of the well-known multidimensional techniques is deployed to evaluate rural structure of Turkey while using geographical information system (GIS) based software ArcGIS to map out Turkey’s rurality based on the results of factor analysis. The results of the study show that Turkey is dominantly rural in terms of traditional meaning of rurality while stressing on divergences and differences between Turkey’s provinces. On the other hand, according to the results of the study, in terms of new definition of rural areas as a part of tourism sector, Turkey does not have a dominant rural character.”

    Research on Distributed Geo-Computing Oriented Self-organized P2P Network

    In GIScience, Spatial Analysis on April 1, 2010 at 9:18 am

    Proceedings of the Second Symposium International Computer Science and Computational Technology (ISCSCT ’09), Huangshan, P. R. China, 26-28,Dec. 2009, pp. 205-208

    Xicheng Tan and Fang Huang

    “With the extending of spatial information system into the distributed network environment, it faces some challenges including the mass data character of the spatial data, the limited band width of current network, the devilishly centralized spatial information management and geographic computing resources, as well as the higher requirements of the spatial information service capability. For overcoming these challenges, this paper puts forward a Geo-Computing oriented self-organized P2P network model, and the structure of the P2P network is designed. For performing spatial analysis tasks, the paper also analyzes the spatial data management on the self-organized P2P network. Finally, the test system, which has simulated the slope analyzing based on the self-organized P2P network, is also presented. Compare with the single server based spatial analysis systems the P2P computing based analysis task performs more efficiently and has a better capability of supporting huge amount of requests from the users.”

    EDGIS: A Dynamic GIS based on Space Time Points

    In GIS, Spatial Analysis, Temporal Analysis on April 1, 2010 at 8:14 am

    International Journal of Geographical Information Science, Volume 24, Issue 3 March 2010 , pages 329 – 346

    Edward Pultar; Thomas J. Cova; May Yuan; Michael F. Goodchild

    “Contemporary GIS can handle static spatial data for querying and visual representation, but the temporal dimension remains a challenge. This paper addresses the need for a dynamic GIS capable of managing complex data types. The design relies on a representation of the theoretical spatiotemporal primitive known as the ‘geo-atom’. This paper proposes a novel and implemented data structure called the space time point (STP) built on this theory. With the STP representation, spatiotemporal data queries can be posed to return useful results about dynamic geographic phenomena and their interaction. Two key challenges addressed in this research are (1) data structures to represent hybrid (object and field) spatiotemporal phenomena and (2) the design of a dynamic GIS interface. These challenges are addressed by the implementation of the system, referred to as ‘Extended Dynamic GIS (EDGIS)’, that uses the proposed STPs. The EDGIS system is described from theory to its implementation in Java™ and a series of application examples are described followed by performance metrics. The paper concludes with a discussion of areas for further research such as integration of the system with geo-sensor networks, hazards, transportation, and location-based services (LBS).”

    Managing Sensor Traffic Data and Forecasting Unusual Behaviour Propagation

    In GIScience, Spatial Analysis, Temporal Analysis on March 31, 2010 at 9:12 am

    GeoInformatica, Volume 14, Number 3 / July, 2010

    Claudia Bauzer Medeiros, Marc Joliveau, Geneviève Jomier, and Florian De Vuyst

    “Sensor data on traffic events have prompted a wide range of research issues, related with the so-called ITS (Intelligent Transportation Systems). Data are delivered for both static (fixed) and mobile (embedded) sensors, generating large and complex spatio-temporal series. This scenario presents several research challenges, in spatio-temporal data management and data analysis. Management issues involve, for instance, data cleaning and data fusion to support queries at distinct spatial and temporal granularities. Analysis issues include the characterization of traffic behavior for given space and/or time windows, and detection of anomalous behavior (either due to sensor malfunction, or to traffic events). This paper contributes to the solution of some of these issues through a new kind of framework to manage static sensor data. Our work is based on combining research on analytical methods to process sensor data, and data management strategies to query these data. The first aspect is geared towards supporting pattern matching. This leads to a model to study and predict unusual traffic behavior along an urban road network. The second aspect deals with spatio-temporal database issues, taking into account information produced by the model. This allows distinct granularities and modalities of analysis of sensor data in space and time. This work was conducted within a project that uses real data, with tests conducted on 1,000 sensors, during 3 years, in a large French city.”

    Spatio-temporal Analysis of the Indus Urbanization

    In GIS, Social Science, Spatial Analysis, Temporal Analysis on March 31, 2010 at 6:31 am

    Current Science, Vol. 98, No. 6, 25 March 2010

    Kavita Gangal, M. N. Vahia, and R. Adhikari

    “The greater Indus valley was home to Neolithic cultures starting from 7000 BCE. They formed the antecedents of the urban Harappan civilization, whose rise and decline are dated to 2600 BCE and 1900 BCE
    respectively. At its peak, the Harappan civilization covered an area of more than a million square kilometres, making it the largest urbanized civilization of the Bronze Age. In this communication, we integrate GIS information on topography and hydrology with radiocarbon and archaeological dates of 1874 sites, to analyse the spatio-temporal growth and decline of the Indus urbanization. Our analysis reveals several large-scale patterns in the growth and decline of urbanism. In the growth phase, urbanism appears to nucleate in three distinct geographical locations, situated in Baluchistan, Gujarat and the Ghaggar–Hakra valley. In the mature phase when urbanism is fully developed, the area distribution of sites follows a Zipfian power law, a feature common to modern urban agglomerations. In the decline phase, the pace of de-urbanization is nonuniform with a strong geographical variation. The decline starts in the Ghaggar–Hakra region, followed by a large-scale collapse in the lower Indus plain, leaving, however, a resilient zone in Gujarat which has a delayed decline. The patterns discerned through our analysis will find use within a Bayesian framework to test hypotheses for the growth and decline of the Harappan civilization.”

    Post-doc Research Associate Position in Migration Modelling at University College London, Centre for Advanced Spatial Analysis

    In Education, GIS, Modeling, Social Science, Spatial Analysis, Statistics on March 30, 2010 at 9:48 am

    “This is an EPSRC-funded research position working on the Explaining, Modelling & Forecasting Global Dynamics (ENFOLD-ing) project.   The main purpose of this post is to initiate, develop, design and be responsible for the delivery of a programme of high quality quantitative research into the relevant statistical, geographical and theoretical aspects related to migration analysis, as well as related issues to the overall aims of the ENFOLD project; this includes working in and contributing to the wider ENFOLD team effort.

    “Funding is available for two years in the first instance.

    “Requirements

    “The ideal candidate will have extensive programming experience (in C#, C++, Java, Python etc) , expertise in designing, constructing and analysing large databases and a PhD in any of the following:

    • a quantitative speciality within a social science discipline such as; statistics, geography, economics, sociology, epidemiology/ public health, GIS, spatial analysis
    • a science discipline with experience in social science applications, such as computer science, maths, physics, medicine, and any other relevant disciplines.”

    More information

    Identifying Spatial Patterns of Recovery and Abandonment in the Post-Katrina Holy Cross Neighborhood of New Orleans

    In Geography, Social Science, Spatial Analysis on March 30, 2010 at 7:43 am

    Cartography and Geographic Information Science, Volume 37, Number 1, January 2010 , pp. 45-56(12)

    Curtis, Andrew; Duval-Diop, Dominique; Novak, Jenny

    “The devastation caused by Hurricane Katrina is still being felt by many neighborhoods of New Orleans and along the Gulf Coast. As these communities struggle to recover, academia has been forced to acknowledge that there is little known or theorized about the spatial processes of recovery, especially at the fine scale. As a result this paper will investigate how post-disaster landscape characteristics can be extracted from spatial video data for neighborhoods of New Orleans. These will be turned into a statistical surface using analytical approaches more commonly applied in spatial epidemiology. Spatial patterns of abandonment and recovery will be identified that can be used as a basis for a next round of causative investigation. The paper finds that by using the spatial overlap of four different analyses involving two different data input locations and two filter sizes, the Holy Cross neighborhood of New Orleans does indeed reveal areas with higher rates of recovery, and continuing abandonment. However, even within these areas, spatial heterogeneity can be found. This paper uses Google Street View to mirror spatial video data collected in participatory collaborations with New Orleans community groups so that readers can replicate the methods presented here for other neighborhoods of New Orleans.”

    Environmental Controls on Multiscale Spatial Patterns of Salt Marsh Vegetation

    In Environmental Science, Spatial Analysis on March 30, 2010 at 6:20 am

    Physical Geography, Volume 31, Number 1 / January-February 2010

    Daehyun Kim, David M. Cairns, and Jesper Bartholdy

    “In coastal environments, biogeographic patterns are generally influenced by surface elevation and horizontal distance from sea water. However, it is still unclear whether these major topographic factors are significant controls of vegetation patterns across spatial scales at which different physical processes operate. This study investigated such a topography-vegetation relationship in a Danish salt marsh, focusing upon two scales: a macro-scale (ca. 500 m) across the marsh platform, encompassing seaward and landward areas, and a meso-scale (ca. 25 m) across tidal creeks. While long-term sea-level variation and grazing influenced the macro-scale pattern, short-term fluvial-geomorphic processes drove the meso-scale pattern. Despite these different underlying processes, similar floristic gradient structures between the two scales were identified by nonmetric multidimensional scaling. The gradient represented an ecological sequence from early to late succession, and strongly correlated with surface elevation. However, the gradient did not show any significant relationship with distance from shoreline or tidal channels. Our results suggest that, in salt marshes, elevation plays a still more important ecological role than the horizontal position relative to sea water at both macro- and meso-scales. The presence of one such fundamental component makes the system relatively simple, and will facilitate future scaling attempts.”

    Spatio-temporal Patterns of Pressure over the North Atlantic

    In Environmental Science, Spatial Analysis, Temporal Analysis on March 29, 2010 at 8:46 am

    International Journal of Climatology, published online 20 Nov 2009

    Sílvia Antunes, Oliveira Pires, and Alfredo Roch

    “The North Atlantic mean sea level pressure field variability is analysed. A space-time study is performed using multichannel singular spectral analysis, allowing the detection of significant space-time modes of variability with periodicity behaviour. It is shown that there is a space variability associated with the time variability of the pressure field. The oscillation is not quasi-meridional but has different orientations, rotating in a cycle, with a periodicity of about 9 years, from the positive North Atlantic oscillation (NAO) phase through the negative NAO phase and again to the positive phase. This periodicity behaviour was previously detected in the temporal principal components extracted from a principal component analysis but, in the time domain, it was found as not significant. Furthermore, the analysis of a long series of an NAO index had already revealed similar periodicity behaviour. Copyright © 2009 Royal Meteorological Society”

    Anomaly Detection and Spatio-temporal Analysis of Global Climate System

    In Climate Change, Environmental Science, Spatial Analysis, Temporal Analysis on March 29, 2010 at 8:02 am

    International Conference on Knowledge Discovery and Data Mining, Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data, Paris, France 2009

    Mahashweta Das and Srinivasan Parthasarathy

    “Knowledge discovery from temporal, spatial and spatio-temporal data is pivotal for understanding and predicting the behavior of Earth’s ecosystem model. An important influence leaving its impact on the ecosystem is the global climate system. In this paper, the Earth Science data that we have analyzed consists of daily global air temperature and precipitation measurements, aggregated from heterogeneous sensors for fifty years (1950–1999). The enormous amount of data that is available for analysis requires employment of data mining techniques for discovering interesting patterns, detecting significant changes and extracting meaningful insights from the data. Our work considers the problem of detecting anomalous (abnormal or unexpected) behavior in the global climate system, discovering teleconnection patterns and providing consequential insights to the analysts.”

    GIS Spatial Analysis of Population Exposure to Fine Particulate Air Pollution in Beijing, China

    In Environmental Science, GIS, Spatial Analysis on March 23, 2010 at 7:31 am

    Environmental Geosciences, March 2010; v. 17; no. 1; p. 1-16

    Tao Tang, Wenji Zhao, Huili Gong, Xiaojuan Li, Ke Zang, Joel D. Bernosky, Wenhui Zhao, and Shanshan Li

    “This research diagnoses the exposure of the residential population and the vulnerable groups of children and elderly people to air particle pollution in urban Beijing. We surveyed the air particle pollutant concentrations in the field. We used a universal kriging model in a geographic information system to interpolate the spatial distributions of each pollutant. Spatial patterns of air particle pollution were overlaid to community-level population distributions to identify the community exposures to high air particle pollution. Spatial and statistic modeling reveals that high concentration of ultra-fine air particles of particulate matter (PM) 0.3 µm is strongly associated with high-population urban communities in the southwest and central western areas in the winter season. By contrast, all the other particle sizes surveyed (PMs of 0.5, 1.0, 3.0, and 5.0 µm) indicate that high concentrations in the summer are associated with high-population communities. Reversed spatial and temporal patterns between PM 0.3 µm and other particle sizes suggest that PM 0.3 µm may have different sources of origin.”

    Analytical 3D Views and Virtual Globes — Scientific Results in a Familiar Spatial Context

    In Science, Spatial Analysis, Visualization on March 23, 2010 at 7:24 am

    ISPRS Journal of Photogrammetry and Remote Sensing, In Press, Corrected Proof, Available online 6 January 2010

    Dirk Tiede, Stefan Lang

    “In this paper we introduce analytical three-dimensional (3D) views as a means for effective and comprehensible information delivery, using virtual globes and the third dimension as an additional information carrier. Four case studies are presented, in which information extraction results from very high spatial resolution (VHSR) satellite images were conditioned and aggregated or disaggregated to regular spatial units. The case studies were embedded in the context of: (1) urban life quality assessment (Salzburg/Austria); (2) post-disaster assessment (Harare/Zimbabwe); (3) emergency response (Lukole/Tanzania); and (4) contingency planning (faked crisis scenario/Germany). The results are made available in different virtual globe environments, using the implemented contextual data (such as satellite imagery, aerial photographs, and auxiliary geodata) as valuable additional context information. Both day-to-day users and high-level decision makers are addressees of this tailored information product. The degree of abstraction required for understanding a complex analytical content is balanced with the ease and appeal by which the context is conveyed.”

    Using Bioclimatic Envelopes to Identify Temporal Corridors in Support of Conservation Planning in a Changing Climate

    In Climate Change, Environmental Science, GIS, Spatial Analysis, Temporal Analysis on March 23, 2010 at 7:12 am

    Forest Ecology and Management, 258, p.S64-S74, Dec 2009

    Rose, N.A. / Burton, P.J.

    “Current and expected shifts in climate are threatening global biodiversity and are forcing managers to re-evaluate how they plan for the protection of species and ecosystems. We propose and illustrate a methodology for identifying geographic locations where climate is expected to remain within the tolerances of conservation targets despite a generally warming climate. Using Generation 3 of the Canadian General Circulation Model and ClimateBC (a climate interpolation and downscaling tool), bioclimatic envelopes were developed for three examples of forest conservation targets. The geographic distribution of the resulting envelopes was projected for four timeslices, and then overlaid using ArcMap GIS software. The resultant intersection of points is presumed to indicate locations of persistent climate over the study’s timeframe. Next, a target’s current mapped distribution was overlaid with the distribution of climate expected to remain within its bioclimatic envelope; the intersection of these points is considered the target’s “temporal corridor.” Current locations with persistent climate are thus expected to provide climatic continuity over time, sufficient to sustain the conservation target. Whereas landscape corridors can provide connectivity in geographic space, temporal corridors are projected to provide continuity in climatic space and over time. The identification of such locations facilitates prioritization of sites for the acquisition or designation of protected areas, and provides guidance on where other current management policies and practices can persist. The projection and mapping of temporal corridors is conceptually simple, yet this can be a powerful tool with many potential applications to assist natural resources planners and managers in a rapidly changing environment.”

    Web-based Visualization and Analysis of NASA Ecological Data

    In Environmental Science, Spatial Analysis, Visualization on March 22, 2010 at 9:28 am

    Where 2.0 Conference, 30 March – 01 April 2010, San Jose, CA

    Sam Hiatt and Andrew Michaelis

    “The Terrestrial Observation and Prediction System (TOPS) at NASA Ames Research Center’s Ecological Forecasting Lab generates a suite of gridded data products in near real-time that are designed to enhance management decisions related to droughts, forest fires, human health, as well as crop, range, and forest production. Our data products hold great potential for supporting research and real-world applications. In order to provide enhanced access to our data and to promote multidisciplinary collaboration we implement web-based tools for visualization and analysis.”

    Space and Gang Crime: Modeling Social Processes in the Spatial Autocorrelation Matrix

    In Social Science, Spatial Analysis, Statistics on March 22, 2010 at 8:24 am

    Symposium: Using GIS and Spatial Analysis To Better Understand Patterns and Causes of Violence

    AAAS Annual Meeting, 22 February 2010

    George E. Tita

    “Criminologist often implicate urban street gangs as agents of contagion by which crime spreads throughout a geographic region. However, prior studies of the spatial distribution of crime have not explicitly modeled the social networks along with the geography of the gangs (i.e., “turf). by including the “socio-spatial” dimensions of gangs, this study is able to demonstrate that gangs are responsible for the diffusion/distribution of crime in Hollenbeck Policing Area of the City of Los Angeles.”

    Using Spatial Analysis to Prioritize Pedestrian Safety Interventions and Describe Geographic Trends in Pedestrian Safety

    In Geography, Spatial Analysis on March 22, 2010 at 8:18 am

    Transportation Research Board Annual Meeting 2010, Paper #10-4049

    “This paper illustrates the application of several geospatial and analytical tools to the problem of prioritizing pedestrian and other safety improvements in New York City, describes the process used to analyze crashes in New York City, then describes the application of spatial analysis to the problem of contextual project evaluation. An analysis was conducted of the change in pedestrian crashes from the 1992-1996 period to the 2002-2006 period using the kernel density technique. Pedestrian crashes in New York City were found to have decreased in severity and frequency from the mid-1990s to the mid-2000s, but these changes were not evenly distributed across New York City Low-density residential and commercial areas did not experience consistent improvements, except at the locations of major NYCDOT safety implementations, e.g. Queens Boulevard.”

    A Spatial Approach to Select Pilot Counties for Programs to Correct the Biased Sex Ratio at Birth in Shandong Province, China

    In GIS, Social Science, Spatial Analysis, Statistics on March 22, 2010 at 7:17 am

    International Journal of Geographical Information Science, Volume 24, Issue 3 March 2010 , pages 403 – 416

    Kun Zhang; Shawn William Laffan; Songlin Zhang

    “The highly skewed sex ratio at birth (SRB) in China has stimulated numerous studies. However, the geographic distribution of SRB is seldom investigated, particularly at the county level. The need for an understanding at this level has increased since the Chinese government initiated its ‘Care for Girls’ campaign to improve the survival rate of females. This campaign has been initiated in a set of pilot counties. In this article we assess the effectiveness of the set of pilot counties in Shandong province and propose two alternate configurations. To do this, we first assess the spatial distribution of the SRB values by county in Shandong, expressed as a z-score (zSRB) after correcting for the biologically expected SRB value and population size of zero-aged children. A local Moran’s Ii analysis of the zSRB values indicates a significant high-high cluster in the southwest of the province. The Ii, zSRB and female deficit (the difference of the observed from biologically expected number of zero-aged females) were then used to define two alternate configurations for the pilot counties. A comparison of the current and alternate configurations against a Monte Carlo randomisation analysis shows that the current configuration is significantly different from a random selection (p < 0.05) for the two criteria of maximising the aggregate female deficit and maximising the zSRB. Although this is a good result, both alternate configurations were more significant (p < 0.001), and therefore represent potentially better configurations for the campaign given the criteria used. The spatial analysis approach developed here could be used to improve the effectiveness of the Care-for-Girls campaign in Shandong province, and elsewhere in China.”

    Urban Transmission of American Cutaneous Leishmaniasis in Argentina: Spatial Analysis Study

    In GIS, Science, Spatial Analysis, Statistics on March 19, 2010 at 7:32 am

    American Journal of Tropical Medicine and Hygiene, 2010 Mar;82(3):433-40

    Gil JF, Nasser JR, Cajal SP, Juarez M, Acosta N, Cimino RO, Diosque P, Krolewiecki AJ

    “We used kernel density and scan statistics to examine the spatial distribution of cases of pediatric and adult American cutaneous leishmaniasis in an urban disease-endemic area in Salta Province, Argentina. Spatial analysis was used for the whole population and stratified by women > 14 years of age (n = 159), men > 14 years of age (n = 667), and children < 15 years of age (n = 213). Although kernel density for adults encompassed nearly the entire city, distribution in children was most prevalent in the peripheral areas of the city. Scan statistic analysis for adult males, adult females, and children found 11, 2, and 8 clusters, respectively. Clusters for children had the highest odds ratios (P < 0.05) and were located in proximity of plantations and secondary vegetation. The data from this study provide further evidence of the potential urban transmission of American cutaneous leishmaniasis in northern Argentina.”

    Female Breast Cancer Mortality Clusters within Racial Groups in the United States

    In GIS, Science, Spatial Analysis, Statistics on March 19, 2010 at 7:05 am

    Health and Place, 16 (2), p.209-218, Mar 2010

    Nancy Tian, J. Gaines Wilson, and F. Benjamin Zhan

    “Although breast cancer is the second leading cause of cancer deaths among women in the Unites States, to date there have been no nationwide studies systematically analyzing geographic variation and clustering. An assessment of spatial–temporal clusters of cancer mortality by age and race at the county level in the lower 48 United States indicated a primary cluster in the Northeast US for both younger (RR=1.349; all RR are p≤0.001) and older (RR=1.283) women in the all-race category. Similar cluster patterns in the North were detected for younger (RR=1.390) and older (RR=1.292) white women. The cluster for both younger (RR=1.337) and older (RR=1.251) black women was found in the Midwest. The clusters for all other racial groups combined were in the West for both younger (RR=1.682) and older (RR=1.542) groups. Regression model results suggest that lower socioeconomic status (SES) was more protective than higher status at every quartile step (Medium-high SES, OR=0.374; Medium-low, OR=0.137; Low, OR=0.061). This study may provide insight to aid in identifying geographic areas and subpopulations at increased risk for breast cancer.”

    SAM: A Comprehensive Application for Spatial Analysis in Macroecology

    In Environmental Science, Spatial Analysis, Statistics on March 18, 2010 at 9:48 am

    Ecography, Volume 33 Issue 1, Pages 46 – 50, Published Online: 4 Mar 2010

    Thiago F. Rangel, Jose Alexandre F. Diniz-Filho and Luis Mauricio Bini

    “SAM (Spatial Analysis in Macroecology) is a freeware application that offers a comprehensive array of spatial statistical methods, focused primarily on surface pattern spatial analysis. SAM is a compact, but powerful stand-alone software, with a user-friendly, menu-driven graphical interface. The methods available in SAM are the most commonly used in macroecology and geographical ecology, and range from simple tools for exploratory graphical analysis (e.g. mapping and graphing) and descriptive statistics of spatial patterns (e.g. autocorrelation metrics), to advanced spatial regression models (e.g. autoregression and eigenvector filtering). Download of the software, along with the user manual, can be downloaded online at the SAM website: <www.ecoevol.ufg.br> (permanent URL at <http://purl.oclc.org/sam/>).”

    A GIS-based Approach to Evaluate Biomass Potential from Energy Crops at Regional Scale

    In Climate Change, Environmental Science, GIS, Spatial Analysis on March 18, 2010 at 7:01 am

    Environmental Modelling and Software, 25 (6), p.702-711, Jun 2010

    Fiorese, G. / Guariso, G.

    “The aim of the paper is to propose a method to maximize energy production from arboreous and herbaceous dedicated crops given the characteristics of the local environment: geo-morphology, climate, natural heritage, current land use. The best energy crops available in the Italian panorama are identified and the problem of maximizing the bioenergy production over an entire regional area is formulated. Each cultivar is thus assigned to the suitable land accounting for sensitive parameters that characterize it and taking into account current land use. The assumption made here is that marginal land and set-asides can be converted to energy crops without altering current practices and cash crops’ production. The method is based on the integration of GIS data (spatially continuous) with data derived from the agricultural census (spatially discrete). We carry out the analysis for Emilia-Romagna, in Northern Italy. The sustainable growth of energy crops, with an optimized network of conversion facilities distributed in the territory, may significantly contribute to the local energy supply and to climate change mitigation.”

    GIS Assessment of Solar Energy Resource in Europe

    In Environmental Science, GIS, Spatial Analysis on March 17, 2010 at 9:20 am

    “A solar radiation database of Europe has been computed within the GRASS GIS software. The database provides monthly and yearly averages of global irradiation on horizontal and inclined surfaces, as well as climatic parameters needed for an assessment of the potential photovoltaic electricity generation. The database is available on-line by means of a set of dynamic web applications. In the first application, a user may browse solar radiation and other maps and query the selected climatic parameters. The second application provides daily profiles of irradiance for a chosen month and for a selected surface inclination and orientation. The third application provides estimates of solar electricity generation.”

    Spatio-temporal Analysis of Fire Events in India: Implications for Environmental Conservation

    In Environmental Science, Spatial Analysis, Statistics, Temporal Analysis on March 17, 2010 at 7:15 am

    Journal of Environmental Planning and Management, Volume 51, Issue 6 November 2008 , pages 817 – 832

    Krishna Prasad Vadrevu; K. V. S. Badarinath; Anuradha Eaturu

    “Information on fires in different geographic regions of India is relatively scarce. This study quantifies spatial and temporal patterns in fire occurrences covering different states and districts in India. Two important scientific questions are answered in this study: (1) how are the fire events distributed across different geographical regions? (2) are there any specific districts where fire events clustered across space and time? To address these questions, Along Track Scanning Radiometer (ATSR) derived satellite fire counts from 1997-2006 were used and the datasets were analysed using spatial scan statistic. Spatial scan statistic provides a test statistic for most likely ‘hotspot’ spatial clusters, based on the likelihood ratio test and Monte Carlo simulation. Results from geographical analysis based on state boundaries suggested Maharastra state had the highest number of fires followed by Madhya Pradesh, Chattisgarh, Orissa, etc., during the 10-year period. Among the several districts, the spatial scan statistic identified the most likely cluster of fire events in Dausa, Karauli, Sawai Madhopur, Bharatpur and Alwar in addition to several other secondary clusters, with high statistical significance. These results are based on a large sample of cases, and they provide convincing evidence of spatial clustering of fire events in the Indian region. Results relating to hotspot areas of fire risk can guide policy makers towards the best management strategies for avoiding damages to forests, human life and personal property in the ‘hotspot’ districts.”

    Small Area Estimation of Sparse Disease Counts using Shared Component Models

    In GIS, Geography, Modeling, Spatial Analysis on March 17, 2010 at 6:58 am

    Health & Place, In Press, Accepted Manuscript, Available online 25 February 2010

    Arul Earnest, John Beard, Geoff Morgan, Douglas Lincoln, Richard Summerhayes, Deborah Donoghue, Therese Dunn, David Muscatello, and Kerrie Mengersen

    “In the field of disease mapping, little has been done to address the issue of analysing sparse health datasets. We hypothesised that by modelling two outcomes simultaneously, one would be able to better estimate the outcome with a sparse count. We tested this hypothesis utilising Bayesian models, studying both birth defects and caesarean sections using data from two large, linked birth registries in New South Wales from 1990 to 2004. We compared four spatial models across seven birth defects: spina bifida, ventricular septal defect, OS-atrial septal defect, patent ductus arteriosus, cleft lip and or palate, trisomy 21 and hypospadias. For three of the birth defects, the shared component model with a zero-inflated Poisson (ZIP) extension performed better than other simpler models, having a lower Deviance Information Criteria (DIC). With spina bifida, the ratio of relative risk associated with the shared component was 2.82 (95% CI: 1.46-5.67). We found that shared component models are potentially beneficial, but only if there is a reasonably strong spatial correlation in effects for the study and referent outcomes.”

    A Country Level Spatial Assessment of Landslide Susceptibility in Romania

    In Environmental Science, GIS, Spatial Analysis on March 17, 2010 at 6:36 am

    Geomorphology, In Press, Accepted Manuscript, Available online 11 March 2010

    Dan Bălteanu, Viorel Chendeş, Mihaela Sima, Petru Enciu

    “The paper proposes a brief spatial analysis of landslides in Romania, completed by a landslide susceptibility model. Landslides constitute a very common geomorphic hazard in this country, mainly in the hilly regions which occupy around 30% of the Romanian territory. The landslide susceptibility assessment at national level was accomplished using a Landslide Susceptibility Index (LSI) computed in GIS, which considers and weights the main factors that control landslide activity: lithology, slope gradient, maximum rainfall in 24 hrs, land use, seismicity and local relief. Each factor was classified into 7-18 classes which were rated from 1 to 10 by means of expert judgement. A formula was devised to compute Landslide Susceptibility Index over each 100 m × 100 m pixel and the resulting values were ranked into 5 landslide susceptibility classes. This synthetic method of landslide susceptibility assessment, applied to the whole country of Romania, is an useful tool to evaluate the distribution of landslide-prone areas, as well as to validate and to enhance some results obtained in previous studies based on field research and map interpretation. The most landslide prone areas correspond to the Subcarpathians (an outer fringe of hilly terrain accompanying the Carpathians), as well as to the Moldavian Plateau in the east. The semi-quantitative approach has been validated with satisfactorily results in a particular sector using independent cartographic landslide inventories.”

    Classifying Historical Remotely Sensed Imagery Using a Tempo-spatial Feature Evolution (T-SFE) Model

    In Imagery, Modeling, Spatial Analysis, Temporal Analysis on March 16, 2010 at 8:45 am

    ISPRS Journal of Photogrammetry and Remote Sensing, Volume 65, Issue 2, March 2010, Pages 182-190

    Yichun Xie, Zongyao Sha, Yongfei Bai

    “Large and growing archives of orbital imagery of the earth’s surface collected over the past 40 years provide an important resource for documenting past and current land cover and environmental changes. However uses of these data are limited by the lack of coincident ground information with which either to establish discrete land cover classes or to assess the accuracy of their identification. Herein is proposed an easy-to-use model, the Tempo-Spatial Feature Evolution (T-SFE) model, designed to improve land cover classification using historical remotely sensed data and ground cover maps obtained at later times. This model intersects (1) a map of spectral classes (S-classes) of an initial time derived from the standard unsupervised ISODATA classifier with (2) a reference map of ground cover types (G-types) of a subsequent time to generate (3) a target map of overlaid patches of S-classes and G-types. This model employs the rules of Count Majority Evaluation, and Subtotal Area Evaluation that are formulated on the basis of spatial feature evolution over time to quantify spatial evolutions between the S-classes and G-types on the target map. This model then applies these quantities to assign G-types to S-classes to classify the historical images. The model is illustrated with the classification of grassland vegetation types for a basin in Inner Mongolia using 1985 Landsat TM data and 2004 vegetation map. The classification accuracy was assessed through two tests: a small set of ground sampling data in 1985, and an extracted vegetation map from the national vegetation cover data (NVCD) over the study area in 1988. Our results show that a 1985 image classification was achieved using this method with an overall accuracy of 80.6%. However, the classification accuracy depends on a proper calibration of several parameters used in the model.”

    Review of Methods for Space-time Disease Surveillance

    In Science, Spatial Analysis, Temporal Analysis on March 15, 2010 at 8:33 am

    Spatial and Spatio-temporal Epidemiology, In Press, Accepted Manuscript, Available Online 20 February 2010

    Colin Robertsona, Trisalyn A. Nelsona, Ying C. MacNabb and Andrew B. Lawsonc

    “A review of some methods for analysis of space-time disease surveillance data is presented. Increasingly, surveillance systems are capturing spatial and temporal data on disease and health outcomes in a variety of public health contexts. A vast and growing suite of methods exists for detection of outbreaks and trends in surveillance data and the selection of appropriate methods in a given surveillance context is not always clear. While most reviews of methods focus on algorithm performance, in practice, a variety of factors determine what methods are appropriate for surveillance. In this review, we focus on the role of contextual factors such as scale, scope, surveillance objective, disease characteristics, and technical issues in relation to commonly used approaches to surveillance. Methods are classified as testing-based or model-based approaches. Reviewing methods in the context of factors other than algorithm performance highlights important aspects of implementing and selecting appropriate disease surveillance methods.”

    Assessing the Context of Health Care Utilization in Ecuador: A Spatial and Multilevel Analysis

    In Geography, Spatial Analysis, Statistics on March 15, 2010 at 7:39 am

    BMC Health Services Research, 2010, 10:64

    Daniel F Lopez-Cevallos and Chunhuei Chi

    “Background: There are few studies that have analyzed the context of health care utilization, particularly in Latin America. This study examines the context of utilization of health services in Ecuador; focusing on the relationship between provision of services and use of both preventive and curative services.

    “Methods: This study is cross-sectional and analyzes data from the 2004 National Demographic and Maternal & Child Health dataset. Provider variables come from the Ecuadorian System of Social Indicators (SIISE). Global Moran’s I statistic is used to assess spatial autocorrelation of the provider variables. Multilevel modeling is used for the simultaneous analysis of provision of services at the province level with use of services at the individual level.

    “Results: Spatial analysis indicates no significant differences in the density of health care providers among Ecuadorian provinces. After adjusting for various predisposing, enabling, need factors and interaction terms, density of public practice health personnel was positively associated with use of preventive care, particularly among rural households. On the other hand, density of private practice physicians was positively associated with use of curative care, particularly among urban households.

    “Conclusions: There are significant public/private, urban/rural gaps in provision of services in Ecuador; which in turn affect people’s use of services. It is necessary to strengthen the public health care delivery system (which includes addressing distribution of health workers) and national health information systems. These efforts could improve access to health care, and inform the civil society and policymakers on the advances of health care reform.”

    Call for Papers: Workshop On Linked Spatiotemporal Data 2010

    In Conferences, GIS, GIScience, Spatial Analysis, Temporal Analysis on March 15, 2010 at 6:56 am

    Workshop On Linked Spatiotemporal Data 2010 (http://stko.psu.edu/lstd2010/)

    In conjunction with the 6th International Conference on Geographic Information Science (GIScience 2010)

    Zurich, 14-17th September, 2010; the workshop will be held on the 14th September 2010.

    Workshop Description & Scope

    Whilst the Web has changed with the advent of the Social Web from mostly authoritative towards increasing amounts of user generated content, it is essentially still about linked documents. These documents provide structure and context for the described data and easy their interpretation. In contrast, the upcoming Data Web is about linking data, not documents. Such data sets are not bound to a specific document but can be easily combined and used outside of the original context. With a growth rate of millions of new facts encoded as RDF-triples per month, the Linked Data cloud allows users to answer complex queries spanning multiple sources. Due to the uncoupling of data from its original creation context, semantic interoperability, identity resolution, and ontologies are central methodologies to ensure consistency and meaningful results. Space and time are fundamental ordering relations to structure such data and provide an implicit context for their interpretation. Prominent geo-related Linked Data hubs include Geonames.org as well as the Linked Geo Data project which provides a RDF serialization of Open Street Map. Furthermore, myriad other Linked Data sources contain location-based references. This workshop aims at introducing the GIScience audience to the Linked Data Web and discuss the relation between the upcoming Linked Data infrastructures and existing OGC services-based Spatial Data Infrastructures. The workshop results will directly contribute to the ongoing work of the NeoGeo Semantic Web Vocabularies Group, an online group focused on the construction of a set of lightweight geospatial ontologies for Linked Data. Overall, the workshop should help to better define the data, knowledge representations, reasoning methodologies, and additional tools needed to link locations seamlessly into the Web of Linked Data. Subsequently, with the advent of “Linked Locations” in Linked Data, the gap between the Semantic Web and the Geo Web will begin to narrow.

    Topics of interest for the Linked Spatiotemporal Data workshop include (but are not limited to):

    Application of Linked Spatiotemporal Data

    • Linked Data and the Sensor Web Enablement
    • Linked Data and mobile applications
    • Linked Data gazetteers and points of interest
    • Linked Data in the domain of cultural heritage research

    Retrieving and Browsing of Linked Spatiotemporal Data

    • Mining Linked Spatiotemporal Data from existing sources
    • Spatiotemporal indexing of Linked Data
    • Harvesting Linked Data from heterogeneous sources
    • Spatial extensions to query languages such as SPARQL (e.g., GeoSPARQL)
    • Visualizing and browsing through the Linked Spatiotemporal Data cloud

    Integration and Interoperation of Linked Spatiotemporal Data

    • Ontologies and vocabularies to support interoperability
    • Identity assumptions and resolution for data fusion and integration
    • The role of space and time to structure Linked Data
    • Versioning of spatio-temporal data
    • Semantic annotation and microformats
    • Adding contextual information to Linked Data

    Linked Data and Volunteered Geographic Information (VGI)

    • Spatiotemporal Aspects of Data Quality, Trust, and Provenance in Linked Data
    • Tag and Vocabulary recommendations for annotating VGI
    • Maintenance of links

    More information

    Spatial-temporal Analysis of Gummosis in Three Cashew Clones at Northeastern Brazil

    In Spatial Analysis, Temporal Analysis on March 15, 2010 at 6:52 am

    Journal of Phytopathology, Published Online: Mar 11 2010

    Alex Q. Cysne, José E. Cardoso, Aline de Holanda N. Maia, and Fabio C. Farias

    “The cashew gummosis caused by the fungus Lasiodiplodia theobromae is one of the most important disease of cashew in the northeast of Brazil. The lack of studies about method of early detection, pathogen dissemination, host predisposition, mechanisms of attack and defence and efficient control measures assures this disease as a limiting factor as to growing of cashew under semi-arid conditions. Therefore, the characterization of spatial patterns of gummosis development under commercial orchards may provide important insights into the mechanisms involving in dissemination and disease progress of this disease, as well as in the understanding of dynamic of host, pathogen and environmental interactions for this pathossystem. This work aimed to characterize gummosis temporal and special dynamics in three commercial orchards of cashew clones of cashew with different levels of susceptibility by studying the special arrangement of diseased plants. Disease incidence and severity, quantified determined by a descriptive scale in clones BRS 226 (resistant), Embrapa 51 (slightly resistant) and Faga 11 (susceptible) in a commercial orchard located in Pio IX district (Piaui state, Brazil), were monitored and mapped. Data were collected within three blocks of 90 plants for each clone. Indices of dispersion were estimated to study the spatial dynamic. The dynamics and structure of gummosis foci were also analysed. As expected, data showed different degrees of gummosis incidence and severity for the three clones. Even under different levels of disease, a random dispersion pattern model of dispersion could be observed at the beginning of epidemic for all clones. However, as disease develops, a clustered model is likely to fit. The increase in disease incidence resulted from the increasing in both focus number and size.”

    Measuring Potential Spatial Access to Primary Health Care Physicians Using a Modified Gravity Model

    In Modeling, Spatial Analysis on March 12, 2010 at 7:34 am

    Canadian Geographer / Le Géographe canadien, Volume 54 Issue 1, Pages 29 – 45, March 2010

    NADINE SCHUURMAN, MYRIAM BÉRUBÉ, and VALORIE A. CROOKS

    “Ensuring equity of access to primary health care (PHC) across Canada is a continuing challenge, especially in rural and remote regions. Despite considerable attention recently by the World Health Organization, Health Canada and other health policy bodies, there has been no nation-wide study of potential (versus realized) spatial access to PHC. This knowledge gap is partly attributable to the difficulty of conducting the analysis required to accurately measure and represent spatial access to PHC. The traditional epidemiological method uses a simple ratio of PHC physicians to the denominator population to measure geographical access. We argue, however, that this measure fails to capture relative access. For instance, a person who lives 90 minutes from the nearest PHC physician is unlikely to be as well cared for as the individual who lives more proximate and potentially has a range of choice with respect to PHC providers. In this article, we discuss spatial analytical techniques to measure potential spatial access. We consider the relative merits of kernel density estimation and a gravity model. Ultimately, a modified version of the gravity model is developed for this article and used to calculate potential spatial access to PHC physicians in the Canadian province of Nova Scotia. This model incorporates a distance decay function that better represents relative spatial access to PHC. The results of the modified gravity model demonstrate greater nuance with respect to potential access scores. While variability in access to PHC physicians across the test province of Nova Scotia is evident, the gravity model better accounts for real access by assuming that people can travel across artificial census boundaries. We argue that this is an important innovation in measuring potential spatial access to PHC physicians in Canada. It contributes more broadly to assessing the success of policy mandates to enhance the equitability of PHC provisioning in Canadian provinces.”

    Biodiverse: A Tool for the Spatial Analysis of Diversity

    In Environmental Science, Spatial Analysis, Statistics, Visualization on March 12, 2010 at 7:27 am

    “Biodiverse is a tool for the spatial analysis of diversity using indices based on taxonomic, phylogenetic and matrix-based (e.g. genetic distance) relationships, as well as related environmental and temporal variations.

    “Biodiverse supports four processes:

    1. linked visualisation of data distributions in geographic, taxonomic, phylogenetic and matrix spaces;
    2. spatial moving window analyses including richness, endemism, phylogenetic diversity and beta diversity;
    3. spatially constrained agglomerative cluster analyses; and
    4. randomisations for hypothesis testing.”

    Epidemiologic Mapping of Florida Childhood Cancer Clusters

    In GIS, Geography, Science, Spatial Analysis, Statistics, Temporal Analysis on March 9, 2010 at 7:58 am

    Pediatric Blood & Cancer, Volume 54 Issue 4, Pages 511 – 518, 2010

    Raid Amin, PhD, Alexander Bohnert, Laurens Holmes, PhD, DrPH, Ayyappan Rajasekaran, PhD, and Chatchawin Assanasen, MD

    “Background: Childhood cancer remains the leading cause of disease-related mortality for children. Whereas, improvement in care has dramatically increased survival, the risk factors remain to be fully understood. The increasing incidence of childhood cancer in Florida may be associated with possible cancer clusters. We aimed, in this study, to identify and confirm possible childhood cancer clusters and their subtypes in the state of Florida.

    “Methods: We conducted purely spatial and space-time analyzes to assess any evidence of childhood malignancy clusters in the state of Florida using SaTScanTM. Data from the Florida Association of Pediatric Tumor Programs (FAPTP) for the period 2000-2007 were used in this analysis.

    “Results: In the purely spatial analysis, the relative risks (RR) of overall childhood cancer persisted after controlling for confounding factors in south Florida (SF) (RR = 1.36, P = 0.001) and northeastern Florida (NEF) (RR = 1.30, P = 0.01). Likewise, in the space-time analysis, there was a statistically significant increase in cancer rates in SF (RR = 1.52, P = 0.001) between 2006 and 2007. The purely spatial analysis of the cancer subtypes indicated a statistically significant increase in the rate of leukemia and brain/CNS cancers in both SF and NEF, P < 0.05. The space-time analysis indicated a statistically significant sizable increase in brain/CNS tumors (RR = 2.25, P = 0.02) for 2006-2007.

    “Conclusions: There is evidence of spatial and space-time childhood cancer clustering in SF and NEF. This evidence is suggestive of the presence of possible predisposing factors in these cluster regions. Therefore, further study is needed to investigate these potential risk factors.”

    A Spatial Analysis of Residential Land Prices in Belgium: Accessibility, Linguistic Border and Environmental Amenities

    In Social Science, Spatial Analysis on March 9, 2010 at 7:42 am

    …from the Social Science Research Network…

    GATE Working Paper 09-29, December 2009

    Florence Goffette-Nagot, Isabelle Reginster, and Isabelle Thomas

    “This paper explores the spatial variation of land prices in Belgium. The originality of the methodology is threefold : (1) to work at the spatial extent of an entire country, (2) to compute several accessibility measures to all jobs and several representations of the environmental amenities and, more importantly, (3) to test the hypothesis that jobs influence land prices only in the same linguistic region. Spatial autocorrelation is accounted for by estimating spatial models. The results show that the linguistic border acts as a strong barrier in the spatial pattern of land prices and that environmental variables have no significant effect at this scale of spatial analysis.”

    Spatial Analysis of Notified Cryptosporidiosis Infections in Brisbane, Australia

    In Science, Spatial Analysis on March 5, 2010 at 10:50 am

    Annals of Epidemiology, Volume 19, Issue 12, Pages 900-907 (December 2009)

    Wenbiao Hu, Kerrie Mengersen, and Shilu Tong

    “This study explored the spatial distribution of notified cryptosporidiosis cases and identified major socioeconomic factors associated with the transmission of cryptosporidiosis in Brisbane, Australia.

    “We obtained the computerized data sets on the notified cryptosporidiosis cases and their key socioeconomic factors by statistical local area (SLA) in Brisbane for the period of 1996 to 2004 from the Queensland Department of Health and Australian Bureau of Statistics, respectively. We used spatial empirical Bayes rates smoothing to estimate the spatial distribution of cryptosporidiosis cases. A spatial classification and regression tree (CART) model was developed to explore the relationship between socioeconomic factors and the incidence rates of cryptosporidiosis.

    “Spatial empirical Bayes analysis reveals that the cryptosporidiosis infections were primarily concentrated in the northwest and southeast of Brisbane. A spatial CART model shows that the relative risk for cryptosporidiosis transmission was 2.4 when the value of the social economic index for areas (SEIFA) was over 1028 and the proportion of residents with low educational attainment in an SLA exceeded 8.8%.

    “There was remarkable variation in spatial distribution of cryptosporidiosis infections in Brisbane. Spatial pattern of cryptosporidiosis seems to be associated with SEIFA and the proportion of residents with low education attainment.”

    Spatial-Temporal Combination of Variables for Monitoring Changes in Metropolitan Areas

    In Geography, Spatial Analysis, Temporal Analysis on March 4, 2010 at 6:54 am

    Applied Spatial Analysis and Policy, Volume 3, Number 1 / March 2010

    Gustavo Garcia Manzato and Antônio Nélson Rodrigues da Silva

    “The objective of this exploratory study is to present a new method for monitoring the dynamic changes of functional urban regions (FURs) or metropolitan areas (MAs) boundaries throughout time. The suggested approach is based on two elements: the population density and an index of transportation infrastructure supply, which are analyzed in two ways. First, we carry out exploratory analyses of those variables separately. Next, the variables are combined using spatial analysis and spatial modeling techniques. A case study in the state of São Paulo, Brazil, shows that the proposed methodology can be particularly useful for urban and regional planning in developing countries, because it stresses the relationship between land-use and transportation supply. So, given the evidence that urban and regional development is strongly influenced by the level of transportation infrastructure supply, the approach can be further improved if considering other elements of transportation infrastructure, such as airports, railways, ports, as well as additional factors which may have effects on land use patterns such as distribution of services and jobs where data is available.”

    Spatial Modelling of Car Ownership Data: A Case Study from the United Kingdom

    In Modeling, Spatial Analysis on March 3, 2010 at 7:05 am

    Applied Spatial Analysis and Policy, Volume 3, Number 1 / March 2010

    Stephen Clark and Andrew O. Finley

    “In this paper a model is formulated to estimate the strength of the relationship between household car ownership and income using cross-sectional data. Whilst reports of such studies are not uncommon in the transport literature, this study is different in that it takes explicit account of the spatial distribution of the data. By incorporating this spatial element in the model formulation, the residual errors in the model are uncorrelated and hence allows for the estimation of parameters that are, in a statistical sense, the best available. These spatial models are fitted to a large data set provided by the United Kingdom Office for National Statistics, covering the area of England and Wales. The recommended model form is a Hierarchical Bayesian spatial regression model with the parameters in the model estimated using the technique of Markov Chain Monte Carlo (MCMC). A common feature of all the spatial models is that the estimate of the elasticity of car ownership with respect to income is seen to be larger than that from a non-spatial model.”

    Video: Marine Spatial Planning Tool – Flower Garden Banks

    In ESRI, Environmental Science, GIS, Spatial Analysis, Video on March 3, 2010 at 7:04 am

    “The Marine Spatial Planning Tool of the Flower Garden Banks is an on-line GIS application that allows the public to view data collected by the national marine sanctuary with data from other agencies.”

    A Spatial Analysis of the Demographic and Socio-economic Variables Associated with Cardiovascular Disease in Calgary (Canada)

    In Geography, Science, Spatial Analysis on March 2, 2010 at 8:03 am

    Applied Spatial Analysis and Policy, Volume 3, Number 1 / March 2010

    Stefania Bertazzon, Scott Olson, and Merril Knudtson

    “The association between cardiovascular disease and a pool of demographic and socioeconomic variables is analyzed, for a large Canadian city, by means of multivariate spatial regression analysis. The analysis suggests that the spatial dependence observed in the disease prevalence is driven by the spatial distribution of senior citizens. A spatially autoregressive specification on a pool of solely socio-economic variables produces a model whose main predictors are family status, income, and educational attainments. This model can provide an effective analytical tool to support policy decisions, because it identifies a set of socioeconomic, not simply demographic predictors of disease. These socio-economic variables can be targeted by social policies much more effectively than demographic variables. A further analytical step recombines the significant explanatory variables based on their spatial patterns. Thus the model is used to identify areas of social and economic concern, and to enable the initiation of specifically localized preventative health measures. Owing to its generality, the method can be applied to other conditions and to analyze multivariate relationships involving not only socioeconomic variables, but also environmental factors.”

    Impact of Sports Arenas on Land Values: Evidence from Berlin

    In Geography, Social Science, Spatial Analysis on March 2, 2010 at 7:47 am

    The Annals of Regional Science, Volume 44, Number 2 / April, 2010

    Gabriel M. Ahlfeldt and Wolfgang Maennig

    “This paper develops a hedonic price model explaining standard land values in Berlin. The model assesses the impact of three multifunctional sports arenas situated in Berlin-Prenzlauer Berg which were designed to improve the attractiveness of their formerly deprived neighbourhoods. Empirical results confirm expectations about the impact of various attributes on land values. Sports arenas have significant positive impacts within a radius of about 3,000 m. The patterns of impact vary, indicating that the effective impact depends on how planning authorities address potential countervailing negative externalities.”

    Planning for Ecosystem Service Markets

    In Environmental Science, Spatial Analysis on March 2, 2010 at 7:39 am

    Journal of the American Planning Association, Volume 76, Issue 1 2010 , pages 59 – 72

    Todd K. BenDor and Martin W. Doyle

    “Problem: Market mechanisms are emerging as means of offsetting the environmental effects of growth. Unfortunately, formal regulation of ecosystem markets is often separated from broader planning for urban development, resulting in offsets that are unsustainable in the face of future urban growth.

    “Purpose: We aimed to assess how 2008 federal regulations that actively promote aquatic resource markets and encourage watershed planning to restore wetlands and streams damaged during development will affect reputedly efficient existing wetland and stream ecosystem markets in North Carolina. We explore how coordination between regulators and planners can improve long-term viability of market-created resource offsets and improve the ability of markets to respond to rapid urban growth.

    “Methods: We analyzed new state and federal regulations and watershed planning efforts and convened a stakeholder forum including representatives of state and federal agencies, land developers, environmental groups, aquatic restoration companies, and academia.

    “Results and conclusions: Problems with aquatic ecosystem markets in North Carolina stem from poor communication among local and regional planners, federal regulators, and state agencies. Institutional barriers and poor coordination cause federal regulatory decisions made without knowledge of land use plans or urban development patterns, faulty projections of market demand for aquatic offsets, and local land use plans that do not provide long-term protection for the offsets. Although regulators consider current surrounding land uses, they do not consider future land uses. We conclude that local land use projections should be required components of ecosystem restoration site plans and that state environmental management agencies’ watershed plans should reflect urban development patterns.

    “Takeaway for practice: Local planners should have input into the design of restoration sites providing environmental offsets as well as into state and regional ecosystem service market implementation plans. Federal, state, regional, and local agencies should facilitate and require information sharing, making planning and regulating ecosystem service markets part of the development process.

    “Research support: This research was supported by the University of North Carolina’s Institute for the Environment.”

    GIS Analysis of Landslides in India

    In Environmental Science, GIS, Spatial Analysis on March 1, 2010 at 8:34 am

    Analisis GIS Terhadap Gerakan Tanah di Girimulyo, Kulonprogo, D.I. Yogyakarta, dan Kajian Faktor – Faktor Pengontrolnya

    Abstract submitted to the 2010 International Geosciences Conference and Exposition

    Yogi Saktyan Respati, Asnanto Multa Putranto, Azim Suwardi, Irien Akinina Fatkhiandari, and Salahuddin Husein

    “There were several landslides had occurred at Girimulyo District, Kulonprogo Regency, Yogyakarta Special Province. These suggest that this area exhibits high potential of mass movement. This research is intended to map and analyze the mass movement potentail by using two methods, i.e. qualitative and quantitative, respectively. Direct observation is on site study for internal factors (e.g. lithologies and geologic structure) and external factors (e.g slope, vegetation, and landuses). Quantitative method utilizes Geographic Information System (GIS) spatial analysis on weighted parameters, i.e. slope, lithologies, geologic structures, and landuses. The research area is mainly composed of weathered lithologies of andesit breccia and breccia tuff covering steep slopes, whilst the rainfall rate reaches up to 2205 mm/y. Both factors are presumed to be the main trigger of mass movement. Result of this research is landslide susceptibility zonation which consist ot four levels which can be used as a basic information for hazard mitigation and regional planning. There were two types of mass movement exist at this area, fall movement were predominant in andesitic intrusion, whereas flow movement mainly took place in andesitic breccias, coralline limestones, and tuffaceous siltstones. This study suggests that more attention and awareness should be paid for areas with high and very high susceptibility levels such as Tanggulangin, Talunombo, and Giripurwo, particularly during high rainy sesason.”

    Geostatistics and Multivariate Analysis as a Tool to Characterize Volcaniclastic Deposits: Application to Nevado de Toluca Volcano, Mexico

    In Science, Spatial Analysis, Statistics on March 1, 2010 at 8:25 am

    Journal of Volcanology and Geothermal Research, Article in Press, Available online 25 January 2010

    F. Bellotti, L. Capra, D. Sarocchi, and M. D’Antonio

    “Grain size analysis of volcaniclastic deposits is mainly used to study flow transport and depositional processes, in most cases by comparing some statistical parameters and how they change with distance from the source.

    “In this work the geospatial and multivariate analyses are presented as a strong adaptable geostatistical tool applied to volcaniclastic deposits in order to provide an effective and relatively simple methodology for texture description, deposit discrimination and interpretation of depositional processes.

    “We choose the case of Nevado de Toluca volcano (Mexico) due to existing knowledge of its geological evolution, stratigraphic succession and spatial distribution of volcaniclastic units. Grain size analyses and frequency distribution curves have been carried out to characterize and compare the 28-ka block-and-ash flow deposit associated to a dome destruction episode, and the El Morral debris avalanche deposit originated from the collapse of the south-eastern sector of the volcano. The geostatistical interpolation of sedimentological data allows to realize bidimensional maps draped over the volcano topography, showing the granulometric distribution, sorting and fine material concentration into the whole deposit with respect to topographic changes. In this way, it is possible to analyze a continuous surface of the grain size distribution of volcaniclastic deposits and better understand flow transport processes.

    “The application of multivariate statistic analysis (discriminant function) indicates that this methodology could be useful in discriminating deposits with different origin or different depositional lithofacies within the same deposit.

    “The proposed methodology could be an interesting approach to sustain more classical analysis of volcaniclastic deposits, especially where a clear field classification appears problematic because of a homogeneous texture of the deposits or their scarce and discontinuous outcrops. Our study is an example of the strong versatility of geospatial analysis to provide an effective and relatively clear methodology for the characterization of volcaniclastic deposits.”

    Applied Spatial Data Analysis with R

    In Books, GIS, Geography, Spatial Analysis, Statistics on March 1, 2010 at 8:05 am

    “Applied Spatial Data Analysis with R is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book’s own website.

    “This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information systems, the environmental sciences, ecology, public health and disease control, economics, public administration and political science.

    “The book has a website where coloured figures, complete code examples, data sets, and other support material may be found: http://www.asdar-book.org.”

    Spatial and Spatio-Temporal Analysis of Salmonella Infection in Dairy Herds in England and Wales

    In Spatial Analysis, Statistics, Temporal Analysis on March 1, 2010 at 8:00 am

    Epidemiology and Infection, Vol. 137, No. 6 (Jun., 2009), pp. 847-857

    S. E. Fenton, H. E. Clough, P. J. Diggle, S. J. Evans, H. C. Davison, W. D. Vink and N. P. French

    “Using data from a cohort study conducted by the Veterinary Laboratories Agency (VLA), evidence of spatial clustering at distances up to 30 km was found for S. Agama and S. Dublin (P values of 0·001) and borderline evidence was found for spatial clustering of S. Typhimurium (P = 0·077). The evolution of infection status of study farms over time was modelled using a Markov Chain model with transition probabilities describing changes in status at each of four visits, allowing for the effect of sampling visit. The degree of geographical clustering of infection, having allowed for temporal effects, was assessed by comparing the residual deviance from a model including a measure of recent neighbourhood infection levels with one excluding this variable. The number of cases arising within a defined distance and time period of an index case was higher than expected. This provides evidence for spatial and spatio-temporal clustering, which suggests either a contagious process (e.g. through direct or indirect farm-to-farm transmission) or geographically localized environmental and/or farm factors which increase the risk of infection. The results emphasize the different epidemiology of the three Salmonella serovars investigated.”

    Photo: Jack Dangermond Opens the Space-Time Modeling and Analysis Workshop at Redlands GIS Week

    In Conferences, ESRI, GIS, Science, Spatial Analysis, Temporal Analysis on March 1, 2010 at 7:34 am

    Jack Dangermond opens the “Space-Time Modeling and Analysis Workshop” at the inaugural Redlands GIS Week, Monday, 22 February 2010.

    Spatio-temporal Complexity Analysis of the Sea Surface Temperature in the Philippines

    In Environmental Science, Spatial Analysis, Temporal Analysis on February 26, 2010 at 7:21 am

    Ocean Sci. Discuss., 6, 2831-2859, 2009

    Z. T. Botin, L. T. David, R. C. H. del Rosario, and L. Parrott

    “A spatio-temporal complexity (STC) measure which has been previously used to analyze data from terrestrial ecosystems is employed to analyse 21 years of remotely sensed sea-surface temperature (SST) data from the Philippines. STC on the Philippine wide SST showed the monsoonal variability of the Philippine waters but did not show significant differences between El Niño, La Niña and normal years. The spatial domain was subsequently divided into six thermal regions computed via clustering of temperature means. The STC values of each thermal region showed variations corresponding to the monsoonal shifts – as well as – to ENSO events. STC characterized environmental heterogeneity over space and time has the potential to define limits of bio-regions. The same approach can be utilized for many long-term remotely sensed data.”

    Diagnostic Techniques Applied in Geostatistics for Agricultural Data Analysis

    In Spatial Analysis, Statistics on February 24, 2010 at 2:41 pm

    Rev. Bras. Ciênc. Solo vol.33 no.6 Viçosa Nov./Dec. 2009

    Joelmir André Borssoi; Miguel Angel Uribe-Opazo, and Manuel Galea Rojas

    “The structural modeling of spatial dependence, using a geostatistical approach, is an indispensable tool to determine parameters that define this structure, applied on interpolation of values at unsampled points by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations in sampled data. The purpose of this study was to use diagnostic techniques in Gaussian spatial linear models in geostatistics to evaluate the sensitivity of maximum likelihood and restrict maximum likelihood estimators to small perturbations in these data. For this purpose, studies with simulated and experimental data were conducted. Results with simulated data showed that the diagnostic techniques were efficient to identify the perturbation in data. The results with real data indicated that atypical values among the sampled data may have a strong influence on thematic maps, thus changing the spatial dependence structure. The application of diagnostic techniques should be part of any geostatistical analysis, to ensure a better quality of the information from thematic maps.”

    Environmental Modeling: Using Space Syntax in Spatial Cognition Research

    In Conferences, Environmental Science, GIS, Modeling, Spatial Analysis on February 24, 2010 at 7:06 am

    Workshop & Tutorial at Spatial Cognition 2010
    15 August 2010, Mt. Hood, Oregon

    “Spatial cognition researchers have exacting methods for studying how people navigate, learn, and remember buildings, cities, and other large environments. Architects and planners have similarly careful computational methods for modeling the physical form of these environments. With this combination tutorial and workshop, we hope to further the pairing of behavioral methods and environmental models in spatial cognition research. The morning tutorial session will include a hands-on lesson in using environmental modeling techniques known as space syntax. No prior experience is necessary for the tutorial.

    “For the afternoon workshop session, researchers and practitioners are invited to submit papers (short or long format) and posters (with an abstract) for presentation. Those who wish to attend without presenting are invited to submit a position paper. Topics to be considered include:

    • Using environmental models (axial maps, segment maps, isovists, visibility graph analysis, agents, etc.) to address theoretical questions concerning spatial knowledge, spatial learning, locomotion, wayfinding, and other topics in spatial cognition.
    • Methodological issues of pairing environmental models and behavioral research methods.
    • Constructing environmental models that capture psychologically relevant features.
    • Relating environmental properties, such as visibility, accessibility, and intelligibility, to cognitive processes and behavior.”

    Spatial Analysis of Learning and Developmental Disorders in Upper Cape Cod, Massachusetts Using Generalized Additive Models

    In Spatial Analysis on February 16, 2010 at 9:08 am

    International Journal of Health Geographics,  9:7 12 February 2010

    Kate Hoffman, Thomas F Webster, Janice M Weinberg, Ann Aschengrau, Patricia A Janulewicz, Roberta F White, and Veronica M Vieira

    “The spatial variability of three indicators of learning and developmental disability (LDD) was assessed for Cape Cod, Massachusetts. Maternal reports of receiving special education services, attention deficit hyperactivity disorder, and educational attainment were available for a birth cohort from 1969-1983. Using generalized additive models and residential history, maps of the odds of LDD were produced that also controlled for known risk factors. While results were not statistically significant, they suggest that children living in certain parts of Cape Cod were more likely to have a LDD. The spatial variation may be due to variation in the physical and social environment.”

    Advances in Spatial Analysis & e-Social Science, University College London, 13 April 2010

    In Conferences, GIS, GIScience, Social Science, Spatial Analysis on February 16, 2010 at 8:35 am

    A one-day conference sponsored by the Economic and Social Research Council (ESRC)

    Tuesday 13 April 2010

    University College London (UCL) Centre for Advanced Spatial Analysis (CASA).

    Several papers will be presented, and the event wraps up with a panel discussion with Mike Goodchild, Keith Clarke
    David Maguire, and Carl Steinitz.

    CyberGIS: Empowering the Synthesis of Computational and Spatial Thinking

    In GIS, Science, Spatial Analysis on February 12, 2010 at 8:06 am

    The National Science Foundation TeraGrid Workshop on Cyber-GIS, Feb. 2-3, 2010, Washington DC

    Shaowen Wang, University of Illinois at Urbana-Champaign

    “Spatial thinking and associated geographic approaches, supported by geographic information systems (GIS), play essential roles in solving scientific problems and improving decision-making practices of significant societal impact. Fulfilling such roles is increasingly dependent on the capabilities of synthesizing spatial and computational thinking (Wing 2006) enabled by cyberinfrastructure. Cyberinfrastructure promises to revolutionize how science and engineering are conducted in the 21st century as computation has become the third pillar of science and engineering (along with theory and experiment) (NSF 2003). CyberGIS represent a new GIS modality comprising a seamless blending of cyberinfrastructure, GIS, and spatial analysis capabilities to empower computational and spatial thinking and, thus, promise to transform geospatial problem-solving and decision-making while advancing cyberinfrastructure.”

    Spatial and Temporal Analysis of Dry Spells in Croatia

    In Spatial Analysis, Statistics, Temporal Analysis on February 9, 2010 at 7:45 am

    Theoretical and Applied Climatology, January 2010

    K. Cindrić, Z. Pasarić, and M. Gajić-Čapka

    “Systematic statistical analysis of dry day sequences, which are defined according to 0.1, 1, 5 and 10 mm of precipitation-per-day thresholds, is performed on seasonal and yearly basis. The data analysed come from 25 Croatian meteorological stations and cover the period 1961–2000. Climatological features of the mean and maximum dry spell durations, as well as the frequency of long dry spells (>20 days) are discussed. The results affirm the three main climatological regions in Croatia, with the highlands exhibiting shorter dry spells than the mainland, and the coastal region exhibiting longer dry spells. The prevailing positive trend of both mean and maximal durations is detected during winter and spring seasons, while negative trend dominate in autumn for all thresholds. Positive field significant trends of mean dry spell duration with 5 and 10 mm thresholds are found during spring and the same is valid for annual maximum dry spell duration with a 10 mm threshold. It is found that the Discrete Autoregressive Moving Average (DARMA(1,1)) model can be used to estimate the probabilities of dry spells in Croatia that are up to 20–30 days long.”

    Mapping and Valuation of Ecosystem Services: Internship Opportunity with WWF / Natural Capital Project

    In ESRI, Environmental Science, GIS, Modeling, Spatial Analysis on February 9, 2010 at 7:38 am

    Intern(s) sought to work on mapping and valuation of ecosystem services using InVEST, an ArcGIS based modeling tool developed by the Natural Capital Project (www.naturalcapitalproject.org). Interns will work on one or more of the following:

    Using InVEST to map and value ecosystem services on WWF priority sites in Sumatra, the Colombian Amazon Piedmont, and the Greater Virungas Landscape in East Africa. Specifically, the intern may: gather and format data sets for use with InVEST; help WWF field programs with applying InVEST; and run the InVEST models for a range of ecosystem services under current land use patterns and future scenarios.

    • Providing feedback on the tool that will contribute to its further development, and helping to improve the documentation.
    • For interns with advanced ArcGIS skills (geoprocessing and Python scripting), there are opportunities to contribute to module development and improvement.
    • The intern may also be able to apply InVEST to another study area relevant to his or her ongoing or planned thesis project

    This is a great opportunity for self-motivated students to gain experience in spatial analysis and ecosystem services, and to possibly develop an independent research project for their thesis requirements. A minimum of two semesters ArcGIS coursework, or equivalent work experience required.

    Also helpful: knowledge of Spatial Analyst Tool and Python scripting, and prior experience with ecosystem services. Must be able to work efficiently and independently. Graduate students are preferred.

    Stipend:  Funding Possible
    Due date for CV and cover letter:  April 15, 2010
    Contact:  Nirmal Bhagabati (nirmal.bhagabati@wwfus.org)

    Call for Contributions: Spatial Cognition 2010, Mt. Hood, Oregon

    In Conferences, Geography, Science, Spatial Analysis on February 5, 2010 at 8:11 am

    Resort at the Mountain, Mt. Hood, Oregon
    15-19 August 2010

    “Spatial Cognition is concerned with the acquisition, organization, utilization, and revision of knowledge about spatial environments, be it real or abstract, human or machine. Spatial Cognition comprises research in very different scientific fields insofar as they are concerned with cognitive agents in spatial environments, such as robotics, artificial intelligence, linguistics, cognitive science, and philosophy. The aim of this research is to help humans to solve spatial tasks and to improve their spatial skills. Research issues in the field range from the investigation of human spatial cognition to mobile robot navigation, including aspects such as wayfinding, spatial planning, spatial learning, representations of space, map comprehension, and communication of spatial information.”

    • More information

    ISDA ’10: Intelligent Spatial Decision Analysis, 28-30 July 2010, Baltimore, Maryland

    In Conferences, Spatial Analysis on February 4, 2010 at 6:57 am

    Intelligent Spatial Decision Analysis (ISDA ’10)
     http://www.unibas.it/utenti/murgante/isda_10/ISDA.html

    in conjunction with

    International Symposium on Intelligent Decision Technologies (IDT’10)

    InnerHarbor, Baltimore, Maryland, USA 28-30 July 2010
    http://idt-10.kesinternational.org/

    Workshop Description
    Within the study on decision-making essence and its links with some strictly related concepts as evaluation and choice, it is possible to state that whereas decision can be mostly considered as a “political” process, evaluation mainly includes technical issues, while choice induces both sides problems.

    • Evaluation concerns an initial phase of a cognitive process and the decision terms of reference defining the boundaries within which the entire process takes place and the evaluation purposes are defined.
    • Decision is a deliberative act which temporarily closes a long and predominantly political process where the relationship among individuals of a community (and therefore among contrasting interests) needs to be regulated.
    • Choice ends an evaluation process which aims to select a decisional alternative among many ones, on the base of different and often conflictual criteria and points of view. So it reminds the necessity to screen and compare many alternatives and to make a selection.

    How does Information Technology application in spatial analysis modify the way of making decisions? Decision Theory based its fundamentals on limited sets of solution and evaluation criteria for a long time, but the way of describing spatial issues of governance, characters and constraints of physical space shows a further complexity that can not be described without the use of new methods, in order to increase decision quality. Even if the core nature of decision approach still remains the same, the number of complexities connected within the process increases rapidly. The interaction among evaluation methods, and the new described complexity of the physical urban space create a new era for spatial decision support involving several disciplines, and domains of knowledge.

    In relation to what above, a decision process necessarily involves the existence of several social actors, usually called “stakeholders”, contributing to the final choice definition and enforcement; it is therefore important to stress the distinction between decision making and decision aiding, sometimes wrongly adopted as synonyms. While a decision maker is the subject able, at the same time, to give the knowledge and to have the responsibility to make a choice, a decision aiding context involves the existence of two distinctive subjects at least: the analyst (or a group of them) aiding the decision via a deep scientific knowledge and the client (public or private) to whom such support is directed. Therefore, in the first case the following elements are usually considered: a well defined set of possible decisional alternatives, a well defined preference system already clear in the decision maker mind and a correctly formulated mathematical problem. A decision! aiding approach implies a set of not necessary stable potential actions compared on the base of n criteria able to reflect, under a natural uncertainty, the social actor preferences; in this case, then, a well formalized mathematical problem is quite impossible. In this context Intelligent Spatial Analysis Systems represent a fundamental support to decision making processes in conformity with a double reading perspective:

    1. they comprise a coherent set of methods and techniques which enable to deepen the investigation on the scientific aspect of decision making process, adopting several rigorous tools and models belonging to different fields as machine learning (i.e. cellular automata, multi-agent systems, Bayesian networks, artificial neural networks, etc.), geostatistics (i.e. kernel methods, kriging, support vector machines, etc.), remote sensing, spatial data warehousing and Spatial OLAP, and spatial data mining;
    2. they represent an innovative mean to enhance and guarantee participation (i.e. spatial multicriteria decision aiding, electronic meetings, focus groups, etc.), consensus building and communicability consensus building and communicability of decision making scenarios among stakeholders, in order to reach a transparent and accepted final choice.

    The aim of the workshop is to investigate such connections among disciplines, by theoretical debates and tales on case studies.

    The programme committee especially requests high quality submissions on the following Conference Themes :

    • Decision Support Theory;
    • Spatial Multicriteria Decision Analysis;
    • Spatial Rough Set;
    • Spatial extension of Fuzzy Set theory;
    • Ontologies for Spatial Analysis;
    • Environmental data mining;
    • Learning from geospatial data;
    • Machine Learning and Geostatistics;
    • Artificial neural networks;
    • Web-based decision analysis tools;
    • Wireless Sensor Networks for Spatial Apllications
    • Ant-based Algorithms;
    • Cellular automata;
    • Bayesian reasoning;
    • Statistical learning theory: support vector machines, kernel methods;
    • Remote sensing and remote sensed image processing;
    • Geographical approach to risk analysis;
    • Spatial Data warehousing foundations and architectures;
    • Spatial Data extraction, cleaning, and loading;
    • Spatial Multidimensional modeling and queries;
    • Spatial OLAP visualization;
    • New Spatial OLAP applications;
    • Spatial OLAP as support for intelligent spatial analysis (data mining, multi-criteria, etc…);
    • Spatial data mining: algorithms and visualization;
    • New spatial data mining applications;
    • Coupling spatial data mining and Spatial OLAP;
    • Geovisual analytics, geovisualisation, visual exploratory data analysis;
    • Visualisation and modelling of track data.

    Authors Guideline
    Please adhere strictly to the formatting provided in the template to prepare your paper and refrain from modifying it.
    For formatting information, see the publisher’s web site
    ( http://www.springer.com/authors/book+authors?SGWID=0-154102-12-417900-0 ).

    Papers should not exceed 10 pages in Springer format. Papers longer than this will be subject to an additional charge. Shorter papers will be acceptable if they adequately convey the material to be described, and are not so short as to be trivial or lacking in depth.

    Submission
    Papers for review for the conference must be submitted electronically in PDF form using the PROSE online submission and review system access.

    You may submit a paper to “Intelligent Spatial Decision Analysis” Session selecting the session from a drop-down box when you submit the paper. Please ensure you select the correct session.

    If you wish to submit a paper to an Invited Session, and the session is not shown on the drop-down box, please wait until the session has been set up.

    Once the paper has been submitted you may check its progress by login in to the PROSE review system using the login details you have been supplied with ( http://idt-10.kesinternational.org/prose.php).

    Proceedings
    Accepted papers will be published by prestigious publishing house, Springer Verlag, as book chapters in a volume of their Engineering Series and indexed in ISI conference publications, EI, INSPEC, etc.

    Outstanding papers will be invited to a submission in two special issues:

    Important dates

    2 March 2010: Deadline for full paper submission
    22 March 2010: Notification of acceptance
    19 April 2010: Deadline for Camera Ready Papers
    28-30 July 2010: ISDA ’10 (IDT’10) Conference

    Linking External Components to a Spatio-temporal Modelling Framework: Coupling MODFLOW and PCRaster

    In Environmental Science, GIS, Modeling, Spatial Analysis, Temporal Analysis on February 4, 2010 at 6:55 am

    Environmental Modelling & Software, Volume 24, Issue 9, September 2009, Pages 1088-1099

    O. Schmitz, D. Karssenberg, W.P.A. van Deursen, and C.G. Wesseling

    “An important step in the procedure of building an environmental model is the transformation of a conceptual model into a numerical simulation. To simplify model construction a framework is required that relieves the model developer from software engineering concerns. In addition, as the demand for a holistic understanding of environmental systems increases, access to external model components is necessary in order to construct integrated models.

    “We present a modelling framework that provides two- and three-dimensional building blocks for construction of spatio-temporal models. Two different modelling languages available in the framework, the first tailored and the second an enhanced Python scripting language, allow the development and modification of models. We explain for both languages the interfaces allowing to link specialised model components and thus extending the functionality of the framework. We demonstrate the coupling of external components in order to create multicomponent models by the development of the link to the groundwater model MODFLOW and provide results of an integrated catchment model. The approach described is appropriate for constructing integrated models that include a coupling of a small number of components.”

    A Spatial Analysis of Gullies on Mars

    In GIS, Planetary GIS, Spatial Analysis on February 2, 2010 at 7:50 am

    Proceedings of the 41st Lunar and Planetary Science Conference (2010)

    L. Kincy, C. Currit, D. Butler, and S. Fuhrmann

    “The possibility of life on Mars has intrigued people for over a century. A necessary re-quirement for life is water, a substance confirmed to exist on Mars. Gullies are features typically created by flowing water. Although Mars today is a desert planet, numerous geologically young gullies exist. The pres-ence of these gullies on the surface of other features, such as craters, suggests the gullies are young relative to the features on which they lie [1]. Many images of Martian gullies have been studied and compared to gullies on Earth to try to determine the origin of Mar-tian gullies. A gully is defined as a surficial feature having an alcove above a channel, and channels are typically associated with water [1].”

    Integrating Climate Change into Forest Planning: A Spatial and Temporal Analysis of Landscape Vulnerability

    In Climate Change, Environmental Science, Spatial Analysis, Temporal Analysis on February 1, 2010 at 9:31 am

    Craig Robert Nitschke, PhD Dissertation, University of British Columbia

    “The achievement of sustainable forest management requires the incorporation of risk and uncertainty into long-term planning. Climatic change is one stressor that will have significant impact on natural disturbances, ecosystems and biodiversity, particularly on landscapes influenced by forest management. Understanding where vulnerabilities lie and when climatic thresholds are reached are important areas of knowledge that must be used to manage the risks associated directly or indirectly with climatic change. The vulnerability of landscapes to natural disturbances, the resilience of ecosystems and distribution of biodiversity are all important components that need to be considered when undertaking forest planning. Through the use of modelling the vulnerability of a 145,000 ha landscape in the south-central interior of British Columbia was used as case study to assess the vulnerability of fire potential, fire regimes, ecosystem resilience and biodiversity to climatic change. The results from the analysis of fire potential identified a 30% increase in fire season length and a 95% increase in fire severity by 2085. A statistically significant shift in fire behaviour was also detected by 2070 with crown fires predicted to be more common. Climatic change was also found to significantly increase mean fire size by 2025 and decrease the mean return interval. By 2085, 95% of the landscape could burn every 50 years or less compared to the 34% currently classified. Ecosystem resilience was modelled to be affected to varying degrees with a shift in many species to higher elevation and/or to non-water deficit sites between 2025 and 2085. Six species were predicted to be at extreme risk and four others at high risk. An analysis of bark beetle risk identified 38.7% of the study area is currently at some degree of risk to attack. An analysis of biodiversity identified 19 indicator species that could be used to monitor management actions with a biodiversity management area that covers 66% of the landscape. These analyses were used as a foundation to guide forest zoning allocation, using the triad zoning framework, and for developing a “Climate-smart” management paradigm to be used for managing the landscape after allocation.”

    Reduction of Ground-based Sensor Sites for Spatio-temporal Analysis of Aerosols

    In Environmental Science, Spatial Analysis, Temporal Analysis on February 1, 2010 at 8:33 am

    Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data, Paris, France, 2009

    Vladan Radosavljevic, Slobodan Vucetic, and Zoran Obradovic

    “In many remote sensing applications it is important to use multiple sensors to be able to understand the major spatio-temporal distribution patterns of an observed phenomenon. A particular remote sensing application addressed in this study is estimation of an important property of atmosphere, called Aerosol Optical Depth (AOD). Remote sensing data for AOD estimation are collected from ground and satellite-based sensors. Satellite-based measurements can be used as attributes for estimation of AOD and in this way could lead to better understanding of spatio-temporal aerosol patterns on a global scale. Ground-based AOD estimation is more accurate and is traditionally used as ground-truth information in validation of satellite-based AOD estimations. In contrast to this traditional role of ground-based sensors, a data mining approach allows more active use of ground-based measurements as labels in supervised learning of a regression model for AOD estimation from satellite measurements. Considering the high operational costs of ground-based sensors, we are studying a budget-cut scenario that requires a reduction in a number of ground-based sensors. To minimize loss of information, the objective is to retain sensors that are the most useful as a source of labeled data. The proposed goodness criterion for the selection is how close the accuracy of a regression model built on data from a reduced sensor set is to the accuracy of a model built of the entire set of sensors. We developed an iterative method that removes sensors one by one from locations where AOD can be predicted most accurately using training data from the remaining sites. Extensive experiments on two years of globally distributed AERONET ground-based sensor data provide strong evidence that sensors selected using the proposed algorithm are more informative than the competing approaches that select sensors at random or that select sensors based on spatial diversity.”

    Spatial Patterns and Health Disparities in Pediatric Lead Exposure in Chicago: Characteristics and Profiles of High-Risk Neighborhoods

    In Environmental Science, Spatial Analysis, Statistics, Temporal Analysis on February 1, 2010 at 7:46 am

    The Professional Geographer, Volume 62, Issue 1 February 2010 , pages 46 – 65

    Tonny J. Oyana; Florence M. Margai

    “Lead poisoning remains a major environmental health threat and a persistent source of health disparities in the United States. In this retrospective study, statistical and geospatial approaches were used to evaluate age- and gender-specific differences in childhood lead prevalence across Chicago, assess the spatiotemporal dynamics of the disease, and identify the socioeconomic and racial composition of high-risk communities. Elevated blood lead levels (≥ 10 μ g/dL of lead) decreased significantly during the study period but disparities persisted across neighborhoods. A significant association was observed between high-risk neighborhoods and housing age, low income, and minority populations. These findings provide insights into the complex geographies of lead exposure and could serve as a basis for developing more targeted health intervention programs. “

    Spatial Analysis of Melioidosis Distribution in a Suburban Area

    In Environmental Science, GIS, Spatial Analysis on January 29, 2010 at 4:02 pm

    Epidemiology and Infection,22 Jan 2010

    M. L. CORKERON, R. NORTON and P. N. NELSON

    “Burkholderia pseudomallei, the causative agent of melioidosis is associated with soil. This study used a geographic information system (GIS) to determine the spatial distribution of clinical cases of melioidosis in the endemic suburban region of Townsville in Australia. A total of 65 cases over the period 1996–2008 were plotted using residential address. Two distinct groupings were found. One was around the base of a hill in the city centre and the other followed the old course of a major waterway in the region. Both groups (accounting for 43 of the 65 cases examined) are in areas expected to have particularly wet topsoils following intense rainfall, due to soil type or landscape position.”

    Surveillance of Mother-to-child HIV Transmission: Socioeconomic and Health Care Coverage Indicators

    In GIS, Social Science, Spatial Analysis on January 29, 2010 at 1:34 pm

    Revista de Saúde Pública, Dececember 2009; 43(6):1006-14.

    Barcellos C, Acosta LM, Lisboa E, Bastos FI. 

    “OBJECTIVE: To identify clustering areas of infants exposed to HIV during pregnancy and their association with indicators of primary care coverage and socioeconomic condition.

    “METHODS: Ecological study where the unit of analysis was primary care coverage areas in the city of Porto Alegre, Southern Brazil, in 2003. Geographical Information System and spatial analysis tools were used to describe indicators of primary care coverage areas and socioeconomic condition, and estimate the prevalence of liveborn infants exposed to HIV during pregnancy and delivery. Data was obtained from Brazilian national databases. The association between different indicators was assessed using Spearman’s nonparametric test.

    “RESULTS: There was found an association between HIV infection and high birth rates (r=0.22, p<0.01) and lack of prenatal care (r=0.15, p<0.05). The highest HIV infection rates were seen in areas with poor socioeconomic conditions and difficult access to health services (r=0.28, p<0.01). The association found between higher rate of prenatal care among HIV-infected women and adequate immunization coverage (r=0.35, p<0.01) indicates that early detection of HIV infection is effective in those areas with better primary care services.

    “CONCLUSIONS: Urban poverty is a strong determinant of mother-to-child HIV transmission but this trend can be fought with health surveillance at the primary care level.”

    Animals Populated Madagascar by Rafting There

    In Environmental Science, Geography, Science, Spatial Analysis on January 29, 2010 at 1:06 pm

    …from Purdue University News Service…

    “How did the lemurs, flying foxes and narrow-striped mongooses get to the large, isolated island of Madagascar sometime after 65 million years ago?

    “A pair of scientists say their research confirms the longstanding idea that the animals hitched rides on natural rafts blown out to sea.

    “The raft hypothesis has always been the most plausible, says Anne Yoder, director of the Duke University Lemur Center. She specializes in using molecular biogenetic techniques and geospatial analysis to examine the evolutionary history of Madagascar. But Ali and Huber’s study now puts hard data behind it, says the Duke professor of biology, biological anthropology and anatomy.”

    Groundwater Rights in Mexican Agriculture: Spatial Distribution and Demographic Determinants

    In Geography, Social Science, Spatial Analysis on January 29, 2010 at 8:53 am

    The Professional Geographer, Volume 62, Issue 1 February 2010 , pages 1 – 15

    Christopher A. Scott;  Sandy Dall’erba; Rolando Diacuteaz Caravantes

    “Groundwater use intensity and aquifer depletion increase from south to north with decreasing rainfall and increasing economic activity in Mexico. To heighten scholarly understanding and offer new insights that strengthen policy responses to aquifer depletion, we analyze the spatial distribution of agricultural groundwater use from irrigation well titles in 2,429 municipalities and its relation to agricultural surface water and population employed in agriculture. Exploratory spatial data analysis reveals spatial dependence among all three variables implying that policy initiatives to address intensive groundwater use must be targeted at clusters of aquifers and municipalities.”

    Crop Production and Road Connectivity in Sub-Saharan Africa: A Spatial Analysis

    In GIS, Spatial Analysis on January 26, 2010 at 7:59 am

    Africa Infrastructure Country Diagnostic (AICD) Working Paper 19

    Paul Dorosh, Hyoung-Gun Wang, Liang You, and Emily Schmidt

    February 2009

    “This study adopts a cross-sectional spatial approach to examine the impact of transport infrastructure on agriculture in Sub-Saharan Africa using new data obtained from geographic information systems (GIS). Our approach involves descriptive statistical analysis and econometric regressions of crop production or choice of technology for each location (a 9×9 kilometer pixel) in Sub-Saharan Africa on (a) agroecological zones and crop production potentials by the Food and Agriculture Organization (FAO) and the International Institute for Applied Systems Analysis (IIASA), (b) GIS data on crop production from the International Food Policy Research Institute’s (IFPRI) spatial crop allocation model (SPAM), and (c) road infrastructure based largely on data from the United Nations Environment Programme (UNEP) and estimated travel times.

    “We address three main issues. First, we analyze the impact of road connectivity on crop production and choice of technology when we control basic supply and demand factors. Second, we investigate the impact on agricultural output of investments that reduce travel time on roads of various types. Third, we provide an example of how this type of analysis could be used to construct benefit-cost ratios of alternative road investments in terms of enhanced agricultural output per dollar invested.

    “We find that agricultural production and proximity (as measured by travel time) to urban markets are highly correlated, even after taking agroecology into account. Likewise, adoption of highproductive/ high-input technology is negatively correlated with travel time to urban centers.

    “There is substantial scope for increasing agricultural production in Sub-Saharan Africa, particularly in more remote areas. Total crop production relative to potential production is 45 percent for areas within four hours’ travel time from a city of 100,000 people. In contrast, it is just 5 percent for areas more than eight hours away. These differences in actual versus potential production reflect the relatively small share of land cultivated out of total arable land in more remote areas.

    “For remote regions, low population densities and long travel times to urban centers sharply constrain production. Reducing transport costs (travel time) to these areas would expand the feasible market size for these regions, easing the constraint on production. If the expansion in production from these areas were small in terms of the relevant regional, national, or subnational market, average market prices outside the formerly remote region would be unaffected, and significant aggregate production increases could result.

    “We find some interesting differences between East Africa and West Africa. On average, East Africa has lower population density, smaller local markets, and lower road connectivity—the average travel time to the nearest city is more than twice that in West Africa. While average suitable area for crop production is similar in East and West Africa, average crop production per pixel in East Africa is just 30 percent of that in West Africa. Road connectivity has different impacts in the two regions. In East Africa the results are similar as for all Sub-Saharan Africa. Longer travel time decreases total crop production, and reducing travel time significantly increases adoption of high-input/high-yield technology in East Africa, but the impacts are insignificant for West Africa. This may be because the more densely roads are connected, the smaller the marginal benefits of more connections. West Africa already has a relatively well-connected road network.”

    Krigging as a Tool for Interpreting Structural Data: Exploring Spatial Analysis of Complex Folding on Seguin Island, Maine

    In Science, Spatial Analysis, Statistics on January 26, 2010 at 7:51 am

    Geological Society of America, Northeastern Section (45th Annual) and Southeastern Section (59th Annual) Joint Meeting (13-16 March 2010)

    BABCOCK, Lori N., LIPIEC, Eva, BAMPTON, Matthew, and SWANSON, Mark T.

    “Seguin Island, located ~12 km SSW of Georgetown, Maine and SE of the Norumbega fault zone consists of Devonian upright F2 anticlines and synclines, with complex parasitic fold structures. Ordovician Cape Elizabeth amphibolite gneiss and syntectonic granite dikes are exposed over the entire coast of the island. Structural data was collected in the NE zone of the western lobe where the folds are best exposed to assess the results of the spatial analysis of collected field data. Orientations of gneissic layering, axial planes, and fold axes were taken with a Brunton compass and recorded with handheld GPS. Gneissic layer lines were traced 2-3 m apart using RTK GPS and Total Stations to delineate the exact fold geometry, and interpreted extensions were digitized in the lab. The fold structures were found to be tight, SW-plunging with NNE striking axial planes, a wavelength of ~10m and amplitude of ~5m but can be highly variable with smaller scale parasitic folds abundant. Kriging, a spatial analysis technique that interpolates values between measured points was used to analyze the structural data. The results of kriging are based on a selected density of data points, or kernel, which best represents the entire set. Effective selection of these points requires knowledge of variations in the dataset. Strike and trend structural measurements were normalized to an 180o scale and divided into nine classes to best display the data. After kriging, the data was converted into a histogram with breaks that were manually shifted to reclassify the data. These breaks were adjusted to better represent the variance of data from the mode in each set. Strong correlations were found in the strike of gneissic layers, and axial planes, and the trend of fold axes. Strike of gneissic layers alternated NNE to NE orientations, suggesting differences in limb orientation across anticline and syncline fold axes. All dip and plunge measurements also became less steep from N to S, clearly visible in the kriging results. Kriging produced interpolated results that clearly reflected the structure of the local area, providing a useful means of visualization. Kriging can provide valuable insight into prevailing structural patterns, correlating features across a given area, and results in a representation of geologic data that is interpretable on an entirely new level.”

    Spatial and Temporal Analysis of Non-Recoverable Strain Geometry as Documented by the Inversion of Earthquake Focal Mechanisms in West-Central Taiwan

    In Environmental Science, Science, Spatial Analysis, Temporal Analysis on January 25, 2010 at 8:13 am

    Geological Society of America, Northeastern Section (45th Annual) and Southeastern Section (59th Annual) Joint Meeting (13-16 March 2010)

    LAMONT, Ellen Ari, LEWIS, Jon C., BYRNE, Timothy, CRESPI, Jean M., and RAU, Ruey-Juin

    “The geologically young (<4Ma) Taiwan Orogen reflects ongoing, rapid (~80mm/yr) arc-continent collision. The collision of the northeast-trending Chinese passive continental margin with the north-trending Luzon volcanic arc on the Philippine Sea plate has caused extensive deformation within the orogen as the collision has propagated from north to south. Additionally, magnetic anomaly patterns in western Taiwan suggest that mountain building in this region is occurring above a relict fracture zone in the lower plate. The relative motion between the Eurasian and Philippine Sea plates here has resulted in numerous large thrust earthquakes. One such earthquake was the 1999 shallow, moment magnitude 7.6, Chi-Chi earthquake in west-central Taiwan. The main shock ruptured the Chelungpu fault horizontally over 80km. Earthquake ruptures such as these reflect non-recoverable strain in the crust related to tectonic forces. By modeling pooled earthquake focal mechanism data from the 1999 Chi-Chi earthquake and related events, using an adaptation of the micropolar continuum model, we were able to solve for best-fitting, partial strain tensors and thus examine the 3-Dimensional geometry of non-recoverable strain. Our results indicate that the dominant mode of deformation in the orogen southeast of the fracture zone is orogen subparallel stretching accommodated by both normal and strike-slip faulting.”

    World Bank Awards Contract for Spatial Analysis of Natural Hazard and Climate Change Risks in Vietnam

    In Climate Change, Environmental Science, GIS, Imagery, Spatial Analysis, Statistics on January 22, 2010 at 7:17 am

    Spatial Analysis of Natural Hazard and Climate Change Risks in Can Tho, Dong Hoi, and Hanoi cities in Viet Nam

    Under a contract from the World Bank, GeoVille has performed a spatial analysis of natural hazard and climate change risks for disaster risk reduction into overall urban development in Can Tho, Dong Hoi, and Hanoi cities, Vietnam. The assessment covers satellite, topographical and multi-level GIS based generation of natural hazards and climate change hazard potential maps, description of methods and provision of statistics and description of hazard potential profiles.

    The scope of the contract includes project management; satellite, topographical, and multi-level GIS based generation of natural hazards and climate change hazard potential maps; and description of methods and provision of statistics and description of hazard potential profiles.

    About GeoVille

    GeoVille Group is an internationally operating company providing products, services and consultancy in the environmental and geo-spatial domain, specializing in Earth observation and GIS applications.

    We are dedicated to customer satisfaction and delivering quality controlled geo-information products.

    We have successfully carried out projects in over 60 countries.

    GeoVille Information Systems GmbH and GeoVille Environmental Services sàrl are based in Austria and Luxemburg.

    Post-Doctoral Scholar: Hydrogeomorphic Response to Changing Climates in the Pacific Northwest, Oregon State University

    In Climate Change, Education, Environmental Science, GIS, Spatial Analysis, Statistics on January 20, 2010 at 10:15 am

    “We are looking for someone to co-lead a multi-year, inter-institutional research effort to characterize and forecast the effects of changing climate on streamflows and geomorphic processes in the Pacific Northwest. Focus will be on developing and extending theoretical and empirical models of hydrologic response to climate drivers, emphasizing the role of geologic and ecologic controls and filters. The individual hired will have primary responsibility for exploring fruitful lines of attack on the problem, data acquisition and analysis, developing and applying relevant hydrologic and statistical models, and reporting results as journal publications and presentations. This post-doctoral position is with the Watershed Processes Group of Oregon State University (www.fsl.orst.edu/wpg), and the person hired will work closely with federal scientists from the USDA Forest Service Pacific Northwest Research Station.

    “Qualifications:

    1. Ph.D. in hydrology, geomorphology, watershed sciences, or a closely related field, with a demonstrated record of publication or other successful dissemination of work.
    2. Strong fundamental understanding of hydrologic processes at the scale of small watersheds to larger catchments, with expertise in one or more of the following: snowpack dynamics, groundwater processes, ecohydrologic interactions, drainage network response to precipitation/runoff relationships.
    3. Experience and facility with distributed parameter hydrologic models; familiarity with climate models and climate change scenarios desirable
    4. Strong statistics, data analysis and visualization skills, particularly with respect to long time-series data sets.
    5. High level working knowledge of GIS and other spatial analysis tools. Expertise with interpreting remote sensing a plus.

    Please send a letter of application describing your research experience and qualifications relevant to this position, a complete resume with links to publications, and the names, email addresses and telephone numbers of three references to Sarah Lewis, sarah.lewis@oregonstate.edu or 3200 SW Jefferson Way, Corvallis, Oregon 97330. Review of applications will begin February 15, 2010, and continue until a suitable candidate is found.”

    Spatial Distribution of African Animal Trypanosomiasis in Western Kenya

    In Environmental Science, Spatial Analysis on January 19, 2010 at 8:35 am

    Spatial Distribution of African Animal Trypanosomiasis in Suba and Teso Districts in Western Kenya

    Samuel Thumbi, Joseph Jung’a, Reuben Mosi, Francis McOdimba

    BMC Research Notes 2010, 3:6

    “Studies on the epidemiology of African Animal Trypanosomiasis (AAT) rarely consider the spatial dimension of disease prevalence. This problem is confounded by use of parasitological diagnostic methods of low sensitivity in field surveys.

    “Here we report a study combining highly sensitive and species specific molecular diagnostic methods, and Geographical information system (GIS) for spatial analysis of trypanosome infection patterns, to better understand its epidemiology. Blood samples from 44 and 59 animals randomly selected from Teso and Suba districts respectively were screened for trypanosomes using PCR diagnostic assays.”

    V1 Magazine Interview with Jack Dangermond: GeoDesign, Virtual Cities, Climate Change, ArcGIS 10, and More

    In Climate Change, Design, ESRI, Environmental Science, GIS, Science, Spatial Analysis, Visualization on January 19, 2010 at 6:53 am

    …from V1 Magazine…

    “V1: You’re a high-energy individual that has applied every waking hour for more than 40 years toward the design and application of technology to help manage the earth. Are your concerns for our planet a strong motivator for you?

    “Dangermond: This purpose has always been the reason for ESRI, and why all of us here work so hard. I think in our own small way ESRI, through the incredible work of our users, has been able to make a difference. However, given the immensity of the problem there is so much more to be done, and we need to keep driving our vision of integrating  geographic thinking into virtually all human activities.”

    The Role of Spatial Analysis in Livestock Research for Sustainable Development

    In Environmental Science, Spatial Analysis on January 18, 2010 at 6:15 am

    GIScience & Remote Sensing, v. 46(1). p. 128-138.

    Notenbaert, A.M.O.

    “The role of spatial analysis in livestock research for sustainable development is pervasive because its versatility supports livestock researchers at many stages of their work. Spatial analysis assists case study identification, characterizes the geographic context of research findings, and subsequently is used to assess the context for out-scaling purposes. Components of livestock systems and elements of their context and interrelationships can be characterized with an explicit spatial dimension. Output from spatial analysis linked to the results of simulation and optimization models provides support for decision-making. This is especially important where decisions involve different disciplines and interaction with a variety of experts usually working together in a sustainable development team.”

    Spatial Assessment and Analysis of Vulnerability: GIScience Applied in the Interdisciplinary Domain of Hazard and Climate Change Research

    In Climate Change, Conferences, GIS, GIScience, Spatial Analysis, Temporal Analysis, Visualization on January 15, 2010 at 6:59 am

    06 – 07 July 2010,  Salzburg, Austria

    “This theme is expected to highlight different developed and currently investigated methodologies to spatially assess vulnerability. It will specifically address the issue of vulnerability assessment, independent from conceptual discussions. The focus will be on the review and discussion of different methods of GIScience employed to assess, quantify and represent vulnerability as integrated spatial phenomena. Within a workshop session, current achievements and future research challenges will be identified and formulated.

    “Topics:

    • Assessments in the domains of disaster risk reduction, climate change, natural hazards and human security;
    • Methods for indicator selection and index construction;
    • Scale issues in vulnerability assessments;
    • Validation and accuracy of vulnerability assessments;
    • Spatio-temporal visualisation of complex indicators.

    “The workshop is scheduled for Tuesday, July 6 and Wednesday, July 7, 2010 and will be followed by the annual GI_Forum. In addition to presentations ranging from different scholarly schools of vulnerability the workshop will focus on output oriented discussion sessions.

    “The papers will be peer-reviewed and published in a book.”

    Spatial and Temporal Analysis of the Nitrate Concentrations in Groundwater for South Africa

    In Environmental Science, Spatial Analysis, Temporal Analysis on January 14, 2010 at 9:00 am

    Biennial Groundwater Conference of the International Association of Hydrogeologists. Somerset West, South Africa, 16-18 November 2009

    Maherry, A; Clarke, S; Tredoux, G; Engelbrecht, P

    “The aims of this investigation was to create an updated view of the nitrate distribution for the country, to identify whether there are any gaps or significant changes in the distribution of nitrate concentration over the sampling record and identify areas where nitrate pollution occurs as an ecological hazard for priority research and remediation. Data was sourced from the national groundwater database for the entire country for the period up until 2008. Previous maps used data pre-1990 and up to 2001. Additional nitrate data was sourced to supplement the NGDB data. The data was evaluated using excel pivot tables, and maps plotted using ArcMAP. Maps of the total count representing the total number of points sampled and their densities for South Africa, as well as the minimum, maximum and average nitrate concentration for the various decades were used to evaluate the extent and duration of nitrate pollution in South Africa. The nitrate concentrations were overlayed on the geological or hydroterrains and land cover for South Africa to investigate if there are links between lithology, land cover and nitrate concentrations. Comparison of maps compiled for different periods indicate that the Western Cape now has elevated nitrate levels, possibly associated with agricultural stock farming. The Northern Cape Province, in particular the Kalahari has elevated nitrate levels, but a distinct lack of recent sampling may mask the extent of the current spatial distribution of nitrate concentrations. The scarcity of sampling points within urban centres makes it difficult for pollution monitoring and control to take place.”

    Patterns of Urban Violent Injury: A Spatio-Temporal Analysis

    In GIS, Social Science, Spatial Analysis, Temporal Analysis on January 13, 2010 at 7:13 am

    Michael Cusimano, Sean Marshall, Claus Rinner, Depeng Jiang, Mary Chipman

    PLoS ONE 5(1)

    “Injury related to violent acts is a problem in every society. Although some authors have examined the geography of violent crime, few have focused on the spatio-temporal patterns of violent injury and none have used an ambulance dataset to explore the spatial characteristics of injury. The purpose of this study was to describe the combined spatial and temporal characteristics of violent injury in a large urban centre.

    “Using a geomatics framework and geographic information systems software, we studied 4,587 ambulance dispatches and 10,693 emergency room admissions for violent injury occurrences among adults (aged 18–64) in Toronto, Canada, during 2002 and 2004, using population-based datasets. We created kernel density and choropleth maps for 24-hour periods and four-hour daily time periods and compared location of ambulance dispatches and patient residences with local land use and socioeconomic characteristics. We used multivariate regressions to control for confounding factors. We found the locations of violent injury and the residence locations of those injured were both closely related to each other and clearly clustered in certain parts of the city characterised by high numbers of bars, social housing units, and homeless shelters, as well as lower household incomes. The night and early morning showed a distinctive peak in injuries and a shift in the location of injuries to a “nightlife” district. The locational pattern of patient residences remained unchanged during those times.

    “Our results demonstrate that there is a distinctive spatio-temporal pattern in violent injury reflected in the ambulance data. People injured in this urban centre more commonly live in areas of social deprivation. During the day, locations of injury and locations of residences are similar. However, later at night, the injury location of highest density shifts to a “nightlife” district, whereas the residence locations of those most at risk of injury do not change.”

    Developing a Web-Based e-Research Facility for Socio-Spatial Analysis to Investigate Relationships between Voting Patterns and Local Population Characteristics

    In GIScience, Social Science, Spatial Analysis on January 7, 2010 at 7:19 am

    Journal of Spatial Science, Vol. 54, No. 2

    E. Liao, T- K. Shyy, R. J. Stimson

    “This paper describes the development of an e-research facility for socio-spatial analysis. It is illustrated with the example of a prototype Web-based GIS and statistical application for the analysis, modelling and visualisation of the relationships between patterns of voting at the 2007 Australian federal election and the demographic and socio-economic characteristics of local populations using 2006 census data. The facility incorporates a web-based GIS which can generate maps displaying patterns of voting for political parties across polling booths with overlay data showing the population characteristics living within the surrounding polling booth catchments. Various classification approaches including equal interval, quantile, median-based natural breaks, and location quotients can be used to generate different map displays. Statistical analysis functionality – such as regression analysis, cluster analysis and discriminant analysis – enables researchers to conduct on-line statistical modelling and the visualisation of outputs. This prototype facility not only gives researchers and students on-line access to socio-spatial datasets through a metadata directory, but also enhances the capacity and capability of researchers and students to undertake spatially integrated social science research.”

    The Spatial Patterns of Adverse Health Effects of Ozone Pollution on Childhood Respiratory Diseases in Urban Houston

    In ESRI, GIS, Geography, Science, Spatial Analysis, Statistics on January 6, 2010 at 6:38 am

    Annals of GIS, Volume 15, Issue 2 December 2009 , pages 127 – 140

    Shing Lin; Yongmei Lu

    “This paper reports on the investigation of the spatial patterns and variations of adverse health effects of ozone pollution on childhood respiratory diseases in Houston, Texas. The study period is June to September of 2001. No significant global relationship exists between ozone pollution and prevalence of childhood respiratory diseases. However, geographically weighted regression (GWR) analysis reveals spatially varied adverse health effect. With the guidance from GWR results, the association between ozone pollution and childhood respiratory disease prevalence is proved to be significant in three sub-regions. Moreover, spatial regression analysis suggests the presence of spatial dependence of the prevalence of childhood respiratory diseases.

    “The spatial variation of the relationship between ozone pollution and childhood respiratory disease prevalence indicates health effects of confounding or intervening factors. The spatial dependency of disease prevalence is related to both the spatial patterns of pollution and those of confounding factors. The findings call for future investigation to examine the factors that might be working together with or against ozone pollution when health effects are concerned. For health practice and management, a set of neighborhood-specific policy, practice, and resource allocation strategies need to be developed to minimize the adverse health effects of ozone pollution.”

    Geospatial Modelling Environment: A Platform Designed for Rigorous Spatial Analysis and Modelling

    In ESRI, GIS, Modeling, Spatial Analysis, Statistics on January 5, 2010 at 7:57 am

    “The promise of GIS has always been that it would allow us to obtain better answers to our questions. But this is only possible if we have tools that allows us to perform rigorous quantitative analyses designed for spatial data. The Geospatial Modelling Environment (GME) is a platform designed to help to facilitate rigorous spatial analysis and modelling.

    “GME provides you with a suite of analysis and modelling tools, ranging from small ‘building blocks’ that you can use to construct a sophisticated work-flow, to completely self-contained analysis programs. It also uses the extraordinarily powerful open source software R as the statistical engine to drive some of the analysis tools. One of the many strengths of R is that it is open source, completely transparent and well documented: important characteristics for any scientific analytical software.

    “It incorporates most of the functionality of its predecessor, HawthsTools, but with some important improvements. It has a greater range of analysis and modelling tools, supports batch processing, offers new graphing functionality, automatically records work-flows for future reference, supports geodatabases, and can be called programatically.”

    2010 Advanced Spatial Analysis Workshop Schedule from PRI and CSISS

    In Education, GIScience, Spatial Analysis, Statistics on January 4, 2010 at 11:23 am

    The Population Research Institute (PRI) at Penn State and the Center for Spatially Integrated Social Science (CSISS) at UC Santa Barbara are pleased to announce the offering of two summer workshops in 2010 under the Advanced Spatial Analysis Training for Population Scientists program (funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). This year both workshops will take place in July 2010 on the UC Santa Barbara campus with Don Janelle serving as the local coordinator. These workshops have a participation cap and are highly competitive. Anyone interested in these workshops must complete an application form (to be posted on‐line at the project website in mid‐January 2010). Closing dates for receipt of an application will be March 31, 2010 and successful applicants will receive notification of invitation to participate by mid‐April.

    • Geographically Weighted Regression – July 12‐16, 2010 (arrival day July 11th)
      The instructors include A. Stewart Fotheringham, Martin Charlton and Chris Brunsdon. A similar workshop was held at Penn State in 2008 and the format for the 2010 workshop will likely be similar. See http://www.csiss.org/GISPopSci/workshops/2008/PSU/agenda.php
    • Spatial Pattern Analysis ‐ July 19‐23, 2010 (arrival day July 18th)
      The instructors include Art Getis, John Weeks and Jared Aldstadt. A similar workshop was held in 2008 at UCSB and the format for the 2010 workshops will likely be similar. See http://www.csiss.org/GISPopSci/workshops/2008/UCSB/agenda.php

    Please consult the training program website for updates: http://www.csiss.org/GISPopSci/

    Contemporary Roles for Spatial Analysis in Archaeology: Seminar Series at University College London

    In Social Science, Spatial Analysis on January 4, 2010 at 9:49 am

    The UCL Institute of Archaeology Seminar Series (January–March 2010)
    31-34 Gordon Square, London WC1H 0PY
    Mondays 4pm, Room 612 (followed by a wine reception)

    Schedule

    • 11 January 2010 – Benjamin Ducke (Oxford Archaeology)
      ‘Science without software no longer. Archaeological data analysis and the Open Source paradigm’
    • 18 January 2010 – Chris Green (University of Leicester)
      ‘Temporal GIS and archaeology’
    • 25 January 2010 – Tony Wilkinson (Durham University)
      ‘From household to region: incorporating agency into the interpretation of regional settlement’
    • 1 February 2010 – Tim Williams (University College London)
      ‘Earth viewers and GIS in archaeological resource management: access and accessibility’
    • 08 February 2010 – Luke Premo (Max Planck Institute for Evolutionary Anthropology)
      ‘A spatially explicit model of Early Stone Age archaeological landscapes’
    • 15 February 2010 (Reading Week – no seminar)
    • 22 February 2010 – Frederic Fol Leymarie (Goldsmiths College)
      ‘Advances in 3D procedural modelling with applications to archaeology’
    • 01 March 2010 – Michael Barton (Arizona State University)
      ‘Stories of the past or science of the future? Archaeology and computational social science’
    • 08 March 2010 – Irmela Herzog (Archaeological Heritage Management of the Rhineland)
      ‘Patterns of movement, least cost paths and our understanding of the archaeological record’
    • 15 March 2010 – Kate Devlin (Goldsmiths College)
      ‘Illuminating virtual reconstructions of past environments’
    • 22 March 2010 – Mark Lake (University College London)
      ‘Rewind and fast‐forward: how archaeological GIS analyses recapitulate general theory’

    GIS, Multi-criteria and Multi-factor Spatial Analysis for the Probability Assessment of the Existence of Illegal Landfills

    In Environmental Science, GIS, Spatial Analysis on January 4, 2010 at 7:21 am

    International Journal of Geographical Information Science, Volume 23, Issue 10 October 2009 , pages 1233 – 1244

    Giancarlo Biotto;  Sonia Silvestri;  Lucia Gobbo;  Elisa Furlan;  Sonia Valenti; Roberto Rosselli.

    “This work deals with the identification of potentially contaminated areas using remote sensing, geographic information systems (GIS) and multi-criteria spatial analysis. The identification of unknown illegal landfills is a crucial environmental problem in all developed and developing countries, where a large number of illegal waste deposits exist as a result of fast, and relatively unregulated, industrial growth over the past century. The criteria used to perform the spatial analysis are here selected by considering the characteristics which are ‘desirable’ for an illegal waste disposal site, chiefly related to the existence of roads for easy access and to a low population density which facilitates unnoticed dumping of illegal waste materials. A large dataset describing known legal and illegal landfills and the context of their location (population, road network, etc.) was used to perform a spatial statistical analysis to select factors and criteria allowing for the identification of the known waste deposits. The final result is a map describing the likelihood of an illegal waste deposit to be located at any arbitrary location. Such a probability map is then used together with remote sensing techniques to narrow down the set of possibly contaminated sites (Silvestri and Omri, 2008), which are candidates for further analyses and field investigations. The importance of the integration of GIS and remote sensing is highlighted and represents a key instrument for environmental management and for the spatially-distributed characterization of possible uncontrolled landfill sites.”

    A Temporal-Spatial Analysis of Malaria Transmission in Adama, Ethiopia

    In Environmental Science, Spatial Analysis, Temporal Analysis on December 31, 2009 at 10:12 am

    The American Journal of Tropical Medicine and Hygiene, 81(6), 2009, pp. 944-949

    Ingrid Peterson, Luisa N. Borrell, Wafaa El-Sadr, and Awash Teklehaimanot

    “ Urban malaria is a growing problem in Africa. Small-scale spatial studies are useful in identifying foci of malaria transmission in urban communities. A population-based cohort study comprising 8,088 individuals was conducted in Adama, Ethiopia. During a single malaria season, the Kulldorff scan statistic identified one temporally stable spatial malaria cluster within 350 m of a major Anopheles breeding site. Factors associated with malaria incidence were residential proximity to vector breeding site, poor house condition (incidence rate ratio [IRR] = 2.0, 95% confidence interval [CI] = 1.4, 2.9), and a high level of vegetation (IRR = 1.8, 95% CI = 1.0, 3.3). Maximum (IRR = 1.4, 95% CI = 1.1, 1.9) and minimum daily temperatures (°C; IRR = 1.3, 95% CI = 1.2, 1.5) were positively associated with malaria incidence after a 1-month delay. Rainfall was positively associated with malaria incidence after a 10-day delay. Findings support the use of small scale mapping and targeted vector control in urban malaria control programs in Africa.”

    Multi-scale Spatiotemporal Analyses of Moose-vehicle Collisions: A Case Study in Northern Vermont

    In Environmental Science, GIS, Spatial Analysis, Temporal Analysis on December 31, 2009 at 5:26 am

    International Journal of Geographical Information Science, Volume 23, Issue 11 November 2009 , pages 1389 – 1412

    Giorgos Mountrakis; Kari Gunson.

    “Moose-vehicle collisions (MVCs) pose a serious safety and environmental concern in many regions of Europe and North America. For example, in the state of Vermont, one-third of all reported MVCs resulted in motorist injury or fatality while collisions have increased from two in 1982 to 164 in 2002. Our work used a MVC dataset from 1983 to 1999 in the Northeastern Highlands of Vermont (four major roads) to perform space, time and spatiotemporal analyses and guide future mitigation strategies. An adapted kernel density estimator was implemented for exploratory analyses to detect high density collision hotspots on roads. The kernel in space showed seven major density peaks which varied in magnitude and spread between roads. The kernel estimator in time for all roads showed an exponentially increasing trend with annual periodicity and a seasonal cyclic component, where the majority of collisions occurred from May to October. Spatiotemporal kernel estimation exhibited discontinuous density hotspots in time and space suggesting changing animal movement patterns across roads. We used an adapted Ripley’s K-function to test the hypothesis that MVCs clustering occurred at multiple scales in space, in time and in space-time combined. Statistically significant spatial clustering was evident on all roads at spatial scales from 2 to 10 km. A more consistent clustering in time occurred on all roads at a scale distance of 5 years. Similar to the kernel estimation, annual periodicity was also evident. Positive space-time clustering was present at small spatial (5 km) and temporal scales (2 years) indicating that where MVCs occur is also influenced by when they occur. In retrospect, using multiple road lengths, and the combined kernel estimation and Ripley’s K-function in time and space, provided a powerful methodology to study varying spatiotemporal patterns of wildlife collisions along roads. This can greatly assist transportation planners in identifying optimal mitigation strategies along specific roads, such as deciding on location and spatial length for permanent and expensive measures (e.g. crossing structures and associated fencing) versus less permanent and inexpensive structures (e.g. wildlife signage and reduced speed limits).”

    Spatio-temporal Analysis of Noise Pollution near Boston Logan Airport: Who Carries the Cost?

    In Environmental Science, GIS, Spatial Analysis, Statistics, Temporal Analysis on December 30, 2009 at 6:57 am

    Urban Studies, Vol. 47, No. 1, 169-182 (2010)

    Yelena Ogneva-Himmelberger, Brian Cooperman

    “Airports are often located near densely populated residential areas, affecting a large number of people. Thus, knowing socio-demographic characteristics of the noise-affected areas is important for the development of policies on noise control and abatement. This study proposes a new methodology that combines airport noise models with spatial statistics and geographical information systems to identify spatial clusters of socio-demographic characteristics in relationship to the noise level. Statistically significant ‘hot’ and ‘cold’ socio-demographic clusters represent spatial concentrations of certain social groups, corresponding to various levels of vulnerability to environmental impacts. Results show that the population ‘paying’ for the cost of noise from Logan International Airport in Boston, USA, is highly vulnerable as there are more minority and lower-income populations, and lower house prices in the noise-affected areas. These results should draw the attention of policy-makers and the public as policies for noise abatement are being developed.”

    Modeling Uncertainty of Moving Objects on Road Networks via Space-time Prisms

    In GIScience, Modeling, Spatial Analysis, Temporal Analysis on December 29, 2009 at 8:06 am

    International Journal of Geographical Information Science, Volume 23, Issue 9 September 2009 , pages 1095 – 1117

    Bart Kuijpers; Walied Othman.

    “Moving objects produce trajectories, which are typically observed in a finite sample of time-stamped locations. Between sample points, we are uncertain about the moving objects’s location. When we assume extra information about an object, for instance, a (possibly location-dependent) speed limit, we can use space-time prisms to model the uncertainty of an object’s location.

    “Until now, space-time prisms have been studied for unconstrained movement in the 2D plane. In this paper, we study space-time prisms for objects that are constrained to travel on a road network. Movement on a road network can be viewed as essentially one-dimensional. We describe the geometry of a space-time prism on a road network and give an algorithm to compute and visualize space-time prisms. For experiments and illustration, we have implemented this algorithm in MATHEMATICA.

    “Furthermore, we study the alibi query, which asks whether two moving objects could have possibly met or not. This comes down to deciding if the chains of space-time prisms produced by these moving objects intersect. We give an efficient algorithm to answer the alibi query for moving objects on a road network. This algorithm also determines where and when two moving objects may have met.”

    Estimating Components of Population Change from Census Data for Incongruent Spatial/Temporal Units and Attributes

    In GIScience, Social Science, Spatial Analysis, Temporal Analysis on December 29, 2009 at 7:47 am

    Journal of Spatial Science, Vol. 54, No. 2

    R. G. Cromley, A. Y. Ebenstein, D. M. Hanink

    “When calculating the components of population change over time, the spatial units of analysis must remain constant.  However, the boundaries of these units often change from one census to the next.  Another limiting factor is the absence of data values for the time period.  Net migration figures might be available for a five year interval in a census but not for a twenty year interval.  GIS and areal interpolation are used here to rectify boundary changes that occur from one census to the next and shift-share analysis is used to estimate the components of population change from the census data.   These methods are applied to a county level study of population change in China between 1982 and 2000.”

    Healthcare Access, Socioeconomic Factors and Late-stage Cancer Diagnosis: An Exploratory Spatial Analysis and Public Policy Implication

    In Social Science, Spatial Analysis on December 28, 2009 at 6:57 am

    International Journal of Public Policy, 2010 – Vol. 5, No.2/3 pp. 237 – 258

    Fahui Wang, Lan Luo, Sara McLafferty

    “Patients diagnosed with late-stage cancer have lower survival rates than those with early-stage cancer. This paper examines possible associations between several risk factors and late-stage diagnosis for four types of cancer in Illinois: breast cancer, prostate cancer, colorectal cancer, and lung cancer. Potential risk factors are composed of spatial factors and nonspatial factors. The spatial factors include accessibility to primary healthcare and distance or travel time to the nearest cancer screening facility. A set of demographic and socioeconomic variables are consolidated into three nonspatial factors by factor analysis. The Bayesian model with convolution priors is utilised to analyse the relationship between the above risk factors and each type of late-stage cancer while controlling for spatial autocorrelation. The results for breast cancer suggest that people living in neighbourhoods with socioeconomic disadvantages and cultural barriers are more likely to be diagnosed at a late stage. In regard to prostate cancer, people in regions with low socioeconomic status are also more likely to be diagnosed at a late stage. Diagnosis of late-stage colorectal or lung cancer is not significantly associated with any of the abovementioned risk factors. The results have important implications in public policy.”

    National Science Foundation TeraGrid Workshop on Cyber-GIS, Washington, DC, 02-03 February, 2010

    In Conferences, GIS, Modeling, SDI, Science, Spatial Analysis, Visualization on December 23, 2009 at 10:00 am

    The NSF Cyber-GIS workshop will take place in conjunction with the 2010 UCGIS Winter Meeting at Doubletree Hotel, Washington, DC. The workshop will focus on the following themes and topics:

    • Complex geospatial systems and simulation of geographic dynamics
    • Computational intensity of spatial analysis and modeling
    • Data-intensive geospatial computation and visualization
    • High-performance, distributed, and/or collaborative GIS
    • Geospatial ontology and semantic web
    • Geospatial middleware, Clouds, and Grids
    • Open source GIS
    • Participatory spatial decision support systems
    • Science drivers for, and applications of Cyber-GIS
    • Spatial data infrastructure

    More information

    A New Methodology for Measuring Coastline Recession using Buffering and Non-linear Least Squares Estimation

    In Environmental Science, GIScience, Spatial Analysis, Statistics on December 22, 2009 at 7:21 am

    International Journal of Geographical Information Science, Volume 23, Issue 9 September 2009 , pages 1165 – 1177

    Joon Heo;  Jung Hwan Kim; Jin Woo Kim.

    “Coastline recession is one of the best indicators of coastal erosion. Three methods for computing coastline recession – the baseline approach, the dynamic segmentation approach and the area-based approach – have been used, each of which has one or more drawbacks. To overcome these problems, a new methodology for measuring coastline recession is proposed, using buffering and non-linear least squares estimation. The proposed method was compared with the three existing methods with respect to two simulated cases and two real coastlines. Test results confirmed that the new method is more reliable than the three other methods, all of which are susceptible to variability of recession, scale, number of line segments, length of coastlines and direction of the baseline. The proposed method, incorporating two physically meaningful values – magnitude and variability of coastline recession according to the mean and standard deviation of coastline offsets, respectively – presents itself as an effective alternative method of assessing coastline recession.”

    Spatial Analysis and Modeling to Assess and Map Current Vulnerability to Extreme Weather Events in the Grijalva–Usumacinta Watershed, México

    In Climate Change, Modeling, Spatial Analysis on December 22, 2009 at 7:12 am

    2009 IOP Conf. Ser.: Earth Environ. Sci. 8 012021

    D López L

    “One of the major concerns over a potential change in climate is that it will cause an increase in extreme weather events. In Mexico, the exposure factors as well as the vulnerability to the extreme weather events have increased during the last three or four decades. In this study spatial analysis and modeling were used to assess and map settlement and crop systems vulnerability to extreme weather events in the Grijalva – Usumacinta watershed. Sensitivity and coping adaptive capacity maps were constructed using decision models; these maps were then combined to produce vulnerability maps. The most vulnerable area in terms of both settlement and crop systems is the highlands, where the sensitivity is high and the adaptive capacity is low. In lowlands, despite the very high sensitivity, the higher adaptive capacity produces only moderate vulnerability. I conclude that spatial analysis and modeling are powerful tools to assess and map vulnerability. These preliminary results can guide the formulation of adaptation policies to an increasing risk of extreme weather events.”

    Call for Papers: Spatial Analysis of Past Built Environments, Berlin, Germany, 01-02 April 2010

    In Conferences, Social Science, Spatial Analysis on December 21, 2009 at 9:16 am

    Interdisciplinary and International Workshop on Spatial Analysis in Past Built Environments

    This two-day workshop aims to promote discussion between a range of researchers in the disciplines of history/archaeology, urbanism, architecture, and computer science who have an interest in the spatial analysis of the built environment, and especially of historic and prehistoric spaces.

    A number of very interesting speakers will be participating, including:

    • Prof. Bill Hillier (keynote speaker-The Bartlett School of Architecture, University College London)
    • Dr David Wheatley (University of Southampton)
    • Dr Graeme Earl (University of Southampton)
    • Hannah Stoeger (University of Leiden)
    • Prof. John Bintliff (University of Leiden)
    • Dr. Akkelies van Nes (Delft university of Technology)
    • Piraye Haciguzeller (Université catholique de Louvain)
    • Dr Quentin Letesson (Université catholique de Louvain)
    • Ulrich Thaler (German Archaeological Institute Athens)
    • Dr. Eleftheria Paliou (Topoi Excellence Cluster)

    If you are interested in participating send your abstracts (30min for presentation +questions) to epaliou@zedat.fu-berlin.de by the 20th of January 2010.

    A New Method for Spatial and Temporal Analysis of Risk in Water Resources Management

    In Environmental Science, Spatial Analysis, Temporal Analysis on December 21, 2009 at 8:11 am

    Journal of Hydroinformatics Vol 11 No 3–4 pp 320–329

    Slobodan P. Simonovic

    “Uncertainty in water resources management is in part about variability and in part about ambiguity. Both are associated with lack of clarity because of the behavior of all system components, lack of data, lack of detail, lack of structure to consider the water resources management problems, working and framing assumptions being used to consider the problems, known and unknown sources of bias, and ignorance about how much effort it is worth expending to clarify the management situation. The two major sources of variability are temporal and spatial heterogeneity. Temporal variability occurs when values fluctuate with time. Other values which are affected by spatial variability are dependent upon location of an area. A major part of the water resources management risk confusion relates to an inadequate distinction between the objective risk (real, physical) and subjective (perceived) risk. Because of the confusion between the two concepts, many characteristics of subjective risk are believed to be valid also for objective risk. The main objective of this paper is to initiate a discussion of the possible methodology for the reliability analysis of water resources systems that will be capable of: (a) addressing water resources uncertainty caused by variability and ambiguity, (b) integrating objective and subjective risk and (c) assisting the water resources management based on better understanding of temporal and spatial variability of risk.”

    Strategies for Real-time Spatial Analysis using Massively Parallel SIMD Computers: An Application to Urban Traffic Flow Analysis

    In GIS, Spatial Analysis on December 18, 2009 at 8:00 am

    International Journal of Geographical Information Science, Volume 10, Issue 6 September 1996 , pages 769 – 789

    Demin Xiong; Duane F. Marble.

    “The current research focuses upon the development of a methodology for undertaking real-time spatial analysis in a supercomputing environment, specifically using massively parallel SIMD computers. Several approaches that can be used to explore the parallelization characteristics of spatial problems are introduced. Within the focus of a methodology directed toward spatial data parallelism, strategies based on both location-based data decomposition and object-based data decomposition are proposed and a programming logic for spatial operations at local, neighborhood and global levels is also recommended. An empirical study of real-time traffic flow analysis shows the utility of the suggested approach for a complex, spatial analysis situation. The empirical example demonstrates that the proposed methodology, especially when combined with appropriate programming strategies, is preferable in situations where critical, real-time, spatial analysis computations are required. The implementation of this example in a parallel environment also points out some interesting theoretical questions with respect to the theoretical basis underlying the analysis of large networks.”

    The Role of Geological Modeling in a Web-based Collaborative Environment

    In Geography, Modeling, Spatial Analysis on December 10, 2009 at 8:22 am

    …from the 2009 Three-Dimensional Geologic Mapping Workshop held by the Illinois State Geological Survey…

    Keith Turner and Frank A D’Agnese

    “Over the past two decades, a series of sophisticated three-dimensional modeling technologies have been developed to address the need for a precise definition of subsurface conditions (Turner, 1991). Because geological modeling requires the extension of traditional GIS methods (Turner, 2000; 2006), the modeling process remains technically challenging. In 2001, during a conference sponsored by the European Science Foundation, four major impediments to the greater use of subsurface geological modeling by a broad spectrum of users were identified (Rosenbaum & Turner, 2003). These constraints were: (1) a lack of 3D/4D mathematical, cognitive, and statistical spatial tools, (2) a lack of cheap modeling tools designed for the shallow subsurface that can be operated without specialist personnel, (3) the inability of models to depict natural variability of geological systems, and (4) a shortage of case histories. By 2008, these constraints had been largely overcome with the use of new modeling software and techniques and, importantly, with an understanding of the needs of the client (Kessler, et al., 2008).”

    Video: Performing Proper Density Analysis

    In ESRI, GIS, Spatial Analysis, Video on December 10, 2009 at 8:18 am

    The purpose of this video is to explain the importance of the decisions that you make when running a density analysis, such as the neighborhood radius and the classification method that you choose for rendering your results.

    Part 1

    Part 2

    UGA Professors Win NASA Grant: Students Will Use Spatial Analysis to Study Effects of Climate Change on Birds

    In Climate Change, Environmental Science, Spatial Analysis on December 8, 2009 at 3:52 pm

    By Sandi Martin, Public Relations Coordinator, University of Georgia

    University of Georgia professors in two schools have received a $447,000 grant from NASA that will offer undergraduate students a year-long combination of classroom and field classes studying the effects of climate change on birds.

    NASA’s three-year global climate change education teaching and research grant funds instruction activities that are scheduled to begin with fall 2010 classes. The grant will fund fall, spring and summer courses that will teach students about global climate change models, research methods and designing field experiments. The final course in the lecture and lab series—to be held during summer classes—will have students perform their experiments in the field. That field experience will make students more competitive for graduate schools and jobs, said Jeffrey Hepinstall-Cymerman, an assistant professor of landscape ecology in the Warnell School of Forestry and Natural Resources. Hepinstall-Cymerman said the students will use NASA data, models, spatial analysis, statistics and field methods while studying the effects of climate change on birds and bird migration.

    “This training offers a unique opportunity for students to obtain an understanding of the complexities and challenges involved in predicting floral and faunal responses to a changing climate, in addition to exposing them to important field and analytical methods at the cutting edge of applied ecology,” he said.

    Hepinstall-Cymerman and two other professors in the Warnell School, Robert Cooper and Michael Conroy, are lead investigators on the grant, which also includes Marshall Shepherd, a professor in the Franklin College of Arts and Sciences. As part of the grant, the team will install ground sensors at Whitehall Forest, a research forest located off campus and managed by Warnell, and at the Coweeta Long Term Ecological Research station to allow students to compare ground measurements with measurements made with NASA satellites. This will allow students to see how the satellite images covering large areas compare to detailed information gathered on the ground, Conroy explained. “This is an excellent example of how you use that technology to teach,” he said.

    The effect of climate change on birds is sometimes overlooked when the controversial subject is debated, but Conroy notes that if springs continue to get warmer, then it affects when the primary food source for birds—insects—emerge. If birds don’t adjust to that change, he said, newly-hatched birds won’t have enough food.

    Global climate models are key tools for studying aspects of climate change. Shepherd, through funding from a Northeast Georgia PRISM (Partnership for Reform in Science and Mathematics) grant, implemented a fully functional educational global climate model called EdGCM into weather-climate exercises in the department of geography. “I was familiar with the NASA-funded EdGCM model from my previous tenure at NASA and felt that it was the ideal platform for integrating climate modeling in an accessible manner for today’s ‘digital native’ students,” said Shepherd. He will assist with implementation of EdGCM into the project’s instructional activities and provide climate science expertise.

    Although the NASA grant primarily funds instruction activities, the summer undergraduate research will offer undergraduate students the type of field research experience generally found only at the graduate level and will tie in with work Cooper is doing on breeding bird productivity along an elevational gradient at Coweeta. “The mountainside is a surrogate for climate change,” said Cooper, “and leafout and insect emergence will be later at higher elevations. Migrating birds that arrive in the spring to breed may be right on time to hit peak insect numbers at higher elevations, but not at lower sites, a phenomenon that is likely to be even more extreme with increasing global temperatures.”

    [Source: University of Georgia press release]

    Call for Papers: International Journal of Applied Geospatial Research

    In GIS, GIScience, Modeling, Science, Spatial Analysis on December 8, 2009 at 8:05 am

    The Editor-in-Chief of the >International Journal of Applied Geospatial Research (IJAGR) invites authors to submit manuscripts for consideration in this scholarly journal. The following describes the mission, coverage and guidelines for submission to IJAGR.

    The International Journal of Applied Geospatial Research (IJAGR) publishes research that exemplifies the usage of geographic information science and technology (GIS&T) to explore and resolve geographical issues from various application domains within the social and/or physical sciences. IJAGR is designed to provide planners and policy analysts, practitioners, academicians, and others using GIS&T useful studies that might support decision-making activities.

    IJAGR is interested in research highlighting various GIS&T application domains that span the social and physical sciences. Topics to be discussed in this journal include (but are not limited to) the following:

    • Biogeography
    • Business and marketing geography
    • Climatology
    • Economic geography
    • Geography of crime
    • Geomorphology
    • Historical geography
    • Medical geography
    • Military geography
    • Natural hazards
    • Political geography
    • Population geography
    • Soil geography
    • Tourism geography
    • Transportation geography
    • Other geographic subfields

    More information

    Analysis of Community-contributed Space-and Time-referenced Data (Example of Panoramio Photos)

    In GIS, Spatial Analysis, Temporal Analysis on December 7, 2009 at 9:06 am

    …from the Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems…

    “Space- and time-referenced data published on the Web by general people can be viewed in a dual way: as independent spatio-temporal events and as trajectories of people in the geographical space. These two views suppose different approaches to the analysis, which can yield different kinds of valuable knowledge about places and about people. We present several analysis methods corresponding to these two views. The methods are suited to the large amounts of the data.”

    Video: Hot Spot Analysis

    In ESRI, GIS, Spatial Analysis, Video on December 7, 2009 at 8:28 am

    The purpose of this video is to walk through a hot spot analysis, with a specific focus on choosing the right parameters for your analysis. Part 1 helps you choose a conceptualization of spatial relationships. Part 2 helps you choose an appropriate distance band by allowing your data to guide the process.

    Part 1: Choosing a Conceptualization of Spatial Relationships

    Part 2: Choosing an Appropriate Distance Band

    Part 3: Understanding Your Results

    Spatial Biodiversity Analyst-Phylogeographer: Post Doctoral Fellow at CSIRO, Canberra, Australia

    In Environmental Science, Spatial Analysis on December 7, 2009 at 8:27 am

    “The Centre for Plant Biodiversity Research requires a qualified, skilled and motivated scientist to research spatial biological information from the Australian National Herbarium together with phylogenetic data and environmental attributes (such as climate, terrain, soils) to map spatial patterns of biodiversity in environmental space.  The appointee will develop and test hypotheses relating to contemporary distribution of particular plant groups in relation to phylogenetic relationships as well as developing predictive approaches to conservation planning at regional and national scales.

    “The successful applicant will work in a team to develop and maintain standards for the capture, management, visualization, analysis and delivery of the spatial content in the organization’s databases, as well as to validate and maintain the spatial data quality. The successful applicant will further develop this team by leading collaborations among CSIRO Plant Industry, the Biodiversity Theme (BRABA) and non-CSIRO scientists throughout Australian and internationally.”

    Spatio-temporal Analysis of Alpine Ecotones: A Spatial Explicit Model Targeting Altitudinal Vegetation Shifts

    In Climate Change, Environmental Science, Spatial Analysis, Temporal Analysis on December 7, 2009 at 8:11 am

    …in Ecological Modelling, article in press…

    Ramón Alberto Díaz-Varela, Roberto Colombo, Michele Meroni, María Silvia Calvo-Iglesias, Armando Buffoni, and Antonio Tagliaferri

    “There is general agreement in literature that Alpine vegetation belt ecotones have shown a trend of upward migration in the last few decades. Despite the potential of such shifts as indicators of global change effects in mountain ecosystems, there are relatively few works focused on their assessment in a systematic and spatially explicit way. In this work our aim is to quantify the altitudinal shifts and analyse the spatial pattern dynamics of mountain ecotones. We developed a novel procedure to delineate the current and former state of three characteristic mountain ecotones, which we formalised as forest, tree and tundra lines. Our approach is based on the recognition of altitudinal extreme outposts identified with ecotone locations at a slope scale. The integration of multi-temporal datasets allows the identification and quantification of altitudinal advances and retreats in the outpost locations for a given period. We tested the method in a section of the Italian Alps for the period 1957–2003. Results show a general trend of an increase in altitude for the three ecotones, despite the occurrence of occasional decreases. We estimate decadal altitude increments of 25 m for forest line, 13 m for treeline and 11 m for tundra line. We also identified changes in ecotone spatial morphology between the two dates, with significant implications in connectivity and colonisation dynamics.”

    UTSA Research Sheds Light on Central Texas Geology and Climate Change

    In Climate Change, Education, Environmental Science, Spatial Analysis on December 3, 2009 at 9:32 am

    …from USTA Today…

    “Research projects by Stuart Birnbaum, University of Texas at San Antonio (UTSA) associate professor of geological sciences, and Daniel Lupton, a UTSA master’s student in geological sciences, reveal new information about Central Texas’ climate and water sources.

    “Birnbaum’s team researched the ancient climate preserved in the chemical signature of samples from Kimble County, Texas, by taking rock samples from a 12-meter cliff exposure of the Hensel paleosol, an ancient soil estimated to be approximately 112 million years old.”

    GIS and Cancer Research: A Bibliography

    In ESRI, GIS, Science, Social Science, Spatial Analysis, Temporal Analysis, Visualization on December 2, 2009 at 4:11 pm

    Bagli, S. 2001.  EHHRA-GIS: A DSS for Health Risk Assessment.  ESRI International User Conference Proceedings 2001.

    http://proceedings.esri.com/library/userconf/proc01/professional/abstracts/a542.html

    Balagopalan, M.  1999.  Communication of Health Risk Assessment by Integrating Geographic Information System (GIS) with Computer Dispersion Models.  ESRI International User Conference Proceedings 1999.

    http://proceedings.esri.com/library/userconf/proc99/proceed/PAPERS/PAP599/P599.HTM

    Battioui, C.  2005.  Calculation of Health Disparity Indices.  ESRI International User Conference Proceedings 2005.

    http://proceedings.esri.com/library/userconf/proc05/papers/pap2395.pdf

    Bellander, T., Berglind, N., Gustavsson, P., Jonson, T., Nyberg, F., Pershagen, G., and Järup, L.  2001.  Using Geographic Information Systems To Assess Individual Historical Exposure to Air Pollution from Traffic and House Heating in Stockholm.  Environmental Health Perspectives Volume 109, Number 6, June 2001.

    http://www.ehponline.org/realfiles/members/2001/109p633-639bellander/bellander-full.html

    Blewett, M.  2007.  Comparative Cluster Analysis for Establishing the Etiology of Multiple Sclerosis.  ESRI International User Conference Proceedings 2007.

    http://proceedings.esri.com/library/userconf/proc07/papers/abstracts/a1568.html

    Borchers, R.  2006.  From Cases to Cartography: Geocoding and Mapping Wisconsin Cancer Incidence Using Nuanced-Match Criteria.  ESRI International User Conference Proceedings 2006.

    http://proceedings.esri.com/library/userconf/proc06/papers/abstracts/a1320.html

    Brunton, H.  2005.  Extending ArcObjects for Statistical Cancer Analysis.  ESRI International User Conference Proceedings 2005.

    http://proceedings.esri.com/library/userconf/proc05/abstracts/a1543.html

    Carlin, S.  2001.  Community Breast Cancer Mapping–Huntington, Long Island.  ESRI International User Conference Proceedings 2001.

    http://proceedings.esri.com/library/userconf/proc01/professional/papers/pap496/p496.htm

    Carlin, S.  2001.  Community Breast Cancer Mapping–Huntington, Long Island.  ESRI Health Conference Proceedings 2001.

    http://proceedings.esri.com/library/userconf/health01/papers/hc01_p05c/hc01_p05c.html

    Colak, E.  2005.  Creating GIS-Based Cancer Density Maps for Trabzon Province of Turkey.  ESRI Health Conference Proceedings 2005.

    http://proceedings.esri.com/library/userconf/health05/docs/pap1014.pdf

    Colak, H., and Yomralioglu, T.  2008.  GIS Based Cancer Density Maps.  ESRI Health Conference Proceedings 2008.

    http://proceedings.esri.com/library/userconf/health08/docs/monday/gis_cancer_maps.pdf

    Cowper, D.  2000.  Using GIS to Examine Physician Practice Patterns in the Department of Veterans Affairs (VA) Health Care System: Examples of Two Cancer Procedures.  ESRI International User Conference Proceedings 2000.

    http://proceedings.esri.com/library/userconf/proc00/professional/papers/PAP219/p219.htm

    ESRI.  2006.  Mapping Papilloma Virus Disease Data Contributes to Cancer Risk Assessments: Using GIS Technology to Track Virus Prevalence.  ArcNews Fall 2006.

    http://www.esri.com/news/arcnews/fall06articles/mapping-papilloma.html

    Files, J., and Balamurugan, A.  2007.  Using ArcGIS/SaTScan to Detect Higher than Expected Cancer Incidence.  ESRI International User Conference Proceedings 2007.

    http://proceedings.esri.com/library/userconf/proc07/papers/abstracts/a1269.html

    Foster, S., Stewart,  S., and Trivers, K.  2008.  Geographic Distribution of Prostate Cancer Incidence in the United States .  ESRI Health Conference Proceedings 2008.

    http://proceedings.esri.com/library/userconf/health08/docs/monday/geo_dist.pdf

    Francois, T.  2009.  Racial Disparities in Breast Cancer Mortality in Chicago.  2009 ESRI Health GIS Conference Proceedings.

    http://proceedings.esri.com/library/userconf/health09/docs/tuesday/racial_disparities_in_breast_cancer_mortality_in_chicago.pdf

    Gardner, J.  2000.  Breast Cancer Research Using GIS, Phase 2.  ESRI International User Conference Proceedings 2000.

    http://proceedings.esri.com/library/userconf/proc00/professional/abstracts/a145.htm

    Garland, C.  2004.  Analyzing Head and Neck Cancer Incidence and Mortality Using GIS.  ESRI International User Conference Proceedings 2004.

    http://proceedings.esri.com/library/userconf/proc04/docs/pap1691.pdf

    Gorham, E., Mohr, S., Garland, F., Garland, C., Grant, W., and Highfill-McRoy, R.  2005.  World Atlas of Ultraviolet A and B Radiation.  ESRI International User Conference Proceedings 2005.

    http://proceedings.esri.com/library/userconf/proc05/papers/pap1778.pdf

    Graham, P.2009.  Using ArcGIS Server 9.3 to Power the Maine BioGeoBank.  ESRI International User Conference Proceedings 2009.

    http://proceedings.esri.com/library/userconf/proc09/uc/abstracts/a1576.html

    Hansen, K.  2007.  Rural-Urban Differences in Stage at Diagnosis and Treatment of Colorectal Cancer in Nebraska .  ESRI Health Conference Proceedings 2007.

    http://proceedings.esri.com/library/userconf/health07/docs/rural-urban.pdf

    Horner, M., Stinchcomb, D., Zao, J., and Cuccinelli, J.  2008.  Geography of Cervical Cancer: Baseline for HPV Vaccine Effectiveness .  ESRI Health Conference Proceedings 2008.

    http://proceedings.esri.com/library/userconf/health08/docs/tuesday/geography_cervical_cancer.pdf

    Kennedy, T.  2003.  Modeling Historical Environmental Exposures Using GIS: Implications for Disease Surveillance.  ESRI Health Conference Proceedings 2003.

    http://proceedings.esri.com/library/userconf/health03/papers/pap3020/p3020.htm

    Krenz, E., Krenz, V., Pinzon-Perez, H., Perez, M., and Hougan, P.  2003.  Barriers to Pap Smears Among Latina MediCal Enrollees Using GIS.  ESRI International User Conference Proceedings 2003.

    http://proceedings.esri.com/library/userconf/proc03/abstracts/a1044.pdf

    Lai, S., Shen, Z., and Banks, D. 2006.  Inclusion of Non-Street Addresses in Cancer Cluster Analysis.  ESRI Health Conference Proceedings 2006.

    http://proceedings.esri.com/library/userconf/health06/docs/cancer_cluster.pdf

    Lang, L.  2000.  Finding the link.  In:  GIS for Health Organizations .

    http://esripress.esri.com/display/index.cfm?fuseaction=display&websiteID=39&moduleID=0

    Ma, M. 2007.  Using GIS in Cancer Cluster Investigation.  ESRI Health Conference Proceedings 2007.

    http://proceedings.esri.com/library/userconf/health07/docs/using_gis_in_cancer.pdf

    MacKinnon, J. 2007.  Detecting an Association between Socioeconomic Status and Late Stage Breast Cancer Using Spatial Analysis and Area-Based Measures.  ESRI Health Conference Proceedings 2007.

    http://proceedings.esri.com/library/userconf/health07/docs/detecting_an_association.pdf

    Massaro, M., and Lee, C.  1999.  The Landscape of Breast Cancer in Georgia.  ESRI International User Conference Proceedings 1999.

    http://proceedings.esri.com/library/userconf/proc99/proceed/abstracts/a626.htm

    McCall Garb, J., Schueler, J., Flannery, C., Pasini, A., and Wait, R.  2001.  Using the American Community Survey and GIS in Breast Cancer Screening.  ESRI International User Conference Proceedings 2001.

    http://proceedings.esri.com/library/userconf/proc01/professional/abstracts/a1045.html

    McCormick, J.  2000.  Sampling Design Issues in Identifying Breast Cancer Sufferers.  ESRI International User Conference Proceedings 2000.

    http://proceedings.esri.com/library/userconf/proc00/professional/papers/PAP949/p949.htm

    Mohr, S., Gorham, E., Garland, F., Garland, C., Grant, W., and Highfill-McRoy, R.  2005.  Mapping Vitamin D Deficiency and Breast and Colon Cancers.  ESRI International User Conference Proceedings 2005.

    http://proceedings.esri.com/library/userconf/proc05/papers/pap1468.pdf

    Oliver, M.  2007.  GIS used to Analyze Race and Socioecomomic Status in Prostate Cancer Incidence in the Southeastern United States .  ESRI Health Conference Proceedings 2007.

    http://proceedings.esri.com/library/userconf/health07/docs/gis_used_to_analyze.pdf

    Qui, F.  2003.  Spatial Pattern and Causation Analysis of Childhood Cancer in Texas.  ESRI International User Conference Proceedings 2003.

    http://proceedings.esri.com/library/userconf/proc03/abstracts/a0842.pdf

    Ramroop, S.  2008.  GIS for Community Food Access and its Relationship to Cancer.  ESRI International User Conference Proceedings 2008.

    http://proceedings.esri.com/library/userconf/proc08/papers/papers/pap_1411.pdf

    Shepard, J., and Shepard, W.  2002.  The Role of Geostatistical Tools in the Analysis and Visualization of Epidemiological Data.  ESRI International User Conference Proceedings 2002.

    http://proceedings.esri.com/library/userconf/proc02/abstracts/a0938.html

    Stinchcomb, D. 2007.  Extensions useful for examining geographic patterns of health data.  ESRI Federal User Conference Proceedings 2007.

    http://proceedings.esri.com/library/userconf/feduc07/presentations/1073_nci_geographic_health_data_january_2007.pdf

    Thorpe, N.  2003.  Childhood Cancer in Maryland: A Geographic Information Systems Approach.  ESRI Health Conference Proceedings 2003.

    http://proceedings.esri.com/library/userconf/health03/papers/pap3006/p3006.htm

    Wells, K. 2009.  Residential Segregation and Prostate Cancer Post- Diagnosis Treatment Decisions.  2009 ESRI Health GIS Conference Proceedings.

    http://proceedings.esri.com/library/userconf/health09/docs/tuesday/residential_segregation_and_prostate_cancer_postdiagnosis_treatment_decisions.pdf

    Williams Pickle, L., Heineman, E., Ward, M., Nuckols, J., Gumpertz, M., and Bell, B.  2001.  Applications of GIS to cancer research at the National Cancer Institute.  ESRI Health Conference Proceedings 2001.

    http://proceedings.esri.com/library/userconf/health01/papers/hc01_p01a/hc01_p01a.html

    Geospatial Analysis of Rural Motor Vehicle Traffic Fatalities

    In Spatial Analysis on December 2, 2009 at 2:27 pm

    …a new report from the National Highway Transportation Safety Administration…

    “In recent years, on average about 44 percent of traffic fatalities occurred in urban areas. NHTSA’s Fatality Analysis Reporting System (FARS) codes the functional classification of land use by a binary indicator, i.e., if the location is a rural or urban area, as defined by the United States Census Bureau. However, this information is not enough to determine the spatial spread of the fatali-ties in the rural areas, i.e., are the fatalities occurring in suburban, exurban, or the outlying rural areas. The focus of this report is to determine the extent of fatalities that occur in rural areas that are close to urban areas. Some of these communities in rural areas that are close to urban areas have significant commuting ties with these urban areas. It would be of interest to law enforcement and highway safety planners involved in rural highway safety initiatives to quantify how many traffic fatalities occur in rural areas that are close to urban areas.

    “FARS has begun reporting latitude and longitude information recently that facilitates the type of geospatial analysis required to quantify fatalities that occur near urban areas as a function of distance from the urban boundaries. The distances (buffer distances) used in this spatial analysis are 2.5, 5.0, 7.5, and 10.0 miles.

    “While 44 percent of all traffic fatalities occur in urban areas, the percentage increases to 63 percent in an area that also includes the rural area within 2.5 miles of the urban boundary. The percentage increases to 73 percent 5.0 miles out, 81 percent 7.5 miles out, and 86 percent 10 miles out. In summary, about three-quarters of all traffic fatalities in the Nation occurred in an area that includes all the urban areas along with the rural areas that are within 5 miles of the urban boundaries.”

    Spatial and Temporal Analysis of Tornado Fatalities in the United States: 1880–2005

    In Spatial Analysis on December 1, 2009 at 8:29 am

    …from Weather and Forecasting, Volume 22…

    Walker S. Ashley

    “A dataset of killer tornadoes is compiled and analyzed spatially in order to assess region-specific vulnerabilities in the United States from 1880 to 2005. Results reveal that most tornado fatalities occur in the lower–Arkansas, Tennessee, and lower–Mississippi River valleys of the southeastern United States—a region outside of traditional “tornado alley.” Analysis of variables including tornado frequency, land cover, mobile home density, population density, and nocturnal tornado probabilities demonstrates that the relative maximum of fatalities in the Deep South and minimum in the Great Plains may be due to the unique juxtaposition of both physical and social vulnerabilities. The spatial distribution of these killer tornadoes suggests that the above the national average mobile home density in the Southeast may be a key reason for the fatality maximum found in this area. A demographic analysis of fatalities during the latter part of the database record illustrates that the middle aged and elderly are at a much greater risk than are younger people during these events. Data issues discovered during this investigation reveal the need for a concerted effort to obtain critical information about how and where all casualties occur during future tornado and hazardous weather events. These new, enhanced data, combined with results of spatially explicit studies exploring the human sociology and psychology of these hazardous events, could be utilized to improve future warning dissemination and mitigation techniques.”

    SDI Job Opportunities: Two Post-Doc Research Positions

    In Environmental Science, GIS, SDI, Spatial Analysis, Temporal Analysis, Visualization on December 1, 2009 at 7:35 am

    The European Commission Joint Research Center (JRC) Institute for Environment and Sustainability has two vacancies for Post-Doc Researchers:

    Spatial and Temporal Analysis of Integrated Quantitative and Qualitative Information

    The Grantholder will work in an exploratory research project which aims to demonstrate how information volunteered by the public can be quality controlled and used to complement official sources in the context of forest fires.

    The project has four objectives:

    1. To develop, test, and deploy workflows able to quality control volunteered geographic information.
    2. To assess the value of volunteered geographic information in supporting both early warning, and local impact assessments of forest fires.
    3. To develop novel analytical and visualization techniques to communicate more effectively to the general public the concepts of risk.
    4. To advance spatial and temporal analysis of integrated quantitative and qualitative information.

    The Grantholder will work in a team and contribute specifically to Objective 4 above. The ideal candidate has a PhD in geographic information science, environmental or social science, (or a university degree in these disciplines and 5 years research experience after the university degree giving access to doctoral studies).

    Practical experience in spatio-temporal analysis is required as well as a good knowledge of spoken and written English.

    Risk Mapping and Visualisation of Fuzzy Concepts

    The Grantholder will work in an exploratory research project which aims to demonstrate how information volunteered by the public can be quality controlled and used to complement official sources in the context of forest fires.

    The project has four objectives:

    1. To develop, test, and deploy workflows able to quality control volunteered geographic information.
    2. To assess the value of volunteered geographic information in supporting both early warning, and local impact assessments of forest fires.
    3. To develop novel analytical and visualization techniques to communicate more effectively to the general public the concepts of risk.
    4. To advance spatial and temporal analysis of integrated quantitative and qualitative information.

    The Grant Holder will work in a team and contribute specifically to Objective 3 above.

    The ideal candidate has a PhD in geographic information science, computer science or engineering, (or a university degree in these disciplines and 5 years research experience after the university degree giving access to doctoral studies).

    Practical experience in the analysis and visualization of fuzzy concepts like risk is required as well as a good knowledge of spoken and written English.

    The deadline for receipt of applications is 15th December 2009 at 12:00 a.m. Milan time

    Tool Kits in Regional Science: Theory, Models, and Estimation

    In Books, Geography, Modeling, Spatial Analysis on November 30, 2009 at 7:30 am

    “Regional Science is now more than 50 years old; in the last two decades, significant advances in methodology have occurred, spurred in large part by access to computers. The range of analytical techniques now available is enormous; this books provides a sampling of the toolkit that is now at the disposal of analysts interested in understanding and interpreting the complexity of the spatial structure of sub- national economies. The set of tools ranges from the more traditional (input-output) to new developments in computable general equilibrium models, nonlinear dynamics, neural modelling and innovation.”

    Quote of the Day

    In ESRI, GIS, Modeling, Quotes, Science, Spatial Analysis on November 25, 2009 at 7:09 am

    “The analysis is only as good as the model.”

    –David Buckley

    Demonstration of Ecosystem Management Decision Support (EMDS) 4.0

    In ESRI, Environmental Science, GIS, Spatial Analysis, Video on November 20, 2009 at 7:26 am

    From The Redlands Institute at the University of Redlands, a demonstration of Ecosystem Management Decision Support (EMDS) version 4.0.

    Complexity and Spatial Networks: In Search of Simplicity

    In Books, GIScience, Modeling, Spatial Analysis on November 19, 2009 at 7:30 am

    “This book offers a panoramic view of recent advances in spatial complexity, in order to enhance our understanding of complex spatial networks by simplicity in terms of both the basic driving forces of systemic impacts and the modelling of such systems. Simple models mapping out the evolution of complex networks are undoubtedly a key issue in spatial economic research. In exploring this untrodden ground, this volume pursues new interdisciplinary pathways for theoretical, methodological and empirical analysis in the complex interconnected space-economy. It highlights ‘evolutionary’ directions and ‘unifying’ perspectives in this fascinating research field.”

    Bird Migration Model: Agent Analyst/Tracking Analyst Integration

    In ESRI, Environmental Science, GIS, Spatial Analysis, Video on November 19, 2009 at 7:18 am

    This video capture to demonstrates the integration of Agent Analyst and Tracking Analyst within ArcGIS Desktop. The model shown–a simulation of bird migration patterns of two species–was developed to learn and demonstrate concepts of Agent Based Modeling within GIS using the Agent Analyst toolkit developed by Argonne National Laboratory.

    GIS Reveals Extent of Early Hawaiian Agricultural Systems

    In GIS, Modeling, Social Science, Spatial Analysis on November 17, 2009 at 9:27 am

    …from The Nature Conservancy…

    “Early Hawaiian agriculture was far more extensive and complex than anyone has fully understood, according to new research by scientists blending state-of-the-art technologies with traditional dirt archaeology.

    “Until now, it has been difficult to prove the full scope of Hawaiian farming technology, said Samuel M. Gon III, ecologist, cultural advisor and senior scientist with The Nature Conservancy. “At the peak of Hawaiian population, there were perhaps a million people. It takes thousands and thousands of acres to feed all those people,” Gon said. Where was all that farmland?

    “A new research tool has now identified thousands of farmed acres not previously known to science—including a vast dry-land agricultural field system in the grassy plains of Ka‘ū on the Big Island.”

    Spatial Modeling of Invasive Plant Spread on Roads and River Networks in Alaska

    In Environmental Science, Modeling, Spatial Analysis on November 17, 2009 at 8:13 am

    …from the Western Wildland Environment Threat Assessment Center, US Forest Service…

    “Most of Alaska’s invasive plants are found only along the state’s limited road system, and Melilotus alba is one of the most widely distributed invasives in the state. Recently, Melilotus has been found to have moved from roadsides to the flood plains of at least three glacial rivers. In one of these cases, Melilotus has become a major component of the flood plain vegetation of the lower Stikine River in southeast Alaska, within the Stikine-LeConte Wilderness. The presence of Melilotus on the lower Stikine River points out the vulnerability of roadless public lands in Alaska to invaders dispersing via linked road-and-river networks. Because more and more noxious species are turning up in Alaska each year, and because they are also spreading along the roadsides, it is likely that other species will follow the roads-to-rivers route that Melilotus has taken. The objective of this project is to develop a simulation model of the potential spread of an invasive plant along roads and river networks in Alaska. The model will allow us to predict the rate of spread, and the number of years until an invasive plant will reach different roadless public conservation units. It will identify certain road-river interfaces and crossings as critical control points for certain public lands conservation units. This information will provide a means of prioritizing and evaluating the effectiveness of different management responses to invasive species in Alaska. The model will highlight which public lands are most vulnerable to invasion via linked road and river networks, as well as showing which lands are least vulnerable. We will be able to use the model to test hypotheses concerning climate change and changing flood regimes, for a variety of management actions and for a variety of invasive species. Initial model development will focus on a 10,000 km2 study area (100 by 100 km) comprising the rivers and roads upstream of the Kanuti National Wildlife Refuge (NWR), north of Fairbanks. This area is bounded on the east by the Dalton Highway, and on the west by the western boundary of the wildlife refuge. Kanuti NWR is entirely located in National Hydrography Data set subregion 1904, and although it has no direct road access, there are 13 major and 112 minor crossings upstream of the refuge, all on the Dalton Highway. When the model is functioning properly on this relatively small test area, we’ll expand it to larger extents, with the goal of scaling the model up to the full extent of interior and south-central Alaska.”

    Research Botanist Position at NatureServe in Arlington, Virginia

    In Environmental Science, GIS, Spatial Analysis on November 13, 2009 at 8:34 am

    natureserveThis is an exciting opportunity with the possibility of advancement for a botanically-inclined conservation biologist to join an international environmental organization and make a positive impact on pressing environmental issues. Initially this will be a part-time position with the possibility of becoming full-time in the fall of 2010. The position is based in our office in Arlington, VA, within a convenient walk of the Rosslyn Metro Station.

    The research botanist develops, reviews, and revises information relating to the conservation status of native plant species, primarily rare species, throughout the United States and Canada. Much of the work centers on compiling data on geographical distribution, abundance, threats, trends, habitat requirements, natural history, and management needs, followed by application of NatureServe criteria to synthesize this information into a standardized estimate of conservation status. The position requires extensive communication with state, federal, academic, and independent botanists, as well as searching and synthesis of published scientific literature. The position is project oriented, with some projects directed to meeting specific data needs of U.S. federal land-management agencies and other work, including data review and taxonomic reconciliation, supporting the information needs of state natural heritage programs/conservation data centers or other clients. The research botanist also provides botanical expertise for the development of NatureServe methodology and assists in using NatureServe botanical data to address conservation problems such as alterations in land use patterns and climate change. S/he often works on a tight schedule to meet deadlines, and helps write proposals and supervises interns.

    Preferred Skills include a working knowledge of GIS, including basic spatial analysis skills.

    You’re Being Followed: Scientists Track Movement of Living Things

    In Geography, Science, Spatial Analysis, Temporal Analysis on November 13, 2009 at 8:23 am

    …from KansasCity.com…

    “Almost 24 centuries after the Greek philosopher Aristotle wrote his book, “On the Movement of Animals,” modern scientists are still struggling to understand how, why, when and where living creatures move.

    “Whether an organism drifts in the sea, swims, wriggles, crawls, walks, runs, jumps, flies or casts its seeds upon the wind, movement is essential to life, they say. No matter how big or little it is, it’s got to get away from its birthplace to find food, escape predators and reproduce.”

    Rainfall Redistribution in a Tropical Forest: Spatial and Temporal Patterns

    In Environmental Science, Geography, Spatial Analysis, Temporal Analysis on November 11, 2009 at 7:00 am

    …from the Water Resources Research journal…

    Alexander Zimmermann, Institute of Geoecology, University of Potsdam, Potsdam, Germany

    Beate Zimmermann, Smithsonian Tropical Research Institute, Balboa, Ancón, Panama

    Helmut Elsenbeer, Institute of Geoecology, University of Potsdam, Potsdam, Germany; Smithsonian Tropical Research Institute, Balboa, Ancón, Panama

    “The investigation of throughfall patterns has received considerable interest over the last decades. And yet, the geographical bias of pertinent previous studies and their methodologies and approaches to data analysis cast a doubt on the general validity of claims regarding spatial and temporal patterns of throughfall. We employed 220 collectors in a 1-ha plot of semideciduous tropical rain forest in Panama and sampled throughfall during a period of 14 months. Our analysis of spatial patterns is based on 60 data sets, whereas the temporal analysis comprises 91 events. Both data sets show skewed frequency distributions. When skewness arises from large outliers, the classical, nonrobust variogram estimator overestimates the sill variance and, in some cases, even induces spurious autocorrelation structures. In these situations, robust variogram estimation techniques offer a solution. Throughfall in our plot typically displayed no or only weak spatial autocorrelations. In contrast, temporal correlations were strong, that is, wet and dry locations persisted over consecutive wet seasons. Interestingly, seasonality and hence deciduousness had no influence on spatial and temporal patterns. We argue that if throughfall patterns are to have any explanatory power with respect to patterns of near-surface processes, data analytical artifacts must be ruled out lest spurious correlation be confounded with causality; furthermore, temporal stability over the domain of interest is essential.”

    Spatial Analysis of Routes and Work Schedules Saves City of Fort Collins Almost $1 Million Annually

    In ESRI, GIS, Spatial Analysis, Video on November 5, 2009 at 8:39 am

    Learn how building inspectors from the City of Ft. Collins, TX, used ArcLogistics to optimize routes and work schedules to realize savings of almost $1 million annually. Recorded at the 2008 ESRI International User Conference.

    Ecosystem Management Decision Support System

    In ESRI, Environmental Science, GIS, Spatial Analysis on November 4, 2009 at 6:19 am

    emdsThe Ecosystem Management Decision Support (EMDS) System is an application framework for knowledge-based decision support of ecological assessments at any geographic scale.  EMDS integrates state-of-the-art GIS as well as knowledge-based reasoning and decision modeling technologies in the Microsoft Windows environment to provide decision support for a substantial portion of the adaptive management process of ecosystem management.  EMDS is built and maintained by a consortium consisting of the U.S. Forest Service, InfoHarvest, Rules of Thumb, and The Redlands Institute (University of Redlands).

    Adaptive Classification Using Self Organizing Maps

    In GIS, GIScience, Spatial Analysis on November 3, 2009 at 8:13 am

    v1…from V1 Magazine…

    “As humans, we have an innate and natural tendency to establish patterns and associations in our environment. Consider for a moment, the capability of the human brain to “process millions of visual, acoustic, olfactory, tactile, and motor data, and…the astonishing ability to learn from experience, generalize from learned rules, recognize patterns, and make decisions”. The ability to recognize patterns allows us to distinguish objects one from another; to interpret sound waves as speech; and to understand the unique patterns of individual letters that collate to form words and sentences.

    “These skills provide meaning, knowledge, and experience to the observer. It is difficult to mimic this type of pattern recognition and establishment of data relationships in a computational context.

    “In other words, how do you train a computer to evaluate disparate datasets in order to recognize the difference between desert and forest conditions or understand the type of complex relationships that the human mind can resolve after many years of experience?”

    A Scan Statistic for Continuous Data Based on the Normal Probability Model

    In Geography, Spatial Analysis, Statistics, Temporal Analysis on November 3, 2009 at 7:30 am

    International Journal of Health Geographics 2009, 8:58

    Martin Kulldorff, Lan Huang, Kevin Konty

    Temporal, spatial and space-time scan statistics are commonly used to detect and evaluate the statistical significance of temporal and/or geographical disease clusters, without any prior assumptions on the location, time period or size of those clusters. Scan statistics are mostly used for count data, such as disease incidence or mortality. Sometimes there is an interest in looking for clusters with respect to a continuous variable, such as lead levels in children or low birth weight. For such continuous data, we present a scan statistic where the likelihood is calculated using the the normal probability model. It may also be used for other distributions, while still maintaining the correct alpha level. In an application of the new method, we look for geographical clusters of low birth weight in New York City.

    A New Method for Fingerprint Analysis: Researchers Apply Geographic Principles to Improve Matches

    In GIS, Geography, Spatial Analysis on November 2, 2009 at 3:55 pm

    …from StatesmanJournal.com…

    “”One of the unique things of this project is there are probability-based models out there for fingerprint analysis,” Dutton said. “The difference of what we’re doing is applying a geographical information system to perform the spatial analysis.”

    “Spatial analysis is the study of distribution of features in a fingerprint, Dutton said.”

    Lessons from Oil Industry May Help Address Groundwater Crisis

    In Environmental Science, Geography, Spatial Analysis on October 30, 2009 at 10:10 am
    oregon

    Declining groundwater in Mississippi has prompted a $1 billion lawsuit against Memphis.

    Although declining streamflows and half-full reservoirs have gotten most of the attention in water conflicts around the United States, some of the worst battles of the next century may be over groundwater, experts say – a critical resource often taken for granted until it begins to run out.

    Aquifers are being depleted much faster than they are being replenished in many places, wells are drying up, massive lawsuits are already erupting and the problems have barely begun. Aquifers that took thousands of years to fill are being drained in decades, placing both agricultural and urban uses in peril. Groundwater that supplies drinking water for half the world’s population is now in jeopardy.

    A new analysis by researchers at Oregon State University outlines the scope of this problem, but also points out that some tools may be available to help address it, in part by borrowing heavily from lessons learned the hard way by the oil industry.

    “It’s been said that groundwater is the oil of this century,” said Todd Jarvis, associate director of the Institute for Water and Watersheds at OSU. “Part of the issue is it’s running out, meaning we’re now facing ‘peak water’ just the way the U.S. encountered ‘peak oil’ production in the 1970s. But there are also some techniques developed by the oil industry to help manage this crisis, and we could learn a lot from them.”

    Jarvis just presented an outline of some of these concepts, called “unitization,” at a professional conference in Kyoto, Japan, and will also explore them in upcoming conference in Stevenson, Wash., and Xi’an, China. Other aspects of the issue have been analyzed in a new documentary film on the special problems facing the Umatilla Basin of eastern Oregon, a classic case of declining groundwater problems. (DVD copies of the documentary are available free upon request, by calling 541-737-4032.)

    The problems are anything but simple, Jarvis said, and are just now starting to get the attention needed.

    “In the northern half of Oregon from Pendleton to the Willamette Valley, an aquifer that took 20,000 years to fill is going down fast,” Jarvis said. “Some places near Hermiston have seen water levels drop as much as 500 feet in the past 50-60 years, one of the largest and fastest declines in the world.

    “I know of a well in Utah that lost its original capacity after a couple years,” he said. “In Idaho people drawing groundwater are being ordered to work with other holders of stream water rights as the streams begin to dwindle. Mississippi has filed a $1-billion lawsuit against the City of Memphis because of declining groundwater. You’re seeing land subsiding from Houston to the Imperial Valley of California. This issue is real and getting worse.”

    In the process, Jarvis said, underground aquifers can be irrevocably damaged – not unlike what happened to oil reservoirs when that industry pumped them too rapidly. Tiny fractures in rock that can store water sometimes collapse when it’s rapidly withdrawn, and then even if the aquifer had water to recharge it, there’s no place for it to go.

    “The unitization concept the oil industry developed is built around people unifying their rights and their goals, and working cooperatively to make a resource last as long as possible and not damaging it,” Jarvis said. “That’s similar to what we could do with groundwater, although it takes foresight and cooperation.”

    Water laws, Jarvis said, are often part of the problem instead of the solution. A “rule of capture” that dates to Roman times often gives people the right to pump and use anything beneath their land, whether it’s oil or water. That’s somewhat addressed by the “first in time, first in right” concept that forms the basis of most water law in the West, but proving that someone’s well many miles away interferes with your aquifer or stream flow is often difficult or impossible. And there are 14 million wells just in the United States, tapping aquifers that routinely cross state and even national boundaries.

    Regardless of what else takes place, Jarvis said, groundwater users must embrace one concept the oil industry learned years ago – the “race to the pump” serves no one’s best interest, whether the concern is depleted resources, rising costs of pumping or damaged aquifers.

    One possible way out of the conundrum, experts say, is maximizing the economic value of the water and using it for its highest value purpose. But even that will take new perspectives and levels of cooperation that have not often been evident in these disputes. Government mandates may be necessary if some of the “unitization” concepts are to be implemented. Existing boundaries may need to be blurred, and ways to share the value of the remaining water identified.

    “Like we did with peak oil, everyone knows were running out, and yet we’re just now getting more commitment to alternative energy sources,” Jarvis said. “Soon we’ll be facing peak water, the only thing to really argue over is the date when that happens. So we will need new solutions, one way or the other.”

    [Source: Oregon State University news release]

    The Washington Times: Geographic Awareness Needed

    In GIS, Geography, Spatial Analysis on October 29, 2009 at 7:45 am

    TWTlogo…from The Washington Times…

    “For decades, geographers have noted that the key to better planning for wars, disasters, climate shifts or any other major force of change is a broader understanding of their spatial dimensions. They also have demonstrated time after time that a lack of geographic awareness about the peoples and places affected by war, natural and other disasters often exacerbates the misery and compounds the challenges to effective recovery. New technologies such as geographic information and global positioning systems can help build awareness about changing environments, and they can provide the foundation upon which meaningful spatial analysis, and thus appropriate policy, is created.”

    Global Tree Death Patterns Reveal Emerging Climate Change Risks for Forests

    In Climate Change, Environmental Science, Spatial Analysis on October 26, 2009 at 5:31 pm

    Recent tree loss, largely driven by climate stress, in forests around the world could portend increased tree mortality under climate change, according to a U.S. Geological Survey (USGS) report recently released online in the journal Forest Ecology and Management.

    The USGS-led review suggests that many of the world’s forests are sensitive to climate-related drought and heat stress, raising the concern that forests may become increasingly vulnerable to future mortality, even in environments that are not normally considered water-limited. The results suggest risks to ecosystem services that are valuable to forests and societies around the world.

    “Trees can die much more quickly than they grow,” said Craig D. Allen, USGS scientist and lead author of the report. “The widespread examples of drought and heat-induced tree mortality that we document illustrate how climate can drive abrupt, broad-scale impacts to essential forest services ranging from timber and protection of watersheds and biodiversity to recreational, aesthetic and spiritual benefits.”

    Although tree mortality episodes occur in the absence of climate change, the report’s results are consistent with projections of future increases in tree mortality due to climate-related stresses. These heat and drought stresses could fundamentally alter the composition, structure and biogeography of forests in many regions, as well as affect how forests sequester carbon.

    “This work by USGS underscores multiple risks that climate change poses to our forests and our world,” said Secretary of the Interior Ken Salazar.  “It also illuminates the importance of our efforts to develop practical, on-the-ground land management strategies that will help us adjust to the stresses that climate change is placing on our forests.”

    The report details 88 cases of significant tree mortality around the world associated with heat and drought since 1970, documenting climate-induced tree losses from Africa, Asia, Australia, Europe, North America and South America.

    “From northern forests of spruce, pine or oak to tropical savannas and rainforests, many forest types appear vulnerable to such climate-driven mortality and to forest pests that are also highly sensitive to temperature,” Allen said.

    The report also identifies key information gaps and scientific uncertainties that currently hinder our ability to identify climate-related trends in tree mortality and to predict future losses in response to climate change, including lack of species-specific knowledge about tree water and temperature stress limits and the absence of a globally coordinated observation system.

    However, in conjunction with other recent observational and experimental studies indicating that higher temperatures can drive increases in tree mortality, this article highlights risks that tree mortality could become more frequent and extensive as global climate change progresses.

    [Source: USGS news release]

    Call for Participation: Space-Time Modeling and Analysis Workshop

    In ESRI, GIS, Science, Spatial Analysis, Temporal Analysis on October 22, 2009 at 7:21 am

    Scientists to Gather for Inaugural Redlands GIS Week in February 2010

    Scientists working on understanding the integration of space and time will gather in California February 22–23, 2010, to attend the Space-Time Modeling and Analysis Workshop. The workshop will be part of the first Redlands GIS Week—a gathering of thought leaders from academia, government, and industry to advance the science and application of geospatial technologies. The remainder of Redlands GIS Week 2010 will be dedicated to informal networking activities, demonstrations, and technical tours.

    The Space-Time Modeling and Analysis Workshop will feature keynote presentations, lightning talks, and small group discussions, as well as opportunities for informal brainstorming with leading geospatial thinkers and implementers.  Researchers are invited to submit 500-word abstracts describing the work that they would present as either a keynote or lightning (focused 10-minute) talk. Preference will be given to abstracts describing concrete results to concrete problems, and software demonstrations are encouraged.

    Redlands GIS Week will be held at ESRI’s headquarters as well as nearby sites in Redlands, California. The event is cosponsored by the University of Southern California, ESRI, the Association of American Geographers (AAG), and the University of Redlands. After the workshop, a publication will share the event’s results with a larger audience.

    For more information and to view the Call for Participation, visit www.redlandsgisweek.org.

    [Source: ESRI news release]

    Spatial Trends of Breast and Prostate Cancers in the United States, 2000 and 2005

    In GIS, Geography, Science, Spatial Analysis, Statistics on October 21, 2009 at 6:31 am

    …from the International Journal of Health Geographics 2009, 8:53…

    Rakesh Mandal, Sophie St-Hilaire, John G Kie, DeWayne Derryberry

    “Background

    “Breast cancer in females and prostate cancer in males are two of the most common cancers in the United States, and the literature suggests that they share similar features. However, it is unknown whether the occurrence of these two cancers at the county level in the United States is correlated. We analyzed Caucasian age-adjusted county level average annual incidence rates for breast and prostate cancers from the National Cancer Institute and State Cancer Registries to determine whether there was a spatial correlation between the two conditions and whether the two cancers had similar spatial patterns.

    “Results

    “There was a significant correlation between breast and prostate cancers by county (r =0.332, p<0.001). This relationship was more pronounced when we performed a geographically- weighted regression (GWR) analysis (r =0.552) adjusting for county unemployment rates. There was variation in the parameter estimates derived with the GWR; however, the majority of the estimates indicted a positive association. The strongest relationship between breast and prostate cancers was in the eastern parts of the Midwest and South, and the Southeastern U.S. We also observed a north-south pattern for both cancers with our cluster analyses. Clusters of counties with high cancer incidence rates were more frequently found in the North and clusters of counties with low incidence rates were predominantly in the South.

    “Conclusion

    “Our analyses suggest breast and prostate cancers cluster spatially. This finding corroborates other studies that have found these two cancers share similar risk factors. The north-south distribution observed for both cancers warrants further research to determine what is driving this spatial pattern.”

    Spatial Analysis of Social Facts: A Tentative Theoretical Framework

    In Geography, Social Science, Spatial Analysis, Temporal Analysis on October 21, 2009 at 6:28 am

    …manuscript published in “Handbook of Quantitative and Theoretical Geography or Advances in Quantitative and Theoretical Geography (2010) 000-046″…

    Author: C. Grasland, Université Paris Diderot

    “This document presents an attempt to build a theoretical framework for the spatial analysis of social facts, derived from Tobler’s first law of geography (‘Everything is related to everything else, but near things are more related than distant things’) and Blau’s theory of macro sociology and multilevel structural analysis. At individual level four basic times of position and interaction are defined (geographical/sociological and discrete/continuous). It is then necessary to discuss the effects of scale aggregation and time dynamics on the elementary levels of position and interaction. This part is illustrated by examples about airflows between world cities in 2000 and euro coins diffusion across borders between 2002 and 2007.”

    College of William and Mary Professor Receives National Science Foundation Grant

    In Education, GIS, Social Science, Spatial Analysis on October 20, 2009 at 11:07 am

    …from The Flat Hat…

    “College of William and Mary Associate Professor of sociology Salvatore Saporito recently received a $1 million grant from the National Science Foundation to create a database of school attendance boundaries for the country’s largest school districts.

    “The database, called the School Attendance Boundary Information System, will receive two years of funding from the grant. Saporito and his team of student researchers are working closely with Stuart Hamilton, program director for the Center for Geospatial Analysis, to map out school boundaries for hundreds of school districts in the U.S. using Geographic Information Systems, a digital mapping system.”

    Variable Selection for Spatial Random Field Predictors Under a Bayesian Mixed Hierarchical Spatial Model

    In Geography, Modeling, Science, Spatial Analysis, Statistics on October 20, 2009 at 6:04 am

    719813…in Spatial and Spatio-Temporal Epidemiology, Volume 1, Issue 1…

    Ji-in Kim, Andrew B. Lawson, Suzanne McDermott, C. Marjorie Aelion

    “A health outcome can be observed at a spatial location and we wish to relate this to a set of environmental measurements made on a sampling grid. The environmental measurements are covariates in the model but due to the interpolation associated with the grid there is an error inherent in the covariate value used at the outcome location. Since there may be multiple measurements made on different covariates there could be considerable uncertainty in the covariate values to be used. In this paper we examine a Bayesian approach to the interpolation problem and also a Bayesian solution to the variable selection issue. We present a series of simulations which outline the problem of recovering the true relationships, and also provide an empirical example.”

    Modelling Individual Space–time Exposure Opportunities: A Novel Approach to Unravelling the Genetic or Environment Disease Causation Debate

    In Geography, Science, Spatial Analysis, Temporal Analysis on October 19, 2009 at 7:53 am

    719813…in Spatial and Spatio-Temporal Epidemiology, Volume 1, Issue 1…

    Clive E. Sabel, Paul Boyle, Gillian Raab, Markku Löytönen, Paula Maasilta

    “The aetiology of Amyotrophic Lateral Sclerosis (ALS) is uncertain. While around 10% is assumed to be inherited, the relative influence of genetic versus physical or social environmental factors (or some combination of the two) has yet to be determined.

    “A previous study identified significant clustering of ALS at the time of birth in south-east Finland and this could support either a genetic or an environmental hypothesis. We know that south-east Finland is an environmentally degraded area, but the population in this region may also be genetically susceptible to this condition.

    “We therefore extend this research by comparing the lifetime residential histories of 1000 ALS cases and 1000 controls matched by birth date, sex and municipality of birth. By focusing on those who originated in the south-east, and comparing the subsequent residential mobility of these two groups, we test whether remaining in south-east Finland is more common among cases than controls and, hence, whether there may be an environmental or genetic influence on ALS associated with that region. Our results indeed suggest that the cases were more likely to remain in south-east Finland after birth, compared to the geographically matched controls. This suggests that moving away is protective, and points towards a risk factor after birth being implicated in the aetiology of the disease.”

    Comparison of Tests for Spatial Heterogeneity on Data with Global Clustering Patterns and Outliers

    In GIS, Geography, Spatial Analysis on October 16, 2009 at 4:52 am

    plague…from the International Journal of Health Geographics 2009, 8:55…

    Monica C Jackson, Lan Huang, Jun Luo, Mark Hachey, Eric Feuer

    “Background

    “The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier) detection) has not been thoroughly investigated.

    “Methods

    “We compare methods for global clustering evaluation including Tango’s Index, Moran’s I, and Oden’s I*pop; and cluster detection methods such as local Moran’s I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango’s MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States.

    “Results

    “For simulated data with outlier patterns, Tango’s MEET, Moran’s I and I*pop had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango’s MEET and I*pop (with 50% of total population as the maximum search window) had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran’s I has powers around 0.2-0.3. In the real data example, Tango’s MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango’s MEET. SaTScan also found clusters and outliers in the lung cancer mortality data.

    “Conclusions

    “SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango’s MEET and Oden’s I*pop perform best in global clustering scenarios among the selected methods. The use of SaTScan for data with global clustering patterns should be used with caution since SatScan may reveal an incorrect spatial pattern even though it has enough power to reject a null hypothesis of homogeneous relative risk. Tango’s method should be used for global clustering evaluation instead of SaTScan.”

    New Peer-reviewed Scientific Journal: Spatial and Spatio-temporal Epidemiology

    In GIS, Geography, Science, Social Science, Spatial Analysis, Temporal Analysis on October 15, 2009 at 12:50 pm

    719813Elsevier, a world-leading publisher of scientific, technical and medical information products and services announced today the launch of a new peer-reviewed scientific journal, Spatial and Spatio-temporal Epidemiology (http://www.elsevier.com/locate/sste). The first issue was published in September 2009 and will be a primary forum for academics and scholars in the growing fields of graphical information systems, epidemiology, exposure science, and spatial statistics.

    Spatial and Spatio-temporal Epidemiology will publish a broad range of topics relating to geospatial health methodology. The journal focuses on answering epidemiological questions where spatial and spatio-temporal approaches are appropriate to help advance our understanding of infectious and non-infectious diseases in humans. Veterinary topics will also be included. The journal places special emphasis on spatio-temporal aspects of emerging diseases (e.g., avian flu, SARS), development of spatial statistical and computational methods, and novel applications of geospatial technology (e.g., GPS, GIS) for shedding insights on exposure and disease processes.

    The Editorial Board will be led by the internationally recognized scholar Professor Andrew B. Lawson, Division of Biostatistics & Epidemiology, College of Medicine, Medical University of South Carolina, USA.

    “Spatial and Spatio-temporal Epidemiology is the premier vehicle for novel developments and advances in the area of geospatial health methodology,” commented Professor Andrew B. Lawson, “In this outlet we hope to attract state of the art papers describing the latest advances in methodology in application to spatial and spatio-temporal epidemiology.”

    Jane Ma, Executive Publisher at Elsevier commented; “H1N1 is one of the world’s greatest challenges for public health. It requires experts from a number of specialties to ensure this challenge is dealt with effectively. Spatial and Spatio-temporal Epidemiology uniquely draws together key research from across the medical, social science and statistics disciplines to address key health issues such as H1N1, Avian ‘flu and cancer clustering in an effort to provide a more holistic approach to epidemiological questions and how space and time impact on these.”

    [Source: Elsevier news release]

    Geographical Variations in the Correlates of Blood Donor Turnout Rates: An Investigation of Canadian Metropolitan Areas

    In GIS, Geography, Social Science, Spatial Analysis on October 14, 2009 at 7:35 am

    plague…from the International Journal of Health Geographics 2009, 8:56…

    Pj Saberton, Antonio Paez, K. Bruce Newbold, Nancy M Heddle

    “Background

    “Like other countries, Canada’s population is aging, and the implications of this demographic change need to be better understood from the perspective of blood supply. Analysis of donor data will help to identify systematic patterns of donation and its correlates. Data Geo-coded blood donor and donor clinic data are provided by Canadian Blood Services. Blood donor data is provided for the fiscal year 2006-2007 indicating the total number of donors for each Canadian postal code, excluding the province of Quebec. Potential correlates of blood donation are selected based on social and economic characteristics, as well as descriptors of city size and geographical location in the urban hierarchy measures of accessibility, and capacity of donor clinics.

    “Methods

    “Data is aggregated to n=3,746 census tracts in 40 Census Metropolitan Areas (CMA) across the country. The number of donors per population in a census tract is regressed against the set of potential donation correlates. Autocorrelation is tested for and results adjusted to provide parsimonious models.

    “Results

    “A number of factors are found to influence donation across the country, including the proportion of younger residents, English ability, proportion of people with immigrant status, higher education, and a population-based measure of accessibility.

    “Conclusions

    “While a number of correlates of blood donation are observed across Canada, important contextual effects across metropolitan areas are highlighted. The paper concludes by looking at policy options that are aimed toward further understanding donor behaviour.”

    The Evolution of the Water Distribution Capital Improvement Planning Template

    In ESRI, GIS, Spatial Analysis on October 14, 2009 at 7:27 am

    esri…from the ESRI Water Utilities Blog…

    “As you may have seen, we released the Water Distribution Capital Improvement Planning (CIP) Template a last week.  First, we wanted to say a big thank you to all of our users and business partners who helped us to refine the initial geoprocessing models and the toolset also shared their workflows for capital planning.

    “We’ve already had a few questions about why we chose the term Capital Improvement Planning (CIP) to describe this template, since not all utilities use that term.  So when we use the term CIP, what we mean is the long term plans of a utility to manage their assets and/or to expand their system, what you may also call a “Capital Plan”, “Long Term Plan” or “5 year plan”.”

    Call for Papers: GIScience Applied to Hazard and Climate Change Research, Salzburg, Austria 6-9 July 2010

    In Climate Change, Conferences, GIS, GIScience, Spatial Analysis on October 11, 2009 at 9:56 am

    Spatial assessment and analysis of vulnerability

    GIScience applied in the interdisciplinary domain of hazard and climate change research

    Workshop within the framework of GI_Forum 2010
    July 6-7, 2010

    This theme is expected to highlight different developed and currently investigated methodologies to spatially assess vulnerability. It will specifically address the issue of vulnerability assessment, independent from conceptual discussions. The focus will be on the review and discussion of different methods of GIScience employed to assess, quantify and represent vulnerability as integrated spatial phenomena. Within a workshop session, current achievements and future research challenges will be identified and formulated.
    Topics

    • Assessments in the domain of disaster risk reduction, climate change, natural
      hazards and human security domain
    • Methods on indicator selection and index construction
    • Scale issues in vulnerability assessments
    • Validation and accuracy of vulnerability assessments
    • Spatio-temporal visualisation of complex indicators
    • The workshop is scheduled for Tuesday, July 6 and Wednesday, July 7, 2010 and will be followed by the annual GI_Forum. Next to presentations ranging from different scholarly schools of vulnerability the workshop will focus on output oriented discussion sessions.

    The papers will be peer-reviewed and published in a book.

    Schedule

    • Deadline for submission of full papers for oral presentation and publication in the
      conference proceedings 1 February 2010
    • Notification about accepted contributions 17 March 2010


    Author Information and Guidelines     [PDF]

    Scientific committee

    • Susan L. Cutter, University of South Carolina (Keynote Speaker)
    • Mark Pelling, King’s College London
    • Thomas Loster, Munich Re Foundation
    • Fabrice Renaud, United Nations University (EHS)
    • Klaus Steinnocher, Austrian Institute of Technology
    • Melanie Gall, Louisiana State University
    • Peter Zeil, Centre for Geoinformatics – University of Salzburg
    • Stefan Kienberger, Centre for Geoinformatics – University of Salzburg

    Contact: Stefan Kienberger

    Hot Spot Analysis – An ArcGIS Tutorial

    In ESRI, GIS, Spatial Analysis, Statistics on October 9, 2009 at 3:59 am

    hotspot“In this 9.3/9.3.1 tutorial, 911 Emergency call data is investigated and analyzed using the Hot Spot Analysis tool (Getis-Ord Gi* statistic). The tutorial begins by setting the scenario: Authorities in your community are spending a large portion of public resources responding to 911 emergency calls. They want to better understand the distribution of 911 calls in order to more effectively allocate emergency response resources. This tutorial guides you through the process of building a Hot Spot Analysis model tool. You will learn how to aggregate incident data, select appropriate parameter settings, and display results.”

    Call for Papers: Geoinformatics Forum, 6-9 July 2009, Salzburg, Austria

    In Climate Change, Conferences, GIS, SDI, Spatial Analysis on October 8, 2009 at 7:45 am

    GI-forumThe Geoinformatics Forum (GI_Forum) focuses on an international audience that shares an interest in Applied Geoinformatics. This Call for Papers aims at researchers who design, develop and apply advanced methods and techniques of Geoinformatics to a broad range of application domains.

    GI_Forum solicits contributions on emerging topics and research outcomes related to current Geoinformatics methodology, and especially wishes to attract submissions pertaining to the following topics:

    • Advances in Geovisualization and Cartography (in cooperation with InterCarto-InterGIS)
    • Spatial Data Infrastructure
    • Mobile GIS and Location Based Services
    • Digital Terrain Representation and Analysis
    • Digital Cities and Urban Sustainability
    • Global Change: Monitoring and Modelling
    • Vulnerability: Spatial Assessment and Analysis
    • Learning with Geoinformation

    GI_Forum 2010 gives authors choices about the type of submission they want to make in order to accommodate a variety of interdisciplinary contributions. Submissions are expected in English language according to the formatting guidelines published on the conference website.

    Deadline for submission of full papers for oral presentation and publication in the conference proceedings and extended abstracts for discussion sessions is 01 February 2010.

    Maps Link Clean Water, Sanitation, and Poverty for Uganda’s Development

    In Environmental Science, GIS, Geography, Social Science, Spatial Analysis on October 8, 2009 at 7:30 am

    …fromt eh World Resources Institute…

    “A new set of maps illustrating levels of clean drinking water, sanitation facilities, and poverty in Uganda will help guide national development planning.

    “Limited access to clean water and sanitation threatens not only the health of Ugandans but also their education opportunities,” said Disan Ssozi, assistant commissioner at Uganda’s Ministry of Water and Environment, co-author of Mapping a Healthier Future: How Spatial Analysis Can Guide Pro-Poor Water and Sanitation Planning in Uganda – a new report released today in Kampala.  “The maps and data in this report will help inform Uganda’s water infrastructure planners and protect the nation’s most vulnerable citizens.”

    “In 2004, Uganda’s central government set national targets to increase access to clean water and sanitation to 100 percent in urban areas and 77 percent in rural districts by 2015.

    “So far, Uganda’s investment plans, which are expected to cost approximately US $1.4 billion, have helped improve drinking water coverage in rural sub-counties, from 25 percent in the early 1990s to 65 percent in 2009.  However, work remains to be done to ensure that all areas meet national targets.”

    Invasive Autumn Olive Species Studied with GIS

    In ESRI, Environmental Science, GIS, Spatial Analysis on October 8, 2009 at 7:00 am

    header-nac09A STUDY OF ELAEAGANS UMBELLATA DISPERSAL BASED ON THE AGES AND RELATIVE LOCATIONS OF INDIVIDUALS IN A STAND

    Mame Redwood, Derek Evans , Chris Evans, David J. Gibson.

    Presented at the 36th Natural Areas Conference, “Living on the Edge: Why Natural Areas Matter”, Vancouver, Washington, USA, September 15-18, 2009.

    This study examines the spread of the invasive species Elaeagans umbellata (Autumn Olive) based on the ages and relative locations of 76 individuals in a 2.95 hectacre stand. All individuals of E. umbellata in the stand were mapped using GPS in a 20 meter grid with locations subsequently mapped using ESRI ArcGIS. The locations of younger individuals were compared to locations of older individuals to examine dispersal routes and test the null hypotheses that age was homogenous across the stand. The age and diameter of each individual was recorded to allow investigation of the age-to-diameter ratio. Analysis of the ages and diameters showed no consistent age: diameter ratio. Analysis of the relative ages of nearest neighbors indicated a non-random age-class structure (χdf=9 = 56.38, p < 0.0001). Individuals aged 1-4 years most often had 5-9 year old neighbors. Individuals aged 5-9 most often had neighbors of the same age. Individuals aged 10-14 most often had neighbors aged 15+, and individuals aged 15+ most often had neighbors aged 9-14. A map presenting the ages and relative locations of individuals showed a cluster of older individuals which appear to be the founder plants during colonization of the stand.

    GIS Used to Study Invasive Weed Abundance in Wisconsin Watershed

    In Environmental Science, GIS, Spatial Analysis on October 7, 2009 at 6:16 am

    header-nac09WETLAND PHALARIS ARUNDINACEA ABUNDANCE AS A FUNCTION OF WATERSHED SOIL AND LAND COVER ATTRIBUTES

    Nina Borchowiec and Amanda Little.

    Presented at the 36th Natural Areas Conference, “Living on the Edge: Why Natural Areas Matter”, Vancouver, Washington, USA, September 15-18, 2009.

    P. arundinacea is a weed that grows invasively across North America. It suppresses native vegetation, ultimately reducing ecological diversity. Knowing how P. arundinacea responds to landscape attributes will help determine how to monitor and manage it. We related P. arundinacea abundance from a statewide data layer created by the Wisconsin Department of Natural Resources. ArcGIS 9.2 was used to calculate the proportions of different soil surface textures, drainage classes, and land-cover types in each watershed to determine NRCS 12-digit watershed characteristics that influenced the abundance of P. arundinacea in wetlands of the Lower Chippewa River Watershed, Wisconsin, USA.

    To reduce the number of covarying attributes, we used non-metric multidimensional scaling to create composite variables. We used multiple linear regression to relate these variables to wetland P. arundinacea abundance, as a percentage of wetland land cover dominated by P. arundinacea.

    One surface texture and one drainage class variable predicted P. arundinacea abundance (log(y) = 1.23 + 0.467drainvar1 – 0.166surftexvar2, R2 = 29.5%, P < 0.001). Synthetic land cover variables were not significant predictors. Relationships between individual predictors and synthetic variables indicate that P. arundinacea is more abundant in wetland watersheds with more wetland-type muck soils and less abundant with substantial open water. These findings indicate that agriculture may not be a strong driver of P. arundinacea abundance at the watershed level. P. arundinacea is not found in watersheds with somewhat excessively drained fine sandy loam, although it‘s uncertain whether this is a function of the soil properties or associated topographic constraints.

    GPS Innovator and Educator Honored as Cal State Fullerton’s Outstanding Professor for 2009

    In Geography, Science, Spatial Analysis on October 6, 2009 at 10:33 am

    fullertonA noted educator and internationally recognized authority on satellite global positioning has been named Cal State Fullerton’s Outstanding Professor for 2009.

    Mohinder Grewal, professor of electrical engineering and a faculty member since 1975, was stunned when faculty members and administrators led by CSUF President Milton A. Gordon walked into a meeting about satellite communications to present him with the award.

    “Each year, one of the university’s 2,000 faculty is chosen as the best,” Gordon said as he walked over to stand next to the honoree. “Guess who it is this year? Professor Grewal!”

    The two dozen students at the meeting loudly applauded as Gordon presented the professor with a crystal trophy engraved with a picture of a communications satellite and words declaring Grewal the 2008-09 Outstanding Professor Award honoree.

    “I’m not going to read the list of his accomplishments,” said Gordon, brandishing several printed pages. “It’s two pages long!”

    “Congratulations, Dr. Grewal. This award is probably 20 years overdue, but that makes it all the more special,” said Raman Unnikrishnan, dean of the College of Engineering and Computer Science.

    Grewal, who earned his doctorate at USC, enjoys an international reputation for contributions to the development of the space-based positioning, navigation and timing systems that lie at the heart of the increasingly common global positioning technology found in everything from smart phones to navigation systems. He holds two patents with a third patent application pending, all for algorithms related to global positioning and navigation.

    Dorota Huizinga, former associate dean of ECS and now associate vice president for graduate studies and research, added: “I’m so happy for you. I have to tell you, whenever I hear my GPS talking to me, giving me directions, I think of you.”

    “Your accomplishments are so wonderful, so impressive and you’re a wonderful teacher,” added last year’s Outstanding Professor Award recipient Stella Ting-Toomey, professor of human communication studies.

    Scott Hewitt, chair of the Academic Senate and professor of chemistry and biochemistry, said, “This honor is deserved, and your membership is a credit to the Academic Senate.”

    “I’m surprised and stunned,” Grewal said, clearly struggling for control. “I have to give credit to my students, staff and colleagues. This would not have happened without their support all this time. Thank you, thank you.”

    Recipients of the award must demonstrate a record of superlative teaching and distinguished scholarship on a national or international scale, have contributed to the stature of the university and to the California State University system and been of service to the campus and the community in ways related to their teaching.

    Crediting the Support of Students and Peers

    Grewal is quick to credit students and colleagues for his achievements.

    “I have had so many good ones, and they made me think and delve. They asked questions I couldn’t answer, and in trying to find answers, I was sent in new directions. As they developed, they worked with me, and many of them now are successful at places like Raytheon and Boeing and other corporations, and as educators. I still work on projects with some of them.”

    His students and colleagues are just as quick to return the favor.

    Former students and alumni, like Laura Cheung (M.S. electrical engineering ’01), principal systems engineer for Raytheon Co. who has known Grewal for a decade as a student, a mentor and a colleague, was lavish in her praise: “As his student at Cal State Fullerton, I benefited greatly from Dr. Grewal’s instruction. His exemplary work in developing and teaching GPS and Kalman filtering classes has made CSUF one of just a few universities in North America to offer such high-quality and valuable GPS instruction.”

    Satinder Singh (M.S. engineering-electrical ’87), president and chief executive officer of the California-based international company Future Computer Solutions Inc., said studying with Grewal changed his outlook. “I had the pleasure of being in three of his courses, and I found Dr. Grewal to be not only most interesting and engaging in his lecture but, more importantly, I found him inspiring. He ignited a deep interest in everything he touched and drew me into what were, for me, uncharted territories.

    “Moreover, his mentorship did not terminate when I completed my studies and moved into the corporate world,” Singh said. ”He made himself readily available. I availed of it freely when I found myself up against a formidable problem. He continued to be generous with his guidance.”

    Grewal’s positive relationship with his students has continued unabated over the years. Master’s in electrical engineering graduates from 2008, Malia Harris, chief engineer, and Kenny Dang, systems engineer, in the California division of Texas-based of DRS Sensors and Targeting Systems, co-authored a letter of recommendation for Grewal, citing his roles as teacher and mentor.

    “Over the last three years, we have taken many courses with Dr. Grewal. We feel he surpasses most instructors in his passion for his work and his ability to engage others,” they noted. “His excitement for his work is contagious [and], he also is extremely supportive of the students around him and encourages them to challenge themselves.”

    Phyllis Harn, an administrative support coordinator in the Electrical Engineering Department for more than two decades before retiring in 2007, sang the professor’s praises with obvious enthusiasm. “There are many great educators at CSUF. However, to be an Outstanding Professor, you need something special,” Harn said. ”I believe when you combine the professional accomplishments of Dr. Grewal with the utmost respect he has earned from everyone, you have that winning combination.”

    “Dr. Grewal’s student evaluations are among the highest in the department; in fact they are always in the top two … He is the sole adviser of all new graduate students who apply to our program and does the initial evaluation and advising for every single applicant to our master’s in software engineering program,” noted Mostafa Shiva, chair and professor of electrical engineering. “Dr. Grewal has earned national and international recognition by his scholarly activities, research and publications. His performance is exceptional in all areas. He is a one-of-a-kind teacher who achieves the highest levels of excellence.”

    Professional Accolades

    Gerard Lachappelle, professor of geomatics engineering and chair of the Wireless Location Department at Shuclich School of Engineering, University of Calgary, Alberta, Canada, and a two-decade industry veteran in navigation research and development, contends that Grewal’s contributions to the field of satellite and inertial navigation have made him “without question one of the academic leaders in this field worldwide.

    “His book ‘Kalman Filtering Theory and Practice Using MATLAB’ has become one of the few standard books for students and research engineers in the field of navigation. His book ‘Global Positioning Systems, Inertial Navigation and Integration’ has equally been accepted in our community. And he has contributed massively to the training of professionals through regular and high-quality short courses,” said Lachappelle.

    The Orange County Engineering Council honored Grewal last spring with the Excellence in Engineering Education Award, its highest award for an educator. The council acts as the umbrella organization for the technology-rich county, which includes dozens of engineering groups, corporations and educational institutions.

    Roboticist Sam Rokni (B.S., M.S. electrical engineering ’05, ’07), now an engineering lecturer at Cal State Fullerton, said Grewal showed him connections to robotics he hadn’t yet considered. Incorporating GPS and space-based navigation, like those used for airplanes, package tracking and cell phones, was a big one. “He helped me see how it could apply to my field.”

    GPS World named Grewal one of the “50+ Leaders to Watch” in the world in 2007 and 2008 for advancements in space-based positioning, navigation and timing systems. In addition to his two co-edited books, he has authored and co-authored dozens of articles and papers on navigation and global positioning and has given many presentations, lectures and seminars internationally.

    Recognition at Commencement

    As the 2008-09 Outstanding Professor Award recipient, Grewal will be recognized at the university’s May 22 Honors Convocation and will lead the faculty at the May 23 and 24 commencement ceremonies. He will receive a $4,000 cash award from the President’s Associates and will present a public lecture next spring.

    Zvi Drezner, professor of information systems and decision sciences and the recipient of the 2005-06 Outstanding Professor Award, chaired the Outstanding Professor Selection Committee.

    Grewal resides in Anaheim Hills and is currently on sabbatical pursuing research in inertial navigation.

    [Source: Cal State Fullerton press release]

    Professor Receives $1 Million NSF Grant for School Attendance Boundary Project

    In Education, GIS, Social Science, Spatial Analysis on October 6, 2009 at 9:54 am

    nsflogo“Salvatore Saporito, an associate professor of sociology at William & Mary, has received a $1 million grant from the National Science Foundation to create a new database of school attendance boundaries for the country’s largest school districts.

    “The grant funds two years of work on the School Attendance Boundary Information System (SABINS). Saporito will build the SABINS database in conjunction with Stuart Hamilton, director of William & Mary’s Center for Geospatial Analysis, and Petra Noble and Rob Warren of the Minnesota Population Center at the University of Minnesota. With the assistance of William & Mary undergraduate student researchers, the team will use Geographic Information Systems (GIS) technology to map school attendance boundaries for 800 of the largest school districts nationwide. Elementary, middle and high school attendance boundaries delineate the geographic areas from which schools draw their students.”

    Fifth International Workshop on “Geographical Analysis, Urban Modeling, Spatial Statistics” in Fukuoka, Japan, 23-26 March 2010

    In Conferences, GIS, Modeling, Science, Spatial Analysis, Statistics on October 6, 2009 at 9:31 am

    (in conjunction with the 2010 International Conference on Computational Science and its Applications)

    During the past decades the main problem of geographical analysis was the lack of spatial data availability. Today the wide diffusion of electronic devices containing geo-referenced information generates a great production of spatial data. Volunteered geographic information activities (e.g. Wikimapia, OpenStreetMap), public initiatives (e.g. Spatial Data Infrastructures, Geo-portals) and private projects (e.g. Google Earth, Microsoft Virtual Earth, etc.) produced an overabundance of spatial data which in many cases does not help the efficiency of decision processes. The increase of geographical data availability has not been fully coupled by an increase of knowledge to support spatial decisions. The inclusion of spatial simulation techniques in recent GIS software favoured the diffusion of these methods, but in several cases led to the mechanism of which buttons to press without having geography in mind. Spatial analytical techniques, geographical analyses and modelling methods are therefore required in order to analyse data and to facilitate the decision process at all levels. Old geographical issues can find an answer thanks to new methods and instruments, while new issues are developing, challenging the researchers for new solutions. This workshop aims at contributing to the development of new techniques and methods to improve the process of knowledge acquisition.

    Mapping Culture: Novel Approach to Fusing Social Science and Geospatial Technology to Go Beyond Traditional Intelligence Analysis

    In GIS, Geography, Social Science, Spatial Analysis on October 6, 2009 at 8:58 am

    “Human Terrain Analysis” Helps Commanders Visualize the Battlefield and Analysts Discover Hidden Patterns

    As the American military continues to try to adjust to the post- 9/11 realities and transform its force, tactics, techniques, and procedures, a small company based in the Reston, VA technology belt has championed a novel approach to traditional intelligence analysis. Its combination of social science and geospatial technology is at the cornerstone of an analytical method the DoD is increasingly turned to that has been termed “Human Terrain Analysis.” SCIA’s mission is to map culture in areas of limited and sparse information to provide U.S. military commanders actionable intelligence analysis on the local socio-cultural dynamics of an area.

    SCIA leverages commercial off-the-shelf geospatial technology and proprietary methods of social scientifically-based analysis to create a variety of maps depicting the geospatial patterns of behavior for groups and individuals of interest for the U.S. military. “Human terrain analysis is essentially the mapping of culture, discovering geospatial patterns of behavior we would not otherwise be aware of. The method enables analytic discoveries and provides the basis for true socio-cultural intelligence analysis of a region,” said Dr. Swen Johnson, who founded SCIA in 2005 to help provide the kind of intelligence product he sought while deployed as a US Army counterintelligence special agent in Kosovo. “Only recently has the government begun institutionalizing this kind of analysis. There were no jobs for ‘Human Terrain Analyst’ back in 2005 and I had to create the company in order to do the work that I saw we needed. It was a classic example how private industry can help the government and military see a way forward.”

    The lack of basic knowledge on the geographic distribution and sociological characterization of ethnic, tribal, and religious groups has been identified as one of the U.S. military’s most pressing intelligence gaps. Typically, military intelligence has been narrowly concerned with either manhunts or kinetic strikes, and its intelligence apparatus has been designed for this kind of fight. As the military broadens its approach to include tribal engagement, stability operations, and support to sovereign governments, SCIA is helping transform the way intelligence data is collected and analyzed.

    Johnson added: “SCIA’s approach to Human Terrain Analysis is about providing a niche type of intelligence analysis that helps our soldiers when they engage tribes and clans in dangerous locations. We go beyond simple demographics to study the micro-sociological environment from a geospatial perspective.”

    The methods that SCIA has helped develop and champion have lead to invitations to teach and train others in both domestic and foreign markets. Foreign military allies of the US, various elements of the U.S. Department of Defense and intelligence community, and the academic community have asked SCIA for assistance. “Currently, we only provide one course open to the public as a community service offering; the other courses we do are on an on-contract basis.” SCIA offers a three-day training seminar on Human Terrain Analysis through George Mason University’s Professional Certificate in Geographic Information Systems (GIS) program once a year. The HTA Seminar introduces analysts to the tools and methods they need for socio-cultural and human terrain analysis, emphasizing social science concepts and methods, geospatial skills specific to human terrain analysis; subject matter expertise of particular cultures of interest; social network analytical software and concepts, and traditional all-source intelligence analytical methods.

    While primarily focused on military objectives, SCIA is in the process of developing commercial applications for the strategy and technology. Johnson says the methods developed in the crisis environments Human Terrain Analysis was born in have obvious applications in the commercial world. For more information about how SCIA is changing the dynamic of military intelligence, please visit www.sciasolutions.com.

    [Source: SCIA press release]

    Technology Drives Climate Science: A GIS-based Action Plan

    In Climate Change, Design, Earth Systems Management, Earth Systems Science, Environmental Science, GIS, Geography, Modeling, Science, Spatial Analysis, Visualization on October 5, 2009 at 12:52 pm

    Our world faces unprecedented challenges, and only one technology is poised to collect, manage, and analyze the myriad of physical, biological, and cultural data describing the past, present, and future of Earth.  That technology is geographic information systems (GIS), commonly used today to view and manage information about geographic places, analyze geographic relationships, and model geographic processes.

    GIS technology has proven to be invaluable in driving intelligent decision making, and its application to climate science is a natural fit.  In fact, extensive work has already been done over the last 40 years to apply GIS technology to address subjects such as land use inventory, data model development, climate model integration, carbon accounting, and climate change visualization.

    We are at a point in the evolution of the technology and its broad application where the next logical step is development of a GIS-based framework for earth systems modeling and global design.  Such a system would cross academic, scientific, and industrial domains and political boundaries to serve as a platform for a comprehensive climate monitoring, modeling, and management system.

    There are several actions we can take now to establish a framework that leverages mature GIS technology to advance climate science.

    • Create a Comprehensive Climate Information System. A GIS-based platform for modeling and managing earth systems will help us identify climate trends, understand the effects of climate change, design mitigation plans, predict possible outcomes, monitor results, and provide feedback for an adaptive response.
    • Create a Climate Data Infrastructure. A global spatial data infrastructure for climate change studies—a loosely-coupled, decentralized directory of all types of climate and map data and imagery—will serve as the basis for earth systems modeling and global design projects conducted in the Climate Information System.
    • Integrate Earth Systems Modeling. A thorough inventory of climate change related spatial data models and sharing of best practices on interoperability will be of tremendous value as we build a Climate Information System for analyzing impacts and alternative futures at a comprehensive, global scale.
    • Develop a Global Climate Dashboard. A Global Climate Dashboard would summarize information from the Climate Information System, providing “executives” and citizens alike with real-time geographic visualization of various earth systems parameters, enabling a more responsive, iterative, and adaptive response to climate change.
    • Move towards Global Design. A GIS-based geodesign framework will provide a robust set of tools for design professionals to support the design and evaluation of alternate futures for our earth and its systems.

    We are only beginning to understand the complex issues posed by climate change.  Only through careful observation of the data, application of scientific principals, and leveraging of modern technology can we hope to grasp the intricacies of the exceedingly complex systems that comprise our planet.  A GIS-based framework for climate science offers the best chance at gaining a scientific understanding of earth systems at a truly global scale and for making thoughtful, informed design decisions that ultimately allow humans and nature to coexist more harmoniously.

    Redlands GIS Week 2010: Space-Time Modeling and Analysis

    In ESRI, Education, GIS, Modeling, Spatial Analysis, Temporal Analysis on September 30, 2009 at 6:33 am

    …from redlandsgisweek.org…

    “Join us for Redlands GIS Week, an annual series of events bringing together thought leaders from academia, government, and industry to advance the science and application of geospatial technologies. Events will feature keynote presentations, lightning talks, and workshops, as well as opportunities for informal brainstorming with leading geospatial thinkers and implementers.

    “Redlands GIS Week is held at ESRI’s state-of-the-art headquarters in Redlands, California USA. The first event, “Space-Time Modeling and Analysis,” is co-sponsored by the University of Southern California, Environmental Systems Research Institute, Inc. (ESRI), and the University of Redlands, and will be held 22-23 February 2010 bringing together key scientists working on integrating space and time. Afterwards, a publication will be produced to promote the event’s results with a larger audience.

    “More information coming soon.”

    NOAA’s Free Sampling Design Tool Extension for ArcGIS

    In ESRI, Environmental Science, GIS, Spatial Analysis, Statistics on September 28, 2009 at 11:01 am

    randomsampling“The Biogeography Branch’s Sampling Design Tool for ArcGIS provides users a means to efficiently sample a population, be it people, animals, objects or processes, in a GIS environment. The tool was created for sampling when the population and component sampling units are defined by known dimensions.

    “The Sampling Design Tool was developed in response to a need by scientists developing sampling strategies in marine environments with limited data. The tool was produced as part of an iterative process of sampling design development, whereby existing data informs new design decisions. The objective of this process, and hence a product of this tool, is an optimal sampling design which can be used to achieve accurate, high-precision estimates of population metrics at a minimum of cost. Although NOAA’s Biogeography Branch focuses on marine habitats and some examples reflects this, the tool can be used to sample any type of population defined in space, be it coral reefs or corn fields.

    “The Sampling Design Tool has two main functions: 1) to help select a sample from a population, and 2) to perform sample design analysis. When both of these functions are combined in an iterative manner, the tool effectively and simply achieves the goal of sample surveys — to obtain accurate, high-precision estimates of population metrics at a minimum of cost.

    Key features of the tool include:

    • Spatial sampling – sampling and incorporation of inherently spatial layers (e.g., benthic habitat maps, administrative boundaries), and evaluation of spatial issues (e.g., protected area effectiveness)
    • Scalable data requirements – data requirements for sample selection can be as simple as a polygon defining the area to be surveyed to using existing sample data and a stratified sample frame for optimally allocating samples
    • This is a screen capture of the main console of the Sampling Design Tool.
    • Random selection – eliminates sampling biases and corresponding criticisms encountered when samples are selected non-randomly
    • Multiple sampling designs – simple, stratified, and two-stage sampling designs
    • Sample unit-based sampling – points or polygons are selected from a sample frame
    • Area-based sampling – random points are generated within a polygon
    • Analysis – previously collected data can be used to compute sample size requirements or efficiently allocate samples among strata
    • Computations – mean, standard error, confidence intervals for sample data and inferences of population parameters with known certainty
    • Output – geographic positions in output simplifies migration to global positioning systems, and sample size estimates and sample statistics can be exported to text files for record keeping

    More information

    [via freegeographytools.com]

    Graduate Study Opportunity: Landscape and Ecological Change Near Abandoned Mines in Northern Canada

    In ESRI, Education, Environmental Science, GIS, Spatial Analysis on September 28, 2009 at 8:35 am

    memorial_univ…from the Northern Research Network blog…

    “Using facilities in Dr. Yolanda Wiersma’s Landscape Ecology and Spatial Analysis (LESA) Lab in the Biology Department at Memorial University of Newfoundland, the successful graduate student will use Environmental Systems Research Institute (ESRI) ArcInfo GIS software to analyze landscape and ecological changes in the regions surrounding one or two of our case study communities.”

    Volunteer Research Assistants Needed for Spatial Analysis of Australian Dolphins

    In ESRI, Education, Environmental Science, GIS, Spatial Analysis on September 28, 2009 at 8:12 am

    murdochWHAT: Volunteer assistants are requested to partake in a PhD project investigating diet and foraging ecology of bottlenose dolphins.

    WHERE: Bunbury, South Western Australia (180 km south of Perth). A beautiful coastal town with easy access to Perth, the Margaret River wine region, surfing and bush walking.

    WHEN: January to March 2010; and June to September 2010.

    DUTIES: Relative composition and abundance of prey species in the Koombana Bay region will be sampled using beach seine nets, fish traps, and gillnets. Volunteers will be required to manually deploy and retrieve fish traps, seines and gillnets, assist in the operation of a research vessel, identify, count, weigh, and measure fish and invertebrate species.

    Stomach contents of stranded dolphins and scat samples will be analysed for prey content. This will involve separating and identifying hard parts in scat and stomach samples. Volunteers may also have the opportunity to assist with post mortem examinations of stranded dolphins.

    Spatial analysis to determine foraging “hot spots” will be carried out using point observational data. Assistants will be required to assist in the creation of data layers by entering data into an ArcGIS format and learn to use some basic GIS tools.

    Fish, invertebrate, and marine plant samples will be collected and prepared for stable isotope analysis. Volunteers may also be required to assist in the biopsying of dolphins for stable isotope work.

    Data entry and management, equipment maintenance, and other office and lab tasks will be required.

    QUALIFICATIONS:
    Mandatory
    -Primary requirement is a good attitude, work ethic, and ability to work in a physically demanding environment. This can include long hours in extreme weather conditions and long days on the water. Hauling fish traps and nets is physically demanding work. Volunteers must be able to repeatedly lift over 23 kg (~51 lbs).
    -Must be able to commit to a minimum of one month. People able to commit for longer periods will be preferred.

    Preferred, but not mandatory
    -Undergraduate degree in the biological sciences
    -Previous field work experience, specifically with fisheries or marine mammals
    -Experience using ArcGIS or similar spatial analysis software
    -Experience managing large datasets
    -Experience operating vessels up to 7 meters in length

    COMPENSATION: Regrettably volunteers will be required to arrange their own transportation to Bunbury, accommodation and all living expenses. (Backpackers and rooms in shared houses are available for approximately AU$90/week). Schedules may be flexible to allow volunteers to work on a part-time basis if legally able in Australia (e.g. possession of a working holiday visa). Academic credit may be earned if arranged through your local institution. Valuable field and lab experience in the ecological sciences will be gained through participation in this project.

    HOW TO APPLY: Please send a CV, letter of interest, and at least one letter of reference to:
    Shannon McCluskey
    Murdoch University Cetacean Research Unit
    c/o Dolphin Discovery Centre
    Bunbury, Western Australia 6230

    or electronically to: S.McCluskey@murdoch.edu.au

    The FullCAM Carbon Accounting Model: Development, Calibration, and Implementation for the National Carbon Accounting System

    In Climate Change, GIS, Imagery, Modeling, Spatial Analysis on September 25, 2009 at 8:55 am

    aus_greenhouse“The Australian National Carbon Accounting System (NCAS) : supports Australia’s position in the international development of policy and guidelines on sinks activity and greenhouse gas emissions mitigation from land based systems; reduces the scientific uncertainties that surround estimates of land based greenhouse gas emissions and sequestration in the Australian context; provides monitoring capabilities for existing land based emissions and sinks, and scenario development and modelling capabilities that support greenhouse gas mitigation and the sinks development agenda through to 2012 and beyond; and provides the scientific and technical basis for international negotiations and promotes Australia’s national interests in international flora.

    “Subsequent to the development of the Excel based CAMFor model for the Australian Greenhouse Office, work commenced on the development of an integrated model which combined the CAMFor model with the 3PG forest growth model, the GENDEC litter decomposition model and the Rothamsted soil carbon model (Roth C). A parallel version of the CAMFor model (CAMAg) was developed for agricultural systems and is also integrated with GENDEC and the Roth C model.

    “The model developed, known as FullCAM, integrates the CAMFor and CAMAg based routines to a single C code model capable of carbon accounting in transitional (afforestation, reforestation and deforestation) and mixed (e.g. agroforestry) systems.

    “The FullCAM model can be run in a spatial mode which will integrate information drawn from the remotely sensed land-cover-change program, productivity surfaces and other ancillary data to perform various accounting routines.”

    Study: Lack of Vegetation Heats Up Low-income Neighborhoods

    In Environmental Science, GIS, Social Science, Spatial Analysis on September 24, 2009 at 1:48 pm

    …from statepress.com…

    “The wealth of a neighborhood could influence the outdoor temperature of the area, according to a study to be released in October by ASU researchers.

    “The study, titled “Geospatial Contributions to Urban Hazard and Disaster Analysis,” is part of a project that began in September 2008 with a $1.4 million grant from the National Science Foundation.

    “Results from the study show that an abundance of vegetation in wealthier neighborhoods helps cool down the area, while a lack of vegetation in low-income neighborhoods creates “heat islands,” said Sharon Harlan, an associate professor with the School of Human Evolution and Social Change who contributed to the study.”

    Texas City Proposes Tree-counting Initiative

    In Environmental Science, GIS, Imagery, Spatial Analysis on September 23, 2009 at 4:02 pm

    …from Pegasus News…

    “The city of Denton is trying to protect its shade-bearing friends through the use of satellite imaging.

    “The City Council discussed a possible survey at last week’s meeting that would determine the average number of trees and how to add more to the city.

    “If the proposal is approved, the city of Denton will collaborate with UNT faculty and a graduate student to head up the research side of the project.”

    Health 2.0: Place-Based Intelligence

    In ESRI, GIS, Geography, Spatial Analysis on September 21, 2009 at 7:19 am

    spatround…new from Spatial Roundtable…

    “Are health and human service organizations at every level technically ready for a place-based approach to building health intelligence and actually delivering services?”

    Waldo Tobler to Speak at San Diego State University October 16th, 2009

    In Education, GIS, GIScience, Geography, Spatial Analysis on September 21, 2009 at 7:15 am

    tobler“Professor Emeritus Waldo Tobler, University of California Santa Barbara, will be honored on Oct. 16 by a symposium whose subject will be Tobler’s contributions to and impact on the field of cartography.

    “Tobler, an American-Swiss cartographer and geographer, is a member of the National Academy of Sciences.  He is best known for ‘Tobler’s Law’ on the effect of distance on human and physical relationships, but is also  heralded as an innovative cartographer who has led the field for five decades.

    “The symposium is sponsored by the Arthur Getis Lectureship in Spatial Analysis and the Department of Geography.  Speakers include:  Getis (SDSU), Andre Skupin (SDSU), S.V. Subramanian (Harvard University) and Waldo Tobler (UCSB).”

    • 3 p.m. – 4:15 p.m., Oct. 16
    • West Commons 220, San Diego State University, California
    • Free and open to the public

    More information

    Spatio-Temporal Analysis of Hydrothermal Water Discharging into a River

    In Environmental Science, Spatial Analysis, Temporal Analysis on September 21, 2009 at 6:32 am

    mtgLogoTopLeft…from the 2009 Portland Geological Society of America (GSA) Meeting, 18-21 October 2009…

    IMAGING AND SPATIO-TEMPORAL ANALYSIS OF TURBULENT MIXING OF HYDROTHERMAL WATER DISCHARGING INTO A RIVER (BREITENBUSH HOT SPRINGS, OREGON)

    ANDREWS, Benjamin J., University of California, Berkeley; CARDENAS, M. Bayani, The Univ. of Texas at Austin; and BENNETT, Philip C., The Univ of Texas at Austin

    “We investigated the thermal plume created by a pipe discharging hot spring water (~60 °C) into a small stream (~10 °C) at Breitenbush Hot Springs, Oregon. High-frequency (16 Hz), high-resolution (1-2 mm pixels) thermal infrared images of hot spring jets show the effects of jet entry conditions on spatial and temporal scales of mixing. Images of thermal plumes showing eddy cascades through space and time are analyzed via correlation analysis.”

    Analysing, Mapping, and Evaluating Spatio-temporal Water Scarcity Problems, February 1st to 11th, 2010 in Salzburg, Austria

    In Conferences, Environmental Science, GIS, Imagery, Spatial Analysis, Temporal Analysis, Visualization on September 21, 2009 at 6:25 am

    “The Z_GIS Winter School 2010 is dedicated to the theme of analysing, mapping and evaluating spatio-temporal water scarcity problems and is hosted by Salzburg University’s Centre for Geoinformatics (Z_GIS).

    “Participants with an interest in GIS, Remote Sensing and Hydrology are welcome to attend the short intensive course in the world cultural heritage city of Salzburg.”

    Three Spatial Analysis and Policy Positions Open at the Centre for Spatial Analysis and Policy, University of Leeds

    In Education, GIS, Spatial Analysis on September 18, 2009 at 7:27 am

    leeds“The School of Geography, sixth in the 2008 RAE ranking, would welcome applications from individuals of (or with potential of) international standing who will complement and strengthen existing expertise in any of the following areas: demography and population geography; regional science and spatial economics; quantitative social policy (including health, deprivation, education and crime); geocomputation.”

    Positions available:  Lecturer, Senior Lecturer, Reader.

    Mobile Application Helps Professional and Citizen Scientists Collect and Analyse Data in the Field

    In Citizen Science, Geography, Spatial Analysis on September 18, 2009 at 7:27 am

    …from BBC News…

    “The EpiCollect software collates data from certain mobiles – on topics such as disease spread or the occurrence of rare species – in a web-based database.  The data is statistically analysed and plotted on maps that are instantly available to those same phones.

    “The approach is outlined in the open-access journal PLoS ONE. The software has been developed for so-called smartphones that run Google’s Android open-source operating system.

    “Researchers can report back to the EpiCollect database with results from experiments they do in the field, and ‘citizen scientists’ can send back photos or videos of certain species from their own backyards.”

    Watershed Hydrology Position at the University of Hawaii-Manoa

    In Education, Environmental Science, GIS, Modeling, Spatial Analysis on September 17, 2009 at 7:27 am

    uhmDepartment of Natural Resources and Environmental Management

    Continuous, review of applications begins September 16, 2009.

    Duties and Responsibilities
    Participate in research training on watershed hydrology. Conduct independent research in the areas of water flow and solute transport, irrigation management, surface/subsurface water quality monitoring, numerical modeling and spatial and temporal data analyses using GPS and GIS.

    Minimum Qualifications
    Ph.D. in hydrology, civil engineering, agricultural engineering or related field with emphasis in hydrology, natural resource management or environmental science. Excellent communication skills and ability to work within multidisciplinary and interdisciplinary teams. Ability to carry out independent research and to prepare manuscripts of results for publications.

    Desirable Qualifications
    Strong numerical modeling at different scales (laboratory, field and watershed levels). Competency in using spatially distributed models and supporting databases.

    To Apply

    Send a cover letter of interest; curriculum vitae; transcripts; names, addresses, fax and e-mail addresses of three referees to Dr. Ali Fares, Hydrology Lab, CTAHR/NREM, University of Hawaii, 1910 East-West Road Honolulu HI, 96822.  For Inquiries call Dr. Ali Fares at 808-956-6361; or email afares@hawaii.edu.

    Spatial Statistics: What’s so HOT about Spatial Pattern Analysis?

    In ESRI, GIS, Spatial Analysis, Statistics on September 16, 2009 at 6:48 pm

    gpbheader[ This blog post was written by Lauren Scott, Geoprocessing/Spatial Statistics Product Engineer in the Software Products Group at ESRI in Redlands, and originally posted on the ESRI Geoprocessing Blog. ]

    Hot Spot Analysis is just one of the pattern analysis tools in the Spatial Statistics Toolbox.  You can use these tools to explore spatial patterns in order to answer questions like:

    • Where are crime rates unexpectedly high?
    • Are there regions in the country where people live longer
    • Where do we find anomalous spending patterns?
    • Are there sharp boundaries between affluence and poverty?
    • Is the disease remaining geographically fixed or is it spreading?
    • Which features are most concentrated?
    • Does the spatial pattern of the virus mirror the spatial pattern of the population at risk?
    • Which site is most accessible?
    • Where is the population center?
    • Which species has the broadest territory?

    To learn more about spatial pattern analysis, check out some of these resources:

    University of Vermont Spatial Analysis Laboratory Named Center of Excellence

    In ESRI, Education, GIS, Spatial Analysis on September 16, 2009 at 4:01 pm

    uvtowerThe University of Vermont’s Spatial Analysis Laboratory, part of the Rubenstein School of Environment and Natural Resources, has received two prestigious honors in recent months.

    The Definiens corporation, founded by Nobel Prize laureate Gerd Binnig, recently designated the lab one of eight international Centers of Excellence, based in part on the Urban Tree Canopy (UTC) assessment work the lab carried out in collaboration with the U.S. Forest Service. The other seven Centers of Excellence organizations are among the most well-respected and well-funded remote sensing labs in the world.

    In addition, ESRI, a leading developer of GIS software, last spring named the lab one of the first ESRI Development Centers.

    Both honors have benefits for the UVM community. “The Definiens designation allows us to receive software with a commercial value of $80,0000 and gives us priority access to technical support and the ability to participate the beta software releases,” said Jarlath O’Neil-Dunne, geospatial analyst at the lab. “Thanks to our ESRI Development Center status, all UVM students, staff, and faculty can now install full versions of ArcGIS on their personal computers,” he said. “A convenience in normal times, having access to GIS software at home will be a necessity if UVM is impacted by the H1N1 virus.”

    “These are both truly impressive honors,” said Mary Watzin, dean of the Rubenstein School of Environment and Natural Resources. “They are a testament to the international stature of the Spatial Analysis Laboratory, placing it among a handful of the most well-respected GIS and remote sensing labs in the world. The designations will also bring tangible benefits to UVM students, faculty, and staff.”

    [ Source: University of Vermont Communications ]

    Analyzing Geographic Clusters and Distributions: Free Online Seminar

    In ESRI, GIS, Modeling, Spatial Analysis, Statistics on September 15, 2009 at 6:10 am

    esricanada…free web seminar from ESRI Canada…

    October 8th, 2009, 1:00 p.m. – 2:00 p.m. Eastern Time

    By identifying and measuring relationships, you are in a better position to understand what’s going on in a place, to predict where something is likely to occur or to investigate why things occur where they do. This seminar will introduce a variety of analysis tools and workflows available in ArcGIS. Attendees will learn the benefits of cost path distance analysis, surface interpolation, spatial statistics tools and regression analysis.

    • Introduce distance analysis methods and strategies
    • Understand available surface interpolation methods in ESRI products
    • Utility of spatial statistics for a wide range of applications
    • Regression analysis in ArcGIS

    More information

    IDB Launches New Biofuels Sustainability Scorecard; Includes Spatial Analysis/GIS Tool

    In Environmental Science, GIS, Green Technologies, Spatial Analysis on September 14, 2009 at 5:24 pm

    idbUpdate incorporates feedback from five regional consultations and addresses concerns regarding food security, indigenous peoples and biodiversity preservation

    The Inter-American Development Bank (IDB) has released a new version of its Biofuels Sustainability Scorecard, which will enable users to better anticipate the impacts of potential biofuel projects on sensitive issues such as indigenous rights, carbon emissions from land use change, and food security.

    The first version of the Scorecard, an interactive, web-based tool that was released a year ago, addressed 23 key variables including greenhouse gas emissions, water management, biodiversity and poverty reduction. The IDB subsequently held five regional meetings to solicit feedback on the Scorecard and began collecting and reviewing hundreds of comments and suggestions submitted by outside experts.

    As a result, the updated version of the Scorecard includes new categories to more thoroughly capture the environmental and social dimensions of biofuels investments. Specifically, there are six new social categories that address issues relating to indigenous people, local grower arrangements and impacts on food security, among others.

    “This new version of the Biofuels Sustainability Scorecard reflects the wisdom and experience of a wide spectrum of experts in academia, NGOs, multilateral institutions and the investment community,” said IDB President Luis Alberto Moreno. “Biofuels continue to be a compelling energy alternative for many Latin American and Caribbean countries, but it is essential to understand the full lifecycle impacts of a project first. This Scorecard now offers an even more effective way to ensure that proposed biofuel projects are truly sustainable.”

    The new version of the Scorecard includes a spatial analysis tool that enables users to quickly access existing Geographic Information System (GIS) data regarding areas for biodiversity preservation. Future versions will add data layers to show the spatial dimensions of categories including water scarcity, cultural sites and high carbon sequestration areas, among others.

    User feedback. The new Scorecard also benefitted from the criticisms and suggestions of investors who used the original version. These included the financial backers of Biobahia Oil, a large biofuel complex planned for Northeastern Brazil.

    Euroventures, the company behind the project, was finding it difficult to determine the full social and environmental impacts of this ambitious project, which aims to cultivate some 30,000 hectares of land and produce 200,000 tons of biodiesel per year. So Adrian Calvert, in charge of investors’ relations at the company, sought technical assistance for a feasibility study from the IDB’s Sustainable Energy and Climate Change Initiative.

    In agreeing to help, IDB experts urged the Biobahia team to run their project through the Scorecard.

    “In an increasingly competitive biofuels industry, sustainability has become the key issue in ensuring access to global markets,” said Guillaume Sagez, managing partner of Euroventures. “The IDB Biofuels Sustainability Scorecard has helped us to think through our project plans and find out how we can adopt certain practices to achieve a higher degree of environmental and social sustainability.”

    Among other things, Sagez said the Scorecard showed his project team that they would need to look more closely at the carbon emissions that would result from proposed land use changes in the project, along with nitrogen oxide emissions that can be expected from cultivation and fertilizer application.

    After using the Scorecard, the Biobahia team suggested improvements to the tool that have now made their way into a new version. Going forward, the IDB plans to continue soliciting input on ways to strengthen the Scorecard. The Bank is part of the Global Bioenergy Partnership and the Roundtable on Sustainable Biofuels, both global efforts to develop sustainability criteria for biofuels, and IDB specialists will coordinate with the Food and Agriculture Organization to improve the Scorecard over the next year.

    [Source: Inter-American Development Bank press release ]

    Spatial Power: Augmenting Renewable Energy Goals

    In Climate Change, Environmental Science, GIS, Green Technologies, Spatial Analysis on September 11, 2009 at 2:32 pm

    renew…from GeoSpatial Today…

    “It will not be an exaggeration to say that our planet is at crossroads.  If humans do not take measures to address the serious environmental issues of earth, the consequences will be unimaginable.  Reduction of greenhouse gas emissions—a smaller carbon footprint is the need of the hour.  Renewable Energy is a viable option to traditional fossil fuel and with GIS technology the path to a greener tomorrow becomes that much easy.”

    Improving Delivery of Justice through Use of Science and Technology

    In GIS, Spatial Analysis on September 10, 2009 at 11:21 am

    …from the Daily News…

    “Walk into a traffic branch of any police station and observe the incident map displayed. The map with many dots, triangles belongs more to the last century. The use of GPS/GIS geographical information systems will enable much more information analysis and planning as well as make the whole job much more exciting.”

    Geospatial Tools Offer Killer App for Gov 2.0

    In ESRI, GIS, Spatial Analysis on September 9, 2009 at 4:51 pm

    …from Government Computer News…

    “If the idea of government 2.0 revolves around using government information as a platform for enabling public discourse, then geospatial technologies are one of the killer apps, Jack Dangermond, president of ESRI, said today at the Gov 2.0 Summit in Washington.

    “Maps and geospatial information systems are becoming richer, smarter, and more pervasive, Dangermond said, but government agencies still need to do more to convert data into services that can populate mapping applications.”

    Government Takes On New Data Services Role

    In ESRI, GIS, Spatial Analysis on September 9, 2009 at 4:36 pm

    …from nextgov…

    “Jack Dangermond, founder and president of California-based ESRI, a large provider of geographic information systems technology, told the audience that location-based, online services will bring as much change to the government as GIS brought to agencies such as the Defense Department.

    “Social media applications such as the broadcast text-messaging service Twitter are adding another layer to federal maps that in some cases can save lives, observers have noted. Dangermond referenced the recent California wildfires to show how a combination of geographic coordinates and live reports from first responders can be used to update maps instantly for emergency workers. He displayed an online map of the spreading fires overlaid with the sites of nursing homes and hospitals.

    “”We’re not just seeing maps, we’re seeing spatial analysis,” Dangermond said.”

    Spatial Analysis of Livestock Disease in Great Britain

    In Environmental Science, Modeling, Science, Spatial Analysis on September 9, 2009 at 6:36 am

    bmclogo…from BMC Veterinary Research…

    On the Question of Proportionality of the Count of Observed Scrapie Cases and the Size of Holding

    The present paper investigates the question of a suitable basic model for the number of scrapie cases in a holding and applications of this knowledge to the estimation of scrapie-affected holding population sizes and adequacy of control measures within holding. Is the number of scrapie cases proportional to the size of the holding in which case it should be incorporated into the parameter of the error distribution for the scrapie counts? Or, is there a different – potentially more complex – relationship between case count and holding size in which case the information about the size of the holding should be better incorporated as a covariate in the modeling?

    We show that this question can be appropriately addressed via a simple zero-truncated Poisson model in which the hypothesis of proportionality enters as a special offset-model. Model comparisons can be achieved by means of likelihood ratio testing. The procedure is illustrated by means of surveillance data on classical scrapie in Great Britain. Furthermore, the model with the best fit is used to estimate the size of the scrapie-affected holding population in Great Britain by means of two capture-recapture estimators: the Poisson estimator and the generalized Zelterman estimator.

    No evidence could be found for the hypothesis of proportionality. In fact, there is some evidence that this relationship follows a curved line which increases for small holdings up to a maximum after which it declines again. Furthermore, it is pointed out how crucial the correct model choice is when applied to capture-recapture estimation on the basis of zero-truncated Poisson models as well as on the basis of the generalized Zelterman estimator. Estimators based on the proportionality model return very different and unreasonable estimates for the population sizes.

    Our results stress the importance of an adequate modelling approach to the association between holding size and the number of cases of classical scrapie within holding. Reporting artefacts and speculative biological effects are hypothesized as the underlying causes of the observed curved relationship. The lack of adjustment for these artefacts might well render ineffective the current strategies for the control of the disease.

    Spatial Analysis of an Archaeological Site in Montana

    In Education, Environmental Science, Social Science, Spatial Analysis on September 8, 2009 at 7:07 am

    montanaA Spatial Analysis of 24HL1085: A Prehistoric Site in the Bear’s Paw Mountains

    By Jessica Jo Bush

    “This thesis is a spatial analysis of 24HL1085 and attempts to discern the use areas of two prehistoric components, Late Archaic and Late Prehistoric, through the identification of spatial patterns created by the excavated lithics, faunal remains, and fire cracked rock (FCR). I also wanted to show that understanding the spatial layout of FCR is just as important as understanding the spatial layout of lithics and faunal remains. In order to complete this analysis the three ring model developed by Stevenson (1985) was adapted and combined with the trend surface analysis created by Hodder and Orton (1976). Theory behind this analysis was based heavily on work done by Binford (1978, 1979, 1980, 1983, 1987). Results from this study showed that both components were comprised of several discernible use areas that provided a better understanding of how the site was created and used. Despite being separated by several thousand years, both components are representative of campsites at which people were hunting and gathering resources locally before leaving. Without the spatial data obtained from the FCR, a spatial analysis would have been almost impossible to complete to the same degree of certainty.”

    Spatial Analysis of Ecosystems: Assistant/Associate Professor, University of South Florida

    In Education, Environmental Science, Spatial Analysis on September 8, 2009 at 6:59 am

    usf_logo“Spatial Analysis/Ecosystems (Assistant/Associate Professor level): We welcome candidates who focus on spatial analysis of ecological processes. Candidates already in tenure track or tenured positions may be considered for the rank of Associate Professor. Review of applications will begin on November 21, 2008. The positions will be open until filled.”

    Risk Assessment Software: Spatial Risk Analyst–Podcast Interview

    In ESRI, GIS, Interviews, Spatial Analysis on September 8, 2009 at 6:12 am

    podcast_iconESRI Podcast: Rich Arata, Distribution Practice Manager, New Century Software, explains the application of GIS to risk assessment management in the gas industry. Spatial Risk Analyst combines spatial and tabular data to assess the impact of threats and analyze the risks to any facility in the gas distribution system.

    • Listen or download: MP3 [09:44 | 4.49 MB]

    Research Associate Position at the Centre for Advanced Spatial Analysis

    In Education, GIS, Modeling, Science, Spatial Analysis on September 4, 2009 at 7:33 am

    ucl“The SCALE project: (Small Changes leAd to Large Effects) Changing Energy Costs in Transport and Location Policy is an EPSRC funded research project being undertaken jointly between the UCL Centre for Advanced Spatial Analysis and UCL Centre for Transport Studies. Two Research Associate vacancies are available, one based in each department.  This advertisement relates to the CASA based post which focuses on land use transportation models. This CASA based post is funded for three years by EPSRC.  All researchers, plus the PhD student (who will be supervised by Shi Zhou in Computer Science) will interact with the team set up by CASA. We are looking for a researcher with expertise in modelling complex systems who has good skills in programming and who could develop a suite of computer programs for the land use transportation modelling effort which will underpin one arm of SCALE. We want someone who will be able to wrestle with the science, and be able to translate this into computable forms which interface with a variety of modules and data bases. Experience in GIS would be an advantage but not essential.”

    Modeling Geographic Complexity: Special Session at Association of American Geographers Annual Meeting, April 2010

    In GIS, Geography, Modeling, Science, Spatial Analysis on September 4, 2009 at 7:08 am

    aagAssociation of American Geographers Annual Meeting
    April 14-18, 2010, Washington, DC, USA

    Understanding geographical systems represents one of the greatest challenges of our time. Complexity has emerged as a useful paradigm to effectively study linked human, socioeconomic and biophysical systems at a variety of different spatial and temporal scales. As a result, descriptive and predictive models of various levels of sophistication and using mostly agents, genetic algorithms, cellular automata and neural networks are now beginning to regularly appear in the geographic literature. However, there still remains many unresolved conceptual, technical and application challenges associated with these complexity based models. The goal of this session is to focus on the following themes:

    1. Conceptual: shared and unique complexity signatures in geographic systems; existing and emerging geographical and complexity theories; epistemological and ontological influences; complexity based model designs; networks and hybrid models; linking classical and spatial statistics in complexity studies.
    2. Technical: space-time patterns and dynamics; standardizing the development and representation of complex systems; rule selection and implementation; multiple-scale interactions and structure, system evolution and self-organization; learning and adaptation; calibration, validation and verification; path-dependence; non-linearity.
    3. Applications: effectiveness of complexity models when embedded in political, institutional and socio-economic systems; human-environment interactions; earth systems science; land use science; landscape ecology; sustainability analysis.

    In order to widely disseminate the ideas emerging from this session, the organizers of the session are exploring the possibility for a special issue of a journal and /or an edited book so that authors will have the opportunity to suitably revise their presentations for publication. Priority will be given for work that has not been published, in review or in press.

    Please e-mail the abstract and key words with your expression of intent to Andrew Crooks <acrooks2@gmu.edu> by October 19th, 2009.

    Analysis and Detection of Health Disparities Using Geostatistics

    In Science, Spatial Analysis, Statistics on September 3, 2009 at 6:58 pm

    The Case of Prostate Cancer Mortality in the United States, 1970 to 1994

    “This paper presents a new geostatistical methodology that accounts for spatially varying population sizes and spatial patterns in the analysis of cancer mortality data.”

    Classifying and Symbolizing Data in ArcMap: Creating a Weather Map–Podcast

    In ESRI, Education, GIS, Spatial Analysis on September 3, 2009 at 7:09 am

    podcast_iconESRI Podcast: ArcMap provides numerous options for classifying and symbolizing your data. This discussion will explore the workflow for creating a weather map in ArcGIS including downloading, classifying, and symbolizing weather data and creating a raster surface from vector data using ArcGIS Spatial Analyst tools.

    • Listen or download: MP3 [10:06 | 4.65 MB]
    • Read the transcript [PDF]

    Qualitative GIS: A Mixed Methods Approach

    In Books, GIS, Spatial Analysis on September 3, 2009 at 7:09 am

    qual…from Amazon.com…

    “Geographic Information Systems are an essential tool for analyzing and representing quantitative spatial data. Qualitative GIS explains the recent integration of qualitative research with Geographical Information Systems.

    “Making reference to representation, analysis, and theory throughout, the text shows how to frame questions, collect data, analyze results, and represent findings in a truly integrated way. An important addition to the mixed methods literature, Qualitative GIS will be the standard reference for upper-level students and researchers using qualitative methods and Geographic Information Systems.”

    ‘Qualitative GIS is coming of age, and this definitive collection explains why it deserves broad attention. These carefully selected essays by leading researchers, organized around a broad conception of qualitative GIS that extends beyond multi-media data integration to embrace new software tools and interpretive, situated epistemologies, will push readers to rethink not only their preconceptions about qualitative GIS, but also about GI science and critical GIS. GIS researchers, practicioners, observers and users will find much to chew on here.’

    –Professor Eric Sheppard, University of Minnesota, USA

    Visualizing and Studying Disease through Maps: Podcast Interview with Dr. Tom Koch

    In ESRI, GIS, Geography, Interviews, Science, Social Science, Spatial Analysis, Visualization on September 2, 2009 at 9:45 am

    podcast_iconESRI Podcast: Dr. Tom Koch, a clinical ethicist, gerontologist, professor, and author of Cartographies of Disease: Maps, Mapping, and Medicine, describes how mapping and geospatial technologies can be used to analyze relationships concerning viral and bacterial occurrences, including the 2009 flu pandemic, H1N1.

    • Listen or download: MP3 [18:51 | 8.81 MB]

    Spatial and Temporal Analysis of H1N1 (“Swine Flu”) in the United States

    In GIS, Geography, Science, Spatial Analysis on September 1, 2009 at 3:13 pm

    …manuscript prepared for Eurosurveillance Journal…

    Applying Health Informatics Approaches to Support Public Health Risk Communication – Spatial and Temporal Analysis of H1N1 Human Infection Distribution in the U.S.

    Chiehwen Ed Hsu, PhD, MPH, Ella T. Nkhoma, PhD, Noriaki Aoki, MD, PhD, Ning Shang, Dejian Lai, PhD

    “(w)e propose a potential informatics-facilitated public health surveillance system for H1N1 risk communication. This system incorporates spatial and temporal analysis to evaluate the nature of emergency relevance of reported human cases of novel H1N1 Influenza human infection and its severity. Human cases reported in the U.S. were analyzed as of June 12, 2009, on the day when the WHO declared Level 6 pandemic flu of the H1N1 virus. It seeks to determine emergency nature of the case by excessive human cases by spatial and temporal distribution in the U.S. We evaluated the distribution trend of historical and current excess cases, and their associated geographic location and time period of occurrence by excess level. We also measured temporal variation pattern of case distribution to understand potential temporal trend of emergency relevance.”

    Interactive Online Micro-spatial Population Analysis based on GIS Estimated Building Population

    In Conferences, ESRI, Education, GIS, Spatial Analysis on September 1, 2009 at 2:43 pm

    urisaFirst Place, 2009 URISA Student Paper Competition

    Ko Ko Lwin, University of Tsukuba

    “Spatial distribution patterns of population is fully depend on landscape structures and never be a homogeneous, especially where the city has a mix of high and low-rise buildings or patched with unpopulated large spaces such as paddy fields or parks or playgrounds or governmental institutions. This will introduce some errors in population data analysis at micro-scale level. In order to eliminate these errors, we need to estimate population at building level. Spatial analysis functions using building population data is absolutely rare or absent in GIS arena because building population information is not available for public use due to privacy concerns. The goal of this paper is to introduce an online interactive micro-spatial population analysis based on building population, which was estimated by LIDAR derived Digital Volume Model (DVM) and number of floors attribute information with census tracts.”

    ArcGIS Geoprocessing: ModelBuilder–An Introduction

    In Conferences, ESRI, GIS, Modeling, Spatial Analysis, Video on August 31, 2009 at 9:01 am

    From the 2009 ESRI International User Conference last month, Dale Honeycutt and Shitij Mehtagive an overview of ModelBuilder.  [1 hour 20 minutes]

    modelb

    Applying Advanced Technology for Threat Assessment: A Case Study of the BTC Pipeline

    In GIS, Spatial Analysis on August 27, 2009 at 4:01 pm

    iags…from the Journal of Energy Security…

    “The study focuses on a risk analysis of the BTC pipeline and integrates state-of-the-art technologies for a comprehensive advanced security analysis (ASA) that includes critical issues such as the geographical and socio-political context along the BTC pipeline. This was addressed in the GIS (Geographical Information System) developed for purpose of integrating satellite imagery together with a number of map layers reflecting both physical and human factors along the BTC pipeline (road networks, topography, vegetation, population density, etc.).

    “During the course of this analysis, the BTC pipeline was sabotaged by PKK insurgents in August 6th 2008. The geographical and socio-political factors of this sabotage have been weighted and extrapolated to the whole of the pipeline by a geospatial analysis on the GIS layers. As a result, the pipeline has been segmented into several degrees of risks which may prompt additional security actions as proposed in this paper.”

    Satellites Used to Predict Infectious Disease Outbreaks

    In Imagery, Science, Spatial Analysis on August 26, 2009 at 7:37 pm

    …from Scientific American…

    “From avian flu to cholera, infectious diseases may not be able to hide for long.  Some researchers have their sights trained on predicting their every move with detailed satellite data.”

    Improving Spatial Analysis and Advancing Geographic Science in ArcGIS 9.4

    In Conferences, ESRI, GIS, GIScience, Geography, Modeling, Science, Spatial Analysis, Statistics, Temporal Analysis on August 26, 2009 at 2:49 pm

    …adapted from Jack Dangermond’s plenary talk at the ESRI International User Conference in San Diego,California in July of 2009…

    j1For me, spatial analysis is the heart of GIS. ArcGIS 9.4 makes a huge step forward in the sreas of spatial analysis and geographic science. Python, the open source scripting language that is rapidly becoming the accepted standard for scientific programming, is being integrating inside of ArcGIS. This will give you a great language to support geoprocessing and spatial analysis, and I think it will bring a lot of advances in geographic science. We’re also going to integrate other software packages for statistics, math, and modeling.

    j2At 9.4 we are adding a lot of functionality such as fuzzy overlay modeling. We’re improving the math-algebra integration. We’re radically improving raster performance for analytic operations, especially on very large data cells. We’re integrating time. And we’re introducing an ecological sampling tool, which brings a lot of geostatistics into play. All of these are examples of extending the quantitative methods that we apply.

    j3A good friend of mine once said, “For each new advance, each new technology, it’s both a technical advance but it’s also an advance in method.” And this science theorem really rings home here as we expand the analytic language of what we can do with geography.

    j4

    Spatial Analysis Aids Relocation of Javanese Rhino

    In Environmental Science, Spatial Analysis on August 26, 2009 at 9:20 am

    …from The Jakarta Post…

    “The study was aimed at assessing the geology, soil type and proximity to water in order to find suitable areas for the planned relocation of the Javanese rhino.

    “The proposed areas are adjacent to Gunung Honje, Gunung Halimun, Masigit Kareumbi and Leuweung Sancang, all of them close to the Ujung Kulon area on the western tip of Java Island.

    ““The spatial analysis suggests there is good possibility of an area on the Ujung Kulon peninsula and on Gunung Hone suitable for the Javan rhino,” the study said.”

    Spatial Analysis of Social Facts

    In Geography, Social Science, Spatial Analysis on August 26, 2009 at 9:16 am

    By Claude Grasland

    “A tentative theoretical framework derived from Tobler’s first law of geography and Blau’s multilevel structural theory of society.

    “This document presents an attempt to build a theoretical framework for the spatial analysis of social facts, derived from Tobler’s first law of geography (‘Everything is related to everything else, but near things are more related than distant things’) and Blau’s theory of macro sociology and multilevel structural analysis. At individual level four basic times of position and interaction are defined (geographical/sociological and discrete/continuous). It is then necessary to discuss the effects of scale aggregation and time dynamics on the elementary levels of position and interaction. This part is illustrated by examples about airflows between world cities in 2000 and euro coins diffusion across borders between 2002 and 2007.”

    Research Analyst – Spatial Analysis Position, University of Canterbury

    In Education, Environmental Science, GIS, Science, Social Science, Spatial Analysis on August 21, 2009 at 8:16 am

    cantThe GeoHealth Laboratory, Department of Geography, University of Canterbury invites applications for a (). This is a three-year fixed term position based in the Health and Disability Intelligence (“HDI”) Unit (part of the Ministry of Health) in Wellington and is available immediately.

    The GeoHealth Laboratory is a joint venture between the University of Canterbury (UC) and the New Zealand Ministry of Health. A number of academic staff, postdoctoral researchers, research fellows and postgraduate students who are based in or affiliated with the GeoHealth Laboratory help in providing a supportive research environment. The GeoHealth Laboratory staff are committed to undertaking policy-relevant health research and have a strong track record of publication in high quality peer reviewed journals, as well as regular contributions to various policy documents and media pieces. For further information about the lab see www.geohealth.canterbury.ac.nz/.

    The successful applicant will have training and research experience in health and , , social epidemiology and/or related discipline. Combined with strong GIS skills and good quantitative and analytical skills developed through their graduate career including at least 1-2 year relevant GIS work experience.. The appointee will be expected to perform a variety of tasks including: undertaking key GIS and spatial data analyses; providing a level of GIS and research support to staff at the HDI Unit; contributing to various health-related research projects; and contributing to the writing and dissemination of research outputs through peer reviewed publications, conferences and workshops.

    Closing Date: 2 September 2009

    Location: Wellington

    Do People Really Walk in Circles?

    In Science, Spatial Analysis on August 20, 2009 at 1:09 pm

    sciam…from Scientific American…

    “Yes, people do really walk in circles—but only when stripped of important visual clues, such as the sun or moon, according to a paper published online today in Current Biology.

    “To test the common wisdom, Jan Souman, a research scientist at the Max Planck Institute for Biological Cybernetics, and his team sent test subjects out into a German forest and the Sahara Desert to see if they could follow directions to walk in a straight line—some on sunny days others on cloudy days or at night. Subjects were monitored via GPS over the course of hours (and followed by an experimenter for safety).”

    Post-Doctoral Research Assistant: CUNY-Environmental Crossroads Initiative

    In Education, Environmental Science, GIS, Modeling, Science, Spatial Analysis, Statistics on August 19, 2009 at 1:09 pm

    RFLogoThe CUNY Environmental Cross-Roads Initiative at City University of New York seeks a post doctoral assistant to collaborate on interdisciplinary synthesis research to understand the widespread alteration of hydrologic systems over local-to-regional domains focusing on the Northeast corridor of the United States over a 500-year period (1600 to 2100). The position requires primary research into this question using a variety of approaches including modeling, statistical and/or geospatial analysis. Work will emphasize the development of a ‘digital library’–an interdisciplinary geophysical, environmental, and social science spatial data infrastructure focused on the northeast United States region. Historical and contemporary datasets related to hydrology, geology, geomorphology, economics, sociology, ecology, etc., to inform this project. Scenarios 100-years into the future will also be executed.

    The position will involve close interaction with a Synthesis Working Group drawn from several collaborating institutions to study regional watersheds and linked human-water processes, and to serve as a test-bed for ideas on how to optimally execute research synthesis in the water sciences.

    This position is supported for a 2-year period by a research grant from the National Science Foundation (NSF) and will enable the successful candidate to work within the context of a major national effort to forward hydrological sciences under the aegis of the Consortium of Universities for the Advancement of Hydrological Science (CUAHSI).  Under the routine supervision of a Senior RF Research Associate or designee, performs simple to moderately complex research, investigation, or analytic activities as part of the research team; works under varying degrees of supervision depending on the scope and complexity of the project. Assists in planning meetings, conferences, web-based communication etc. Writes abstracts. Follows protocols for gathering data, coding data or information, constructing data bases using specified technology, analyzing data, maintaining data security, and archiving data as needed. Keeps accurate, well organized data records; performs the duties of lower level positions as needed; also performs other duties as assigned. Ability to make clear, accurate observation in writing and orally; to take direction and work as part of the team as well as independently; Ability to work cooperatively with other researchers and with students.

    Salary:$52,000 to $58,000

    Core Competencies/Qualifications

    A recent PhD in Earth System Science, Hydrology, Biogeochemistry, Landscape Ecology, or related field, with extensive experience in GIS, data infrastructure development and management, computer programming and/or modeling. Experience in research project management is desired. Capacity to work in a large and diverse team at several professional levels (from students through senior academic and agency scientists). Applicants should attach: curriculum vitae; statement of research interests; contact information of three references.

    Neighborhood Food Environment, Walkability, and Obesity in NYC

    In ESRI, GIS, Science, Spatial Analysis, Statistics on August 17, 2009 at 8:09 am

    705192-fig1…from MedScape Today…

    “Density of BMI-healthy food outlets in New York City: Kernel Density Estimation (KDE) map illustrating the density of BMI-healthy food outlets. This KDE continuous surface was created with ArcGIS Spatial Analyst (ESRI, Redlands, CA), which uses a distance decay quadratic kernel function. Input processing parameters included a half-mile bandwidth and 1,545 discrete points representing the locations of supermarkets, fruit and vegetable markets, and natural food stores.”

    Tracking and Spatial Analysis of Sex Offender Movements

    In ESRI, GIS, Modeling, Spatial Analysis on August 17, 2009 at 7:24 am

    Untitled-1…from corrections.com…

    “The California Department of Corrections and Rehabilitation (CDCR) has begun tracking more than 6,000 sex offender parolees by using global positioning system (GPS) anklets. Sex offender parolees are allowed to travel only through certain areas and must keep away from other people. The GPS device lets parole agents know when parolees are somewhere they should not be by logging GPS coordinates every minute and sending coordinates to a central server every 10 minutes. This information about parolee location is compared to law enforcement incident data through crime-scene correlation reports. Regular e-mail reports keep analysts notified of any incidents that are close to an offender’s tracks in time and space. The features are accessible through an online mapping application, and analysts can review a parolee’s GPS data for up to 4 hours at a time, or view data in real time (with a 15- minute delay).

    “Keeping track of parolees’ movements can take a lot of time and law enforcement resources. Law enforcement and parole agencies need a way to sum vast amounts of spatial behavior and coordinate it with related crime information. Environmental Systems Research Institute’s (ESRI) Modelbuilder and the kernel density tool are essential for analysts who track and analyze sex offender movement data.”

    Video: ArcGIS Spatial Analyst Overview

    In ESRI, GIS, Modeling, Spatial Analysis, Video, Visualization on August 17, 2009 at 6:56 am

    This video shows how the ArcGIS Spatial Analyst dynamic modeling, advanced visualization, and statistical analysis tools can help you analyze your data to make more informed decisions.

    Video: Advanced Planning and Analysis with ArcGIS 9.3

    In ESRI, GIS, Modeling, Spatial Analysis, Video on August 16, 2009 at 6:57 am

    See a complete workflow using ModelBuilder, stepping through the initial creation of a model and the benefits of using the model, to the execution of advanced spatial analysis. Easily disseminate results to a wider audience using a simple Web mapping application.

    Part 1

    Part 2

    Spatial Analysis of Contaminated and Unused Land for Biofuel Crop Potential

    In Green Technologies, Spatial Analysis on August 13, 2009 at 7:40 am

    …from physorg.com…

    “…to maximize energy output, biofuel processing plants need to be strategically located near cropland. The team used spatial analysis to demonstrate how to find ideal locations for processing plants and how biofuel plots could be planted to maximize the contaminated water they receive.”

    Spatial Analysis and Fuel Savings

    In Conferences, ESRI, GIS, Green Technologies, Spatial Analysis, Video on August 13, 2009 at 7:29 am

    Learn how building inspectors from the City of Ft. Collins, TX, used ArcLogistics to optimize routes and work schedules to realize savings of almost $1 million annually. This video was recorded at the 2008 ESRI International User Conference.

    GIS for Archaeology: Free e-book Now Avalaible

    In Books, ESRI, Environmental Science, GIS, Modeling, Science, Social Science, Spatial Analysis on August 11, 2009 at 7:02 am

    archESRI has released a new e-book in the GIS Best practices series titled “GIS for Archaeology.”  Articles in this e-book include:

    • Protecting Archaeological Resources During an Oil Spill in Washington State
    • Archaeology, Genealogy, and GIS Meet at Columbia Cemetery
    • Reconstructing Aztec Political Geographies A Cost-Effective
    • Approach to GPS/GIS Integration for Archaeological Surveying
    • U.S. Bureau of Reclamation Administers Archaeological Sites with GIS
    • Bureau of Land Management’s Cultural Resource Database Goes Digital
    • Modeling Archaeological Sensitivity in Vermont with GIS
    • Understanding Past and Future Land Use

    “GIS for Archaeology” is available as a free PDF download.

    Research Fellow: Institute of High Performance Computing, Singapore

    In Education, Environmental Science, Social Science, Spatial Analysis, Statistics on August 10, 2009 at 11:29 am

    ihpcYou will be engaged in research and development in epidemiological analysis and modeling. You will manipulate and analyse large datasets comprising spatial-temporal information relating to infectious disease and to determine their correlations. You will conduct studies of environmental change and the impacts affecting public health; this will include conducting correspondences related to the work, evaluation and interpretation of the findings, and reporting/presentation of study results. You will assist and/or supervise database development and perform statistical analysis on data collected from research studies.

    Requirements

    • A PhD in Epidemiology, Statistics, or equivalent
    • Knowledge of a wide variety of statistical procedures applied to public health data would be advantageous including but not limited to multivariate correlation analysis, time series analysis, categorical data analysis, logistic regression, survival analysis, spatial analysis, exploratory, and graphical methods.
    • Experience in statistical procedures, data management and warehousing techniques would be an advantage
    • Possess excellent communication skills and a team player

    Contact

    Recruitment Officer
    Institute of High Performance Computing
    1 Fusionopolis Way, #16-16 Connexis
    Singapore 138632
    Email: recruitment@ihpc.a-star.edu.sg
    Web: http://www.ihpc.a-star.edu.sg/

    Peter Cullen Postgraduate Scholarship: Managing Water Resources in Australia

    In Earth Systems Science, Education, Environmental Science, Modeling, Scholarships, Social Science, Spatial Analysis, Statistics on August 10, 2009 at 9:27 am

    nswThe NSW Government has developed a postgraduate scholarship in honour of the late Professor Peter Cullen AO FTSE. Professor Cullen contributed significantly to a new way of thinking about managing water resources in Australia, and NSW.

    “The scholarship will honour the work and achievements of Professor Cullen, supporting those who have been inspired by his leadership and vision for water.”    –Premier of NSW, Nathan Rees

    Funds available

    A three year scholarship of up to $20,000 p.a. will be awarded each year in February. Funds totalling $60,000 will be available to the successful student over the three year period, but with prior written request the allocated funds could be extended to a fourth year. The scholarship may form part of a stipend and/or support student research. The scholarship can be used to pay for such things as equipment, field expenses and sample processing. These conditions will be further defined in the scholarship agreement between the NSW Government and the University/Research Organisation.

    Selection criteria
    There are a number of criteria upon which students will be assessed. They must show they:

    • are a first year PhD research student enrolled at an Australian university
    • are an Australian citizen or have permanent residency
    • can demonstrate expertise in one of the following disciplines: bio-physical sciences, mathematics, statistics, information sciences, spatial analysis and modelling. Students with expertise in law, resource management, social sciences, and resource economics are also eligible
    • can demonstrate academic excellence in their chosen field (a copy of their full academic transcript
      must be supplied)
    • can provide written proof of their supervisor’s support, indicating how a scholar may benefit from
      participation in the Peter Cullen Scholarship.

    The Proposed Project

    The student’s proposed project will be assessed on how well they:

    • Demonstrate how the project will lead to an improvement in our understanding of how rivers, groundwater, wetlands and estuaries function
    • Demonstrate the relevance of the research to water management in NSW
    • Demonstrate how the project improves the linkages between water science and water management in NSW
    • Demonstrate how the project is innovative.

    Peter Cullen Postgraduate Scholarship

    The following additional conditions apply:

    • Supervisor endorsement will be necessary
    • Employer endorsement will be required
    • Preference will be given to full-time students
    • The top up of existing scholarships may be considered.

    Assessment of applications

    A selection panel will be convened by the Department with industry partners. The selection panel will undertake an initial assessment of applications and generate a short list of eligible applicants. The short listed applicants will be required to attend an interview and/or make a formal presentation of the proposed research to the selection panel. The selection panel will make a recommendation to the Minister.

    Reporting


    The successful applicants will be required to submit an annual progress report to remain eligible for the scholarship. The progress report will include a financial report on expenditure, a list of project activity, and a report of project outcomes.

    All communication for the project will be required to acknowledge the scholarship.

    Additionally, the successful applicant will be required to give an annual presentation to funding partners and NSW Government scientists.

    Important dates
    Applications for the 2010 scholarship will open 01 August 2009, and close 28 August 2009.

    Application

    All application forms and documents should be sent to:
    Peter Cullen Scholarships
    C/- Human Resources, Department of Water and Energy
    PO Box 3720, Parramatta NSW 2124
    By email information@dwe.nsw.gov.au

    Enquiries

    Simon Williams
    Scholarship Convenor
    Department of Water and Energy
    Telephone 02 4224 9687 or 0413 601 500
    Email simon.williams@dnr.nsw.gov.au
    Source http://www.jason.edu.au/pdf/1248253296.pdf

    Science is Being Transformed by Analytics

    In Science, Spatial Analysis on August 10, 2009 at 6:38 am

    right_mayThe Q3 2009 issue of sascom magazine features an article by futurist Thorton May titled “Top 8 Things Transformed by Analytics in 2009.”  One of the top eight is science.  Here’s an excerpt:

    “In 2005, Microsoft assembled 30 of the world’s greatest scientists from 12 nationalities to examine the challenges facing scientists in the future, paying particular attention to the impact of computer science on the sciences. The study, called 2020 Science, concluded, “We are starting to give birth to ‘new kinds’ of science and possibly a new economic era of ‘science-based innovation’ that could create new kinds of high-tech sectors that we can barely imagine today, just as we could hardly have imagined today’s rapidly growing ‘genomics’ sector happening two decades ago.”

    “Today, science may be giving way to ‘open science.’ While openness has always been an integral part of science, with findings presented in journals and conferences, the open-science movement encourages scientists to share work-in-process long before they present results. This concept has the potential to speed discoveries, increase collaboration and transform the field in unforeseen ways.”

    Read the article

    PhD Position: Spatial Analysis of Late Neolithic Settlements

    In Education, GIS, Modeling, Spatial Analysis on July 27, 2009 at 4:19 pm

    Available from October 1st, 2009, closing date for applications: September 1st, 2009.

    Subject

    “Spatial analysis of Late Neolithic settlements in the province of Noord-Holland (The Netherlands) and interregional comparison.”

    This PhD position is part of the project Unlocking Noord-Holland’s Late Neolithic Treasure Chest. This project is co financed by the the Netherlands Organisation for Scientific Research (NWO) and administered by the State Service for Cultural Heritage (RCE). The project comprises five studies. Two PhD’s are based at the Groningen University (spatial analysis, ceramics), one PhD at Leiden University (flint). The studies on archaeobotany and archaeozoology are carried out by researchers from the state service and private firms.

    Introduction

    In the second half of the past century, and the 1970-1990′s in particular, excavations were conducted at a series of Late Neolithic settlements belonging to the Single Grave Culture (SGC) (c. 2900-2500 cal BC) in the province of Noord-Holland (Kop van Noord-Holland, De Gouw). These excavations have demonstrated the exceptional quality of the sites, especially thanks to the good preservation of organic materials. In significant contrast to the generally poor and heavily biased archaeological record of the SGC elsewhere in the Netherlands, the rich body of excavation data potentially permits the development of models about settlement variability, the use and role of material culture, as well as landscape use. So far, the excavation data from the various sites have never been analysed integrally. Hence, any ‘models’ of cultural dynamics in the SGC are based on very incomplete data. This project aims to unlock and integrate cultural/ecological information and research data in order to provide a sound basis for cultural modeling and development of heritage management strategies. We will thereby obtain a better understanding of site variability in relation to landscape use, subsistence strategies and the material world of the inhabitants. It provides an opportunity to study a micro-region within the wider SGC culture, so far largely known from its burial context. Its place in relation to the communities in the central and eastern parts of the Netherlands can be assessed and possible long-distance contacts with related Corded Ware groups elsewhere can be studied, addressing the debate on the apparent uniformity of the Corded Ware complex.

    Research topics

    The study of settlement variability focuses on the identification of functional differences between sites. For this it is necessary to characterise the sites in terms of settlement size, intra-site spatial organisation and functional variability, as well as the duration of occupation (permanent versus seasonal). Insight into these aspects will be obtained through the analysis of cultural and palaeoecological remains. Also, efforts will be made to draw inferences on group composition of settlement inhabitants (sex, age) from material remains and physical anthropological data. For the interpretation of spatial patterns in terms of behaviourally meaningful processes, data will be analysed in an interdisciplinary fashion, in relation to the spatially referenced excavation recordings of objects, features and lithological layers.

    Spatial analysis will play a pivotal role throughout the project. The work will start with the digitising of excavation plans and linking of find numbers in order to provide for a spatially referenced environment for further analyses. The availability of such an environment is also of importance for the sampling of materials in other research modules. The analysis of spatial data will next focus on research at various levels: identification and characterisation of structures (e.g. house plans, barns, fences, pits, and wells), characterisation of spatial patterns in find distributions, and development of spatial models of site formation dynamics. This multi-level approach contributes to the evaluation and interpretation of research results in the other modules and provides a sound basis for syntheses at site level. It will also contribute to the compilation of models for site formation that are not restricted to the SGC sites in Noord-Holland, but extend to other Neolithic wetland sites in the Netherlands.

    The candidate needs affinity with computer-based modelling, spatial analysis and site formation processes.

    2009 ESRI User Conference Proceedings Now Online

    In Climate Change, Conferences, ESRI, Education, Environmental Science, GIS, GIScience, Geography, Imagery, Modeling, Science, Social Science, Spatial Analysis, Statistics, Temporal Analysis on July 24, 2009 at 6:49 pm

    GIS Helps Evaluate Soil’s Ability to Retain Earth’s Carbon

    In Climate Change, Environmental Science, GIS, Science, Spatial Analysis on July 23, 2009 at 5:01 pm

    …from Environmental Expert…

    “The study evaluated AAAWD of Ca2+ from 1994 to 2003 within the continental United States by soil order, using spatial analysis of Ca2+ wet deposition data obtained from the National Atmospheric Deposition Program (NADP) and the State Soil Geographic (STATSGO) Database from the Natural Resources Conservation Service of the U.S. Department of Agriculture. Using geographic information system (GIS) software, spatial data layers were developed and averaged to create a final Ca2+ wet deposition map layer. The total Ca2+ wet deposition per soil order (in kg) was then calculated by combining the final average Ca2+ wet deposition map layer with the generalized soil order data layer.”

    Spatial Analysis of Illegal Drug Use using Wastewater Samples

    In Science, Spatial Analysis on July 16, 2009 at 5:00 am

    …from Science Codex…

    “A team of researchers has mapped patterns of illicit drug use across the state of Oregon using a method of sampling municipal wastewater before it is treated.

    “Their findings provide a one-day snapshot of drug excretion that can be used to better understand patterns of drug use in multiple municipalities over time. Municipal water treatment facilities across Oregon volunteered for the study to help further the development of this methodology as a proactive tool for health officials.”

    Spatio-temporal Analysis of Human West Nile Virus in the United States

    In Science, Spatial Analysis, Temporal Analysis on July 15, 2009 at 9:31 am

    plague…from the International Journal of Health Geographics 2009, 8:36…

    “Spatio-temporal cluster analysis of county-based human West Nile virus incidence in the continental United States”

    By Ramanathan Sugumaran, Scott R Larson, and John P DeGroote

    “Background: West Nile virus (WNV) is a vector-borne illness that can severely affect human health. After introduction on the East Coast in 1999, the virus quickly spread and became established across the continental United States. However, there have been significant variations in levels of human WNV incidence spatially and temporally. In order to quantify these variations, we used Kulldorff’s spatial scan statistic and Anselin’s Local Moran’s I statistic to uncover spatial clustering of human WNV incidence at the county level in the continental United States from 2002-2008. These two methods were applied with varying analysis thresholds in order to evaluate sensitivity of clusters identified.

    “Results: The spatial scan and Local Moran’s I statistics revealed several consistent, important clusters or hot-spots with significant year-to-year variation. In 2002, before the pathogen had spread throughout the country, there were significant regional clusters in the upper Midwest and in Louisiana and Mississippi. The largest and most consistent area of clustering throughout the study period was in the Northern Great Plains region including large portions of Nebraska, South Dakota, and North Dakota, and significant sections of Colorado, Wyoming, and Montana. In 2006, a very strong cluster centered in southwest Idaho was prominent. Both the spatial scan statistic and the Local Moran’s I statistic were sensitive to the choice of input parameters.

    “Conclusions: Significant spatial clustering of human WNV incidence has been demonstrated in the continental United States from 2002-2008. The two techniques were not always consistent in the location and size of clusters identified. Although there was significant inter-annual variation, consistent areas of clustering, with the most persistent and evident being in the Northern Great Plains, were demonstrated. Given the wide variety of mosquito species responsible and the environmental conditions they require, further spatio-temporal clustering analyses on a regional level is warranted.”

    Spatial Analysis of Epidemic Outbreak Patterns of Diarrhea in Thailand

    In GIS, Science, Spatial Analysis, Statistics on July 15, 2009 at 9:00 am

    plague…from the International Journal of Health Geographics 2009, 8:36…

    “Exploring Spatial Patterns and Hotspots of Diarrhea in Chiang Mai, Thailand”

    By Nakarin Chaikaew, Nitin Tripathi, and Marc Souris

    “Diarrhea is a major public health problem in Thailand. The Ministry of Public Health, Thailand, has been trying to monitor and control this disease for many years.

    “The methodology and the results from this study could be useful for public health officers to develop a system to monitor and prevent diarrhea outbreaks.

    “Methods:  The objective of this study was to analyse the epidemic outbreak patterns of diarrhea in Chiang Mai province, Northern Thailand, in terms of their geographical distributions and hotspot identification. The data of patients with diarrhea at village level and the 2001-2006 population censuses were collected to achieve the objective.

    “Spatial analysis, using geographic information systems (GIS) and other methods, was used to uncover the hidden phenomena from the data. In the data analysis section, spatial statistics such as quadrant analysis (QA), nearest neighbour analysis (NNA), and spatial autocorrelation analysis (SAA), were used to identify the spatial patterns of diarrhea inChiang Mai province.

    “In addition, local indicators of spatial association (LISA) and kernel density (KD) estimation were used to detect diarrhea hotspots using data at village level.

    “Results:  The hotspot maps produced by the LISA and KD techniques showed spatial trend patterns of diarrhea diffusion. Villages in the middle and northern regions revealed higher incidences.

    “Also, the spatial patterns of diarrhea during the years 2001 and 2006 were found to represent spatially clustered patterns, both at global and local scales.

    “Conclusion:  Spatial analysis methods in GIS revealed the spatial patterns and hotspots of diarrhea in Chiang Mai province from the year 2001 to 2006. To implement specific and geographically appropriate public health risk-reduction programs, the use of such spatial analysis tools may become an integral component in the epidemiologic description, analysis, and risk assessment of diarrhea.”

    Spatial Analysis Identifies Octocoral Hotspots in the Gulf of Mexico

    In Environmental Science, GIS, Science, Spatial Analysis on July 15, 2009 at 8:53 am

    peters_dissertation_adj1-300x225…from Deep Sea News…

    “Distribution and Diversity of Octocorals in the Gulf of Mexico,” by Peter J. Etnoyer

    COASTAL AND MARINE SYSTEM SCIENCE PROGRAM

    DEPARTMENT OF PHYSICAL AND ENVIRONMENTAL SCIENCES

    TEXAS A&M UNIVERSITY-CORPUS CHRISTI

    “This dissertation tested the null hypothesis of no difference in octocoral assemblages at the three spatial scales (referred to as basin, region, and site scale) through meta-analysis of two large, original datasets. Univariate and multivariate techniques were used to compare and contrast depth zones, regions, and sites (six outer continental shelf banks) within a GIS framework. Spatial analysis techniques were used to identify octocoral ‘hotspots’ within Flower Garden Banks National Marine Sanctuary.”

    Spatial Analysis in Epidemiology

    In GIS, Geography, Modeling, Science, Spatial Analysis, Statistics, Visualization on July 13, 2009 at 8:30 am

    51EveiROHHLby Mark Stevenson, Kim B. Stevens, David J. Rogers, and Archie C.A. Clements

    This book provides a practical, comprehensive and up-to-date overview of the use of spatial statistics in epidemiology – the study of the incidence and distribution of diseases. Used appropriately, spatial analytical methods in conjunction with GIS and remotely sensed data can provide significant insights into the biological patterns and processes that underlie disease transmission. In turn, these can be used to understand and predict disease prevalence. This user-friendly text brings together the specialised and widely-dispersed literature on spatial analysis to make these methodological tools accessible to epidemiologists for the first time.With its focus is on application rather than theory, Spatial Analysis in Epidemiology includes a wide range of examples taken from both medical (human) and veterinary (animal) disciplines, and describes both infectious diseases and non-infectious conditions. Furthermore, it provides worked examples of methodologies using a single data set from the same disease example throughout, and is structured to follow the logical sequence of description of spatial data, visualisation, exploration, modelling and decision support. This accessible text is aimed at graduate students and researchers dealing with spatial data in the fields of epidemiology (both medical and veterinary), ecology, zoology and parasitology, environmental science, geography, and statistics.

    Using Geostatistical Analyst for Analysis of California Air Quality

    In ESRI, Environmental Science, GIS, Modeling, Science, Spatial Analysis, Statistics on July 8, 2009 at 1:14 pm

    caaqSouthern California experiences some of the worst air quality in the United States.  Konstantin Krivoruchko used air quality data collected by the California Air resources Board, Air Quality Data Branch, Statistical and Analytical Services Section, beginning in 1980 to showcase spatial statistical air quality data analysis using the Geostatistical Analyst extension to ArcGIS.

    Spatial Analysis of Urban Tree Canopy for Brunswick, Maryland

    In Environmental Science, Imagery, Science, Spatial Analysis on July 8, 2009 at 6:48 am

    uvm…from The Frederick News-Post…

    “Tree canopy cover in Brunswick is good compared to Frederick , and even when compared with the cities of Baltimore and Washington.

    “It stands at 38 percent, according to a recent study by the University of Vermont. That means 38 percent of land area in Brunswick has shade provided by trees, known as urban tree canopy.

    “The University of Vermont conducted the study using satellite imagery taken in 2007, combined with LiDAR, which is similar to radar. DNR commissioned the imagery for the entire state. UVM’s Spatial Analysis Laboratory does the analysis in consultation with the U.S. Forest Service Northern Research Station.”

    Spatial Analysis of Somali Pirate Activity

    In Geography, Spatial Analysis on July 7, 2009 at 6:36 am

    piratesUNOSAT has released a report titled “Analysis of Somali Pirate Activity in 2009” covering the time frame of 01 January 2009 to 20 April 2009. Among the findings: the overall hijacking success rate for this period of 2009 was 23% (down from 40% in 2008), and the distance from the coast has increased over the last year.

    Spatial Analysis of Instream Nitrogen Loading to Streams in the Southeast United States

    In Environmental Science, Modeling, Science, Spatial Analysis on July 1, 2009 at 6:47 am

    wileycoverimage…from the journal Hydrological Processes, published online: 18 Jun 2009…

    “Understanding how nitrogen transport across the landscape varies with landscape characteristics is important for developing sound nitrogen management policies. We used a spatially referenced regression analysis (SPARROW) to examine landscape characteristics influencing delivery of nitrogen from sources in a watershed to stream channels. Modelled landscape delivery ratio varies widely (by a factor of 4) among watersheds in the southeastern United States - higher in the western part (Tennessee, Alabama, and Mississippi) than in the eastern part, and the average value for the region is lower compared to other parts of the nation. When we model landscape delivery ratio as a continuous function of local-scale landscape characteristics, we estimate a spatial pattern that varies as a function of soil and climate characteristics but exhibits spatial structure in residuals (observed load minus predicted load). The spatial pattern of modelled landscape delivery ratio and the spatial pattern of residuals coincide spatially with Level III ecoregions and also with hydrologic landscape regions. Subsequent incorporation into the model of these frameworks as regional scale variables improves estimation of landscape delivery ratio, evidenced by reduced spatial bias in residuals, and suggests that cross-scale processes affect nitrogen attenuation on the landscape. The model-fitted coefficient values are logically consistent with the hypothesis that broad-scale classifications of hydrologic response help to explain differential rates of nitrogen attenuation, controlling for local-scale landscape characteristics. Negative model coefficients for hydrologic landscape regions where the primary flow path is shallow ground water suggest that a lower fraction of nitrogen mass will be delivered to streams; this relation is reversed for regions where the primary flow path is overland flow.”

    ESRI UC Q & A: What Is Being Added to ArcGIS to Support the Work of Science?

    In ESRI, GIS, GIScience, Modeling, Spatial Analysis, Statistics on July 1, 2009 at 6:33 am

    uc20091…from the 2009 ESRI UC Q & A…

    The principle that GI science underlies all our software development and consulting projects is central to ESRI’s work. Some of the main areas in which science is most easily seen include the following:

    • Spatial Statistics: new spatial statistics tools have been added incrementally to the geoprocessing tool boxes in ArcGIS. For example, 9.3 has a new geographically-weighted regression tool to analyze the geographic relationship between two or more variables.
    • Geoprocessing: improvements and new geoprocessing tools provide many opportunities for scientific analysis with ArcGIS. There are improved contouring and zonal histogram tools, several performance enhancements, and some framework changes in 9.3 that enhance the user experience.
    • Cartography: the cartographic capabilities of ArcGIS have improved significantly in recent releases. The ESRI Mapping Center blog http://mappingcenter.esri.com/ has a substantial amount of cartographic science. Watch for a similar geoprocessing blog coming soon.
    • 3D: editing, analyzing and viewing 3D GI is a very hot area right now. ESRI is pushing ahead aggressively in enhancing the 3D capabilities of ArcGIS. Now that ArcGIS 9.3 is shipping this is a major focus for R&D.
    • Data Modeling: information is only as good as the representation and storage model that is used to organize it. For this reason ESRI has invested heavily in the past few years on working with communities of users to create standardized data models for different geographic domains (water, forestry, geology, marine, etc.). These are all published on-line at http://support.esri.com/index.cfm?fa=downloads.datamodels.gateway

    ESRI UC Q & A: What is the Concept Behind the User Conference Theme: GIS–Designing our Future?

    In Conferences, Design, ESRI, Environmental Science, GIS, Spatial Analysis on July 1, 2009 at 6:23 am

    …from the 2009 ESRI UC Q & A…

    Our world is increasingly influenced by human activities. There is a growing awareness that population growth, land use development, and natural resource utilization are now affecting the environment and the ability of life on the planet to be sustainable. As geographers, we know that our world is also a highly interconnected network. What we do in one place often sets off a chain of consequences. This is evidenced by global climate change, loss in biodiversity, and the increasing conflict between human land use and the natural landscape.

    uc20091Clearly, we as humans need to better understand these patterns; the connection between our actions and the consequences they create. Taking responsibility for our future will require new approaches that integrate our best science and technology with our most creative thinking.

    GIS and Designing our Future

    For decades, GIS technology and GIS professionals have helped integrate, analyze, and visualize geographic information and knowledge. This has resulted in thousands of GIS applications benefiting nearly every field. However, GIS has fallen short in the area of being fully integrated with how people do design work and make decisions that change geography.

    People who do this type of design work come from many different fields (planners, foresters, engineers, and dozens of others). While they use a wide variety of design techniques and methods, they all use geography as a common framework.

    Geographic problem solving is complicated. It requires geographic information as well as a creative design process that synthesizes this information and creates a plan. Traditionally, geographic design (regardless of scale) used maps and sketches as a basis for laying out alternative plans. These maps were typically evaluated and communicated as part of a process for decision making. Obvious examples include land use or transportation planning, however this approach to design and decision making is used in nearly every field and organization.

    Design and Human Behavior

    Many consider “design” as something that pertains only to the world of the specialist (architects, artists, engineers, etc.); however, the concepts and processes of design apply broadly to almost all human behavior. Human beings design all sorts of things, from their careers to relationships and even their lifestyles. We design our living spaces, combinations of clothes to wear, how to present ourselves, and how to get our ideas across.

    Good design starts with a conscious process of getting clear on the end objective (i.e. the creation of some sort of entity or outcome). This is typically followed by visualizing and evaluating the consequences of alternatives. Usually, this process is iterative and involves inductive and deductive reasoning together with a creative act or inspiration that results in a solution.

    Design with Nature

    Many ecologists, environmental planners, and geographers have long advocated integrating geographic information into the planning and design process as a basis for creating better land management and sustainable environments. Ian McHarg popularized this idea with his book Design with Nature. The principal idea is that people who make geographic decisions should consciously and systematically consider all the factors—physical, social, economic, and biological—as part of their decision making process. These factors should guide both where and how development should take place and also be used to evaluate alternative plans and scenarios.

    GeoDesign Process

    In the 1990s, Dr. Carl Steinitz, a Harvard professor of urban planning and landscape architecture, outlined a conceptual framework for how GIS could be integrated with geographic design and planning. His methodology includes six steps:

    Step 1. Inventory and measurement of geography

    Step 2. Geographic analysis (landscape process modeling)

    Step 3. Suitability and capability analysis (creating interpretive maps)

    Step 4. Designing alternative plans (using sketching for laying out plans/scenarios for the future)

    Step 5. Evaluation of impacts resulting from alternative designs

    Step 6. Decision making regarding the best plan

    Today, GIS supports the creation and management of large collections of geographic data (step 1) and the ability to model landscape and cultural processes using advanced models (step 2). This modeling and mapping capability can also be used to determine the most suitable and capable locations for selected facilities or land use (step 3).

    However, it is in designing alternative plans (step 4) where existing GIS technology is limited today. Creating something like a land use plan or forest management plan requires a design process where alternative combinations of spatial uses can be easily sketched out and quickly evaluated. These designs need to consider the suitability and capability of the geography as well as the optimal spatial arrangements created by a designer.

    GIS Technology and GeoDesign

    This year, ESRI is extending our GIS technology to better support the geographic design process. Specifically, we are adding tools to do interactive design sketching on top of GIS output maps (i.e. step 4 in Dr. Steinitz’s model). This will give users the ability to do not only geographic design and sketching, but also easily evaluate and refine these designs based on feedback given by the spatial analysis and reporting tools of a GIS (step 5).

    We believe these design and sketching tools will provide a strong and necessary first step for supporting a new GeoDesign field. This GIS-based approach will strengthen the ability to directly integrate geographic knowledge into the way we plan, make decisions and evaluate consequences. It will extend far beyond the traditional design community, affecting virtually all organizations making geographic decisions.

    GIS Professionals will be Required

    Clearly, widespread adoption of this GeoDesign vision could significantly affect our future. This will not happen automatically, nor will it be driven simply by the creation of this new technology. It will take vision, the development of new methodologies, continued dedication, and hard work to extend GIS into this new field. The results, however, will be important. They promise to change our process for designing our future with methods that integrate all the factors necessary for creating a sustainable world.

    For more information on GeoDesign, read the following articles in ArcNews:

    Jim Tobias Building a Web-based Mapping System for a Tuberculosis Genotyping Information Management System (5QaG&S):

    In GIS, Interviews, Modeling, Science, Spatial Analysis on June 29, 2009 at 7:50 am

    jimtobiasWelcome to the first installment of GISandScience.com’s Five Questions about GIS and Science (5QaG&S).

    GISandScience.com: Who are you and what do you do?

    Jim Tobias: Jim Tobias, MS, GISP. I am currently building a web-based mapping system for a Tuberculosis (TB) Genotyping Information Management System for the US Centers for Disease Control and Prevention.

    GISandScience.com: How did you get started with geospatial technology?

    Jim Tobias: I started with geospatial technology in 1992 with NOAA and was supporting marine mammal research in the Gulf of Mexico and Caribbean.

    GISandScience.com: How does geospatial technology help you do your job / scientific work?

    Jim Tobias: Geospatial technology is critical to disease control and prevention and I am working to re-ignite interest in mapping in the spirit of Dr. John Snow and his investigations of cholera in London during the 1854 outbreak.

    GISandScience.com: How important is a formal process/methodology (for example, the scientific method; the geographic approach) when using geospatial technology in your scientific work?

    Jim Tobias: Perhaps the greatest part of the ArcGIS software is the ModelBuilder and the ability to build workflows with standard inputs, processes, and outputs that can all reside within a single geodatabase. This speaks to the Scientific Method and allows researchers to run analyses and then zip and ship those inputs, models, and outputs to other researchers where experiments can be replicated, vetted, and examined with transparency of process.

    GISandScience.com: What features or capabilities would make geospatial technology even more valuable for scientific work?

    Jim Tobias: The Model Builder should be expanded and should begin to offer a full visual programming environment such as Orange Data Mining tools.  The Orange Data Mining tools allow visual programming of drag-and-drop Python widgets that encapsulate analytic methods in the spirit of Dr. John Tukey and his Exploratory Data Analysis. The Python widgets can be strung together visually and used to create programs that I would challenge a hard-coding programmer to build in several weeks. It is possible to build very robust visual EDA and ESDA models and workflows and applications within a matter of 15 minutes using the Orange Canvas and visual programming techniques. These models and applications can be rapidly shared and are all Python and so one begins to build a Swiss watch with transparent gears that any scientist can examine, modify, and a framework to build upon for future analytics. A similar environment is the KNIME and the TAVERNA project. These folks have all recognized that the pace of science can be accelerated and built within an open, transparent, and replicable environment that caters to the Scientific Method.

    If you are a scientist working with geospatial technologies and would like to participate is the 5QaG&S interview series, please email me at martz(at)esri(dot)com.

    Spatial Analysis of Trends in Extreme Precipitation Events in High-Resolution Climate Model Results and Observations for Germany

    In Climate Change, Modeling, Spatial Analysis, Statistics on June 29, 2009 at 7:16 am

    jgrBy L. Tomassini and D. Jacob, Regional Climate Modeling, Max Planck Institute for Meteorology, Hamburg, Germany.

    From J. Geophys. Res., 114.

    A statistical extreme value analysis is applied to very high-resolution climate model results and observations encompassing the area of Germany. Two control runs representing the current climate, as well as three scenario simulations of the regional climate model REMO, are investigated. The control runs were compared against high-resolution observations. The analysis is divided into two main parts: first trends in extreme quantiles of daily precipitation totals are estimated in a station-by-station analysis. In the second part, the spatial characteristics of the estimated trends in heavy rainfall are investigated over the area of Germany by fitting a parametric geostatistical model to these trends. The rule of thumb of estimating trends in extreme quantiles of heavy precipitation based on the Clausius-Clapeyron relation, about 6.5% per 1°C temperature increase, has been roughly confirmed for Germany by our study with respect to the observations, but the climate model computes weaker trends. In the control simulations, the climate model tends to underestimate trends in heavy rainfall compared to observations. In the scenario simulations, positive trends prevail (as in the observations). They are, however, relatively small when set in relation to the uncertainties. The trends become significantly positive to a larger spatial extent only in the A2 scenario simulation. The estimated shape of the extreme value distributions does not change significantly in the scenario simulations compared to the climate model control runs. The parameter estimates for the geostatistical model for the trends in extreme quantiles of daily precipitation sums are rather uncertain. The most striking feature of the analysis is a reduction of the spatial variance of the trends over the considered area of Germany in the scenario simulations compared to observations and, in particular, the climate model control runs.

    Spatial Analysis of Plague in California: Niche Modeling Predictions of the Current Distribution and Potential Response to Climate Change

    In Climate Change, GIS, Modeling, Science, Spatial Analysis on June 29, 2009 at 7:03 am

    plagueBy Ashley Holt, Daniel Salkeld, Curtis Fritz, James Tucker, and Peng Gong.

    From the International Journal of Health Geographics, 2009, 8:38.

    Background
    Plague, caused by the bacterium Yersinia pestis, is a public and wildlife health concern in California and the western United States. This study explores the spatial characteristics of positive plague samples in California and tests Maxent, a machine-learning method that can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (Spermophilus beecheyi) as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC) statistics. Additionally, model results were compared to locations of positive and negative coyote (Canis latrans) samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance.

    Results
    Models of plague activity in California ground squirrels, based on recent climate conditions, accurately identified case locations (AUC of 0.913 to 0.948) and were significantly correlated with coyote samples. The final models were used to identify potential plague risk areas based on an ensemble of six future climate scenarios. These models suggest that by 2050, climate conditions may reduce plague risk in the southern parts of California and increase risk along the northern coast and Sierras.

    Conclusions
    Because different modeling approaches can yield substantially different results, care should be taken when interpreting future model predictions. Nonetheless, niche modeling can be a useful tool for exploring and mapping the potential response of plague activity to climate change. The final models in this study were used to identify potential plague risk areas based on an ensemble of six future climate scenarios, which can help public managers decide where to allocate surveillance resources. In addition, Maxent model results were significantly correlated with coyote samples, indicating that carnivore surveillance programs will continue to be important for tracking the response of plague to future climate conditions.

    Books about Geostatistics and Spatial Statistics

    In GIS, Spatial Analysis on June 23, 2009 at 8:10 am

    Treeline Ecology and Spatial Analysis: Post-Doctoral Research Position

    In Education, Environmental Science, GIS, Spatial Analysis, Statistics on June 18, 2009 at 5:15 pm

    slflogoApplications are invited for a post-doctoral position in treeline ecology and spatial analysis. The successful candidate will work primarily on analyzing existing long-term ecological data from the Stillberg treeline research site in Davos, Switzerland and on publishing results from this analysis. The goals of the project include an improved understanding of tree growth at treeline and the role of subalpine forests in avalanche protection. Available data sets include monitoring data of a systematic afforestation with 92’000 trees planted in 1975 and a large number of spatially and temporally high resolution data of climate and other environmental variables. Depending on the interests of the candidate, she or he will complement these unique data sets with additional experiments.

    Candidates should have expertise in spatial analysis with GIS, strong statistical and writing skills and interest in treeline ecology. A background in dendroecology and/or spatial modelling would be an asset. A completed (or imminent) Ph.D. in forest ecology or a closely related field is required.

    Our group is part of the Swiss Federal Institute for Forest, Snow and Landscape Research WSL and the Institute for Snow and Avalanche Research, SLF in Davos. This position is funded for two years with a possibility for a third year of funding. The salary is approximately 66’000 CHF per year.

    To apply, please submit your application (cover letter describing your background and interest in the position and your CV including photo and list of publications) using reference number 594 to Mrs. Madleine Oberhänsli, Human Resources SLF, Flüelastrasse 11,7260 Davos Dorf, Switzerland. For further information please contact Dr. Peter Bebi, SLF, e-mail: b…@slf.ch tel. ++41 81 417 02 73.

    Spatial Statistics and Geostatistics Resources

    In Conferences, GIS, Science, Spatial Analysis, Statistics on June 18, 2009 at 12:58 pm

    Articles and Blog Posts

    Books

    Education

    Conferences

    An Introduction to Using Regression Analysis with Spatial Data

    In ESRI, GIS, Spatial Analysis, Statistics on June 15, 2009 at 11:49 am

    laurenESRI’s Lauren Scott, Geoprocessing Spatial Statistics Product Engineer, and Monica Pratt, editor of ArcUser magazine, have written an excellent introduction to using regression analysis with spatial data in the Spring 2009 issue of ArcUser.

    GIS and Earth Systems Modeling

    In Earth Systems Engineering, Earth Systems Management, Earth Systems Science, Environmental Science, GIS, Modeling, Science, Spatial Analysis on June 5, 2009 at 6:30 am

    An ever-growing number of models currently exist for abstracting, simulating, and understanding complex details of physical, biological, and social systems and subsystems.   The domains of the individual modeling packages vary widely, from soils to hydrology, from socioeconomics to land-use transportation.  While much progress has been made in recent years to develop models to help us to better understand our world, there is still much more to be done—especially in the area of integration.  As we gain more detailed understanding of different granular systems and their components, the challenge in addressing complex issues such as global climate change is coupling these models together to gain a more complete picture.  The combination of powerful hardware, sophisticated software, and increased human knowledge have all contributed to better models and more accurate simulations, but a GIS-based framework for integrating these disparate representations of past, present, and future states is key to understanding the whole earth.

    The Earth System Modeling Framework (ESMF) is an open source collaborative project co-sponsored by the U.S. Department of Defense, NASA, the National Science Foundation, and the National Oceanic and Atmospheric Administration (NOAA).  The goal of the ESMF project is to build “…high-performance, flexible software infrastructure to increase ease of use, performance portability, interoperability, and reuse in climate, numerical weather prediction, data assimilation, and other Earth science applications.”

    A key component is definition of an architecture for coupling together of disparate modeling systems, as well as providing support of new, framework-complaint models.  A core principle of the ESMF framework is the deconstruction of complex models into small components defined by standards such that they can be quickly and easily assembled in different ways to create new models.

    One of the key tenants of ESMF is interagency collaboration—the framework streamlines and simplifies dialog and model/code sharing between analysts and modelers across a wide range of U.S. government agencies.  The end result is much more comprehensive model views of climate impacts.   However, ESMF is primarily focused on sharing of code and models, not data and workflows.

    Integrating Models with GIS

    GIS itself is an incredibly valuable tool for spatial analysis and modeling, but there are a many standalone models available designed for highly specialized, domain-specific modeling, analysis, and problem solving.   Most domain-specific models are not yet and probably never will be fully implemented in a GIS framework; however, the spatial display, analysis, and data management capabilities of GIS can still be utilized to greatly streamline almost any modeling workflow.  The diagram below shows an example of how GIS provides a comprehensive framework for a highway noise modeling workflow.

    model1

    Using GIS for noise model workflow management and post-modeling support.

    The diagram below shows a more comprehensive modeling framework where GIS is used for workflow management and post-modeling support for multiple domain-specific models; in addition, outputs from multiple models can be compared, analyzed, and modeled within the GIS system itself.  Such a GIS-based framework offers a comprehensive environment for modeling across complex earth systems.

    model2

    A GIS-based framework integrating multiple domain-specific models and performing multidisciplinary modeling.

    Creating a framework that successfully brings together and manages a plethora of data sources and modeling systems to tackle the most pressing environmental issues of our time is surely a monumental challenge, but it is a challenge for which GIS is well suited.  Once the data and technology framework is in place and a clear workflow is established, the challenge then becomes organizing a large group of people to do the work of modeling multiple complex scenarios in order to identify the best of possible design futures for the planet.

    What Is Needed

    Because most domain-specific models are implemented in a GIS framework, yet they are instrumental to the success of an earth systems modeling and global design framework, a complete accounting of available models, how they work, and how they integrate with GIS is essential.

    1. Maintain a Knowledge Base of Earth Systems Models. In support of earth systems modeling and global design framework, we need an open, wiki-like knowledge base cataloging environmental and earth systems models at all scales.
    2. Share Best Practices on the Use of Models in a GIS Framework. The models knowledge base should include best practices information on how each model integrates with GIS, in terms of data models, data management, display and visualization, and analysis.

    New Spatial Analysis Tutorial Workbook Published

    In Books, ESRI, Education, GIS, Modeling, Spatial Analysis on June 4, 2009 at 9:49 am

    GISTSA_FrontCover_lrgWith the release of GIS Tutorial II: Spatial Analysis Workbook, ESRI Press has expanded its instructional workbook offerings to benefit geographic information system (GIS) users at the intermediate level.

    Building on the basic skills taught in GIS Tutorial: Workbook for ArcView 9, GIS Tutorial II teaches readers how to perform spatial analysis using the tools in ArcGIS Desktop. Detailed, step-by-step procedures are included to guide them in a number of spatial analysis methods including comparison, overlay, density, proximity, statistical, temporal, distribution, pattern, cluster, autocorrelation, and hot spot.

    Observes David W. Allen, author of GIS Tutorial II, “Spatial analysis is what distinguishes GIS from other forms of digital map representations. It’s the problem-solving aspect of GIS, whether it’s done in the viewer’s brain or worked to a full conclusion on the map. The tools seem very basic—buffers, overlays, selections—but when combined in the correct sequence and symbolized sufficiently, they can reveal things about the data that can’t be seen in a spreadsheet or chart.”

    Allen is the GIS manager for the City of Euless, Texas, where he designs data structures and custom applications from scratch. He has used his knowledge of GIS as an instructor at Tarrant County College for the past eight years, during which time he assisted in the development of a GIS degree program and worked to establish a state standard for GIS degree programs in Texas.

    The exercises in GIS Tutorial II also provide practical application to the concepts presented in The ESRI Guide to GIS Analysis, volumes 1 and 2, which are previous ESRI Press publications written by Andy Mitchell. Says Mitchell, a senior technical writer at ESRI, “David Allen has produced an excellent volume to complement the ESRI Guide to GIS Analysis series—one that has long been needed. David’s experience as a GIS practitioner, as well as an instructor, has led him to include exercise scenarios based on spatial analysis tasks that GIS analysts working in government and industry perform every day. The data used in the workbook is derived from real-world GIS datasets—with all their complexity—adding yet another level of realism to the exercises. GIS Tutorial II will be invaluable for anyone wanting to expand their knowledge of the extensive spatial analysis capabilities of ArcGIS.”

    Exercise data and a 180-day trial of ArcGIS Desktop 9.3 software accompany the book on two separate DVDs. GIS Tutorial II: Spatial Analysis Workbook (ISBN: 9781589482012, 424 pages, $79.95) is available from online retailers, at www.esri.com/esripress, or by calling 1-800-447-9778.

    Spatial Analysis of Wetlands Will Help Reduce Ugandan Poverty, Boost Economy

    In Environmental Science, GIS, Spatial Analysis on June 4, 2009 at 8:10 am

    uganda_wetlands_mapDrawing on Uganda’s rich baseline of wetland data and poverty mapping, a new report titled “Mapping a Better Future: How Spatial Analysis Can Benefit Wetlands and Reduce Poverty in Uganda” from the World Resources Institute provides a detailed examination of the links between ecosystem services and the location of poor communities and presents practical lessons for policy-makers across government.

    GIS and Global Design

    In Climate Change, Design, Earth Systems Management, Environmental Science, GIS, Science, Spatial Analysis on June 4, 2009 at 7:13 am

    “Man may perish by his own explosive and insidious inventions.  For an adjustment to them he leaves himself precious little time, and progressively less as his technological wizardry runs wild and rushes on.  If he is to survive at all, it cannot be through slow adjustment.  It will have to be through design more subtly considered and circumspect, through more cautious planning in advance.”

    Richard Neutra, 1954

    The current anthropogenic domination of earth systems cannot be overstated.  Once we as a species acknowledge our moral and environmental imperative to carefully and thoughtfully manage our planet for the health of all component earth systems and grapple with the ethical issues of geoengineering, we can move away from accidental, poorly-planned geoengineering and into an era of conscious geodesign at a global scale.  A GIS-based framework offers the best approach for understanding and addressing the breadth of climate change science issues in a holistic manner.  Aggregating complex physical, biological, and social data and models within a unified framework will give us single view of the whole earth system and provide us with the tools to manage—and ultimately design—our future in the most effective, efficient, and morally defensible way.

    Landscape architecture and urban and regional planning have taught us to analyze alternative development ideas in a broad environmental context, and GIS tools were a natural outgrowth of this technique; but to date these design concepts have yet to be fully applied at a truly global scale to help us to understand and respond to climate change challenges.

    Mature Concepts, New Focus

    “Design is the first signal of human intention … What is our intention as a species and how do we go about thinking about that?”

    William McDonough, 2009

    Michael Batty states that “(a) narrow but suitable definition of design as it pertains to geographic systems … is the process of generating physical artefacts which meet ‘agreed’ human (social and economic) goals pertaining to specific points or periods in time and space.”  He goes on to describe the design process as increasingly evolutionary, where human-initiated or -influenced systems grow and evolve in a manner and fashion similar to biological systems.  This growth and evolution is in response to ever-changing environments and their associated assemblages of constraints.

    Reasoned design and management in the age of the anthropogenic earth is our moral imperative, but the biggest obstacle to our success is that we are not yet set up to work, or even think, in this way.  Brad Allenby notes that “(w)e lack solid data and analytical frameworks to make assertions about the costs, benefits, and normative assessments of different . . . practices”. GIS and the emerging field of geodesign are critical to the success of approaches such as earth systems management and engineering (ESEM) and other logical and rational models for dealing with the environmental and planning problems of ours and future generations.

    Design considering place was at the core of Ian McHarg’s beliefs, and it is the basis for current research and development efforts in the emerging field of geodesign.  Geodesign borrows concepts from landscape architecture, environmental studies, geography, planning, sustainability, and integrative studies. Much like GIS and environmental planning before it, geodesign takes an interdisciplinary, synergistic approach to solving critical problems and optimizing location, orientation, and features of projects at local, regional, and global scales.

    Geodesign may be a new term to some people, but GIS and design have a long history together.  And whether they realize it or not, over the last 40 years, many GIS professionals have been involved in geodesign projects primarily in the fields of environmental, regional, and urban planning.  To a certain extent, this is already done today by numerous GIS practitioners in fields like urban and regional planning and environmental management.  But geodesign makes this easier by making it an integral part of the workflow, both shortening the cycle time of the design process and improving the quality of the results.   With a debt of gratitude to Steinitz, the geodesign framework also lets us design and test various alternatives, helping us make the most educated and informed decisions about the best possible future.

    When we talk of designing our future, we believe that combining the wealth of data available about our world with sophisticated analysis and management tools is the prescription for understanding and shaping the future of our planet—an anthropogenic future where advances in human society, technology, etc., are carefully designed in close collaboration with nature, resulting in the best of possible future worlds.  Moving forward, there are some guidelines we can follow to help leverage geospatial technologies in support of global design.

    Guidelines for Global Design

    “To live in a world subject to purposeful, planetwide change will not, I think, be quite the same as living in one being messed up by accident.  Unless geoengineering fails catastrophically … the relationship between people and their environment will have changed profoundly.”

    Oliver Morton, 2009

    A geodesign framework will provide a robust set of tools for design professionals to support the design of alternate future for our earth and its systems.  And the need for such tools has never been greater. We live in an ever more complex world, where our impact on the natural environment is massive and can no longer be ignored. People are starting to recognize the importance Richard Neutra placed on the inseparable relationship between humans and nature and to realize Ian McHarg’s vision of design with nature, and they want to act. Matt Ball notes that “(t)here is now a growing interest in combining design functionality with the broader geographical context that geospatial tools offer in order to engage more deeply in land-use planning.”

    1. Establish Geodesign as a Field of Study. To what extent are the fundamental spatial concepts that lie behind GIS relevant in design? To what extent can the fundamental spatial concepts of design be addressed with GIS? Is it possible to devise a curriculum to develop spatial thinking in both GIS and design? To begin developing answers to such questions, a specialist meeting on spatial concepts in GIS and design was held December 15–16, 2008, in Santa Barbara, California. The purpose of the meeting was to discuss the potential for integrating design more fully into GIS, as well as the development of curriculum in spatial thinking. Spatial design is concerned primarily at project- and regional scales, while geodesign is concerned with similar issues but also at a global scale.  Further discussion is needed to fully develop these concepts and build a curriculum around them.
    2. Differentiate between Unconscious and Conscious Global Design. Until recently, development projects and other programs and policies affecting the environment have been mostly short-sighted, project-based, and exclusive.  We need to focus on longer-term issues that are global in nature and inclusive of multiple factors.  The primary difference is intent.  Conscious geodesign—carefully and thoughtfully manage our planet for the health of all component earth systems–lets us control the fate not just of the human race, but of the entire planet and all of its systems.
    3. Develop Robust Design Tools for GIS Environments. The experience GIS developers have gained while developing CAD integration tools and sketching tools has led to an appreciation of the power that could be derived by associating drawing tools, symbology, data models, process models, and other design tools into a single, integrated framework for performing geodesign. Having “back of the napkin” design sketches available for immediate analysis and feedback should be a primary area of research and development over the coming years for geospatial application developers.
    4. Promote GIS as a Foundational Design System. Integration of design tools with existing GIS functionality is important, but it’s only the first step. Ultimately, we need to expand the application of GIS to the point that it is a foundational design system. As Richard Neutra did with architecture in the 1950s, we need to advance a framework for design and planning that not just incorporates but also embraces technology; science; and, ultimately, nature in a system that helps us design and choose the best alternative futures.

    Conclusion

    “We are as gods, and we might as well get good at it.”

    Stewart Brand, 1968

    As humanity comes to grips with its overwhelming impact on the natural world, we are also gaining a much better appreciation for our inextricable link to nature. And with that, of course, comes an enormous responsibility—a responsibility made all the more gargantuan by the fact that we still have a long way to go toward fully understanding the dynamics of the various systems and developing a robust suite of comprehensive models and other tools to support these activities.  An GIS-based framework for global design offers the best chance at gaining a true, scientific understanding about earth systems and for making thoughtful, informed design decisions and proposing alternatives that allow humans and nature to coexist more harmoniously.

    Spatial Analysis: New Online Training Courses

    In ESRI, Education, GIS, Modeling, Spatial Analysis on May 7, 2009 at 2:20 pm

    Creating and Analyzing Surfaces Using ArcGIS Spatial Analyst
    June 2, 2009
    8:30 a.m.- 4:30 p.m. Pacific Time

    In this course, you will use ArcGIS Spatial Analyst to model a variety of real-world scenarios for more informed decision making. You will work specifically with elevation rasters and other data to model surfaces, evaluate results, and create a variety of maps.

    Geoprocessing Raster Data Using ArcGIS Spatial Analyst
    June 4, 2009
    8:30 a.m.-4:30 p.m. Pacific Time

    In this course, you will examine suitability modeling techniques using raster data. You will learn to classify, weight, and combine data to identify sites suitable for a specific use. In course exercises, you will work with ModelBuilder to implement a suitability modeling workflow.

    Swine Flu Fear Spreads

    In GIS, Science, Social Science, Spatial Analysis on April 28, 2009 at 9:39 am

    As global media sensationalizes the story of swine flu, it’s a good time to take a deep breath and reflect upon how health scientists have successfully used geospatial technology to better understand and control infectious diseases.

    GIS for Species Modeling Session at the 2009 ESRI International User Conference

    In Conferences, ESRI, Environmental Science, GIS, Geography, Modeling, Science, Spatial Analysis on April 21, 2009 at 9:42 am

    uc2009Date/Time:
    10:15 a.m.  – 11:30 a.m. Tuesday, 14 July 2009

    Location:
    Room 32 B, San Diego Convention Center, San Diego, California USA

    Presenter(s):
    Lisa LaCivita (GMU), Tony McKinney (U.S. Fish and Wildlife Service), Dawn Lemke (Alabama A&M University)

    Description:
    GIS is increasingly important for advanced scientific techniques involving species survival and management, with predictive models for understanding and managing ecosystems. These papers show how GIS is being used at the cutting edge of scientific and analytical techniques.

    Papers:

    Geo-referencing Primary Type Mollusks for the Smithsonian Institution
    Lisa LaCivita, GMU

    This unique opportunity to contribute to science, contains great geography lessons, context and complexities. What are best practices for geo-referencing? Can they be applied to legacy data? Why geo-reference Primary Type Mollusks and what is involved? How does our current suite of techno-tools change the dynamic of geo-referencing? Can projects of this type be brought to the “classroom” to further ecological and geographic education? The presenter believes that there exists tremendous potential for supporting educational initiatives, such as STEM (science, technology, engineering and mathematics) and SOL (standards of learning), by utilizing the Smithsonian’s collections. This session will explain the geo-referencing initiative, explore the possibilities and seek dialogue and involvement from the GIS community.

    Monitoring a Rare Desert Sand Dune Species: A Success Story
    Tony McKinney, U.S. Fish and Wildlife Service

    We utilized ArcInfo and ArcMAP for project design and analysis and GPS for field mapping and navigation to assess the density, abundance, and distribution of Peirson’s milk-vetch (Astragalus magdalenae var. peirsonii), a threatened plant in the Algodones Dunes of Imperial County, California, that has been the focus of Dune Use versus Dune Preservation litigation for the past few years. Our focus was to asses the status of this plant which has a life history that overlaps peak OHV use in the dunes, and to use this information to build a management program covering the dunes. We sampled 123,488 cells as the base to select 750 seed bank cells. Sample plots were re-visited to predict distribution and trend analysis. We present our overall results, discuss the importance of GPS to collect field data in this barren landscape, and the utility of spatial analysis to support land management decisions.

    Integrating GIS and Statistical Modeling in Assessing Invasive Plants
    Dawn Lemke, Alabama A&M University
    Jennifer Brown , Biomathematics Research Centre, Canterbury UniversityPrivate Bag 4800
    Philip Hulme , National Centre for Advanced Bio-Protection Technologies, Lincoln University
    Wubishet Tadesse , Alabama A&M University

    As our impacts on the landscape changes the composition of ‘natural’ areas, it is important that we integrate spatial technology to assist in active management. This research explores the integration of GIS and remote sensing with statistical analysis to assist in species distribution modeling. It is applicable to both native and non native communities and has the ability to assist land managers in identifying both areas of importance and areas of threat. It has been suggested that Maximum Entropy models can better assess possible species distribution, while logistic regression is more representative of the current species distribution. This presentation discusses the application of these models in association with GIS in application to modeling non native species in the Cumberland Plateau and Mountain Region.

    ESRI UC web site

    Spatial Analysis, Biogeography, and the Hunt for Osama bin Laden

    In GIS, Geography, Modeling, Science, Spatial Analysis on March 3, 2009 at 9:17 am

    The work of two geography professors and five of their students at UCLA using biogeography theory and spatial analysis tools to locate the possible whereabouts of Osama bin Laden has been all over the news (both geospatial and mainstream) over the last several weeks. Yesterday Scientific American published an interesting blog post which offers a critique of the paper; perhaps most importantly, that the authors “omitted several key details from their analysis, most notably pertinent political or historical context”.

    You can find the original paper published in the MIT International Review here [PDF].

    Advanced Spatial Analysis Workshops for Population Scientists

    In GIS, GIScience, Geography, Modeling, Science, Social Science, Spatial Analysis on March 2, 2009 at 1:43 pm

    The Population Research Institute (The Pennsylvania State University) and the Center for Spatially Integrated Social Science (University of California, Santa Barbara) are offering advanced spatial analysis workshops for population scientists who already possess a working knowledge of GIS and spatial statistics, and who use these tools in their research.

    Spatial & Multilevel Modeling
    @ The Population Research Institute, University Park, PA
    June 21-June 26, 2009

    Spatial Regression Modeling
    @ The Center for Spatially Integrated Social Science, Santa Barbara, CA
    July 12-July 17, 2009

    For more information and to fill out an application, visit the Advanced Spatial Analysis program web site.