Applied Geography

Archive for the ‘Temporal 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.”

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.”

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.”

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.”

The Utility of “Google Trends” for Epidemiological Research: Lyme Disease as an Example

In Temporal Analysis on August 10, 2010 at 11:07 am

Geospatial Health, Volume 4, Number 2, May 2010, Pages 135-137

Ari Seifter1, Alison Schwarzwalder2, Kate Geis3, John Aucott4

“Internet search engines have become an increasingly popular resource for accessing health-related information. The key words used as well as the number and geographic location of searches can provide trend data, as have recently been made available by Google Trends. We report briefly on exploring this resource using Lyme disease as an example because it has well-described seasonal and geographic patterns. We found that search traffic for the string “Lyme disease” reflected increased likelihood of exposure during spring and summer months; conversely, the string “cough” had higher relative traffic during winter months. The cities and states with the highest amount of search traffic for “Lyme disease” overlapped considerably with those where Lyme is known to be endemic. Despite limitations to over-interpretation, we found Google Trends to approximate certain trends previously identified in the epidemiology of Lyme disease. The generation of this type of data may have valuable future implications in aiding surveillance of a broad range of diseases.”

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.”

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.”

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.

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.”

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.”

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.”

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.”

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.”

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.”

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.”

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.”

Comparative Study of Land Cover using Multi-temporal Satellite Images

In Imagery, Temporal Analysis on July 20, 2010 at 9:11 am

3rd International Conferecne on Cartography and GIS

15-20 June, 2010, Nessebar, Bulgaria

Borislav Marinov and Margarita Mondeshka

“The comparative study of land cover and soil status are provided using space images with middle resolution. The Landsat TM+ and SPOT 5 images are included in analysis. The unsupervised and supervised classifications are applied for determination of different types of land cover. The terrain investigations are made by taking and analysing the soil samples for typical soil types presenting in the area of investigation. The analysed images are taken at different time moments in autumn and spring seasons to avoid the influence of crop stage of vegetation and snow coverage. The influence of used channels and space resolution of images on the reliability and accuracy of classified areas are investigated. The improvement of interpretation is established in the case of applying the combination of unsupervised and supervised classification. The recommendations are formulated for appropriate properties of utilised space images. The diversity and amount of terrain investigations are suggested for obtaining the reliable and representative results.”

Temporal Analysis of Sweet Chestnut Decline in Northeastern Portugal using Geostatistical Tools

In Environmental Science, Statistics, Temporal Analysis on July 19, 2010 at 1:17 pm

ISHS Acta Horticulturae 866: I European Congress on Chestnut – Castanea 2009

J. Castro, J.C. Azevedo, and L. Martins

“The rising demand for sweet chestnut (Castanea sativa) in Portugal and elsewhere in Europe has led to more intensive management practices to increase nut production. This intensification has potentially increased the widespread of ink and chestnut blight diseases, causing decline in sweet chestnut orchards health and production and limiting the establishment of new planted areas. In this study we estimated chestnut decline along the last twenty years (1986 to 2006) in the northern part of Portugal using 1986, 1995 and 2006 aerial photography to quantify the damage at the tree level within fixed sample plots according to a categorical scale. Mean damage and damage variance in each date, however, were not significantly different. Geostatistical analyses indicated, however, changes in the spatial distribution of damaged and undamaged areas over time. The spread of decline in the region of study was estimated using Kriging based on the spherical model. During the examined period we observed spread of chestnut decline and increasing damage levels in regions where damage is systematically high. The chestnut productive surface in the region has increased in the last twenty years because new plantations exceeded mortality areas. The spatial analyses applied here have made clearer the relations between the spread of chestnut decline and geographical variables.”

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.”

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.”

Using the Newly-created ILE DBMS to Better Represent Temporal and Historical GIS Data

In GIScience, Temporal Analysis on July 13, 2010 at 11:21 am

Transactions in GIS, Volume 14 Issue s1, Pages 39 – 58

Vitit Kantabutra, J. B. “Jack” Owens, Daniel P. Ames, Charles N. Burns, and Barbara Stephenson

“This article introduces a type of DBMS called the Intentionally-Linked Entities (ILE) DBMS for use as the basis for temporal and historical Geographical Information Systems. ILE represents each entity in a database only once, thereby mostly eliminating redundancy and fragmentation, two major problems in Relational and other database systems. These advantages of ILE are realized by using relationship objects and pointers to implement all of the relationships among data entities in a native fashion using dynamically-allocated linked data structures. ILE can be considered to be a modern and extended implementation of the E/R data model. ILE also facilitates storage of things that are more faithful to the historical records, such as gazetteer entries of places with imprecisely known or unknown locations. This is difficult in Relational database systems but is a routine task using ILE because ILE is implemented using modern memory allocation techniques. We use the China Historical GIS (CHGIS) and other databases to illustrate the advantages of ILE. This is accomplished by modeling these databases in ILE and comparing them to the existing Relational implementations.”

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.”

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]

    • 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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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).”

    Video: Time Lapse Development with ArcGIS

    In ESRI, GIS, Temporal Analysis, Video, Visualization on May 10, 2010 at 7:23 am

    Shane Michael at IgniteSpatial NOCO, 07 May 2010

    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.”

    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.”

    Temporal Analysis of the Reduction in Gas Emission in Areas of Mechanically-harvested Sugarcane using Satellite Imagery

    In Environmental Science, GIS, Imagery, Temporal Analysis on May 6, 2010 at 7:20 am

    Ciencia e Investigación Agraria, 37(1):113-121, 2010

    Christiano Luna Arraes, Jesús Camacho-Tamayo, Teresa Tarlé Pissarra, Célia P. Bueno, and Sergio Campos

    “The primary objective of this study was to estimate the amount of gas not emitted into the air in areas cultivated with sugarcane (Saccharum officinarum) that were mechanically harvested. Satellite images CBERS-2/CCD, from 08-13-2004, 08-14-2005, 08-15-2006 and 08-16-2007, of northwestern São Paulo State were processed using the Geographic Information System (GIS)-IDRISI 15.0. Areas of interest (the mechanically-harvested sugarcane fields) were identified and quantified based on the spectral response of the bands studied. Based on these data, the amount of gas that was not emitted was evaluated, according to the estimate equation proposed by the Intergovernmental Panel on Climate Change (IPCC). The results of 396.65 km2 (5.91% for 2004); 447.56 km2 (6.67% for 2005); 511.54 km2 (7.62% in 2006); and 474.60 km2 (7.07% for 2007), calculated from a total area of 6,710.89 km2 with sugarcane, showed a significant increase of mechanical harvesting in the study area and a reduction of gas emissions of more than 300,000 t yr.”

    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.”

    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.”

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    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.”

    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.”

    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.”

    Real-time Monitoring of Water Quality using Temporal Trajectory of Live Fish

    In Environmental Science, Temporal Analysis on April 22, 2010 at 6:59 am

    Expert Systems with Applications, Volume 37 , Issue 7 (July 2010)

    Heng Ma, Tsueng-Fang Tsai, and Chia-Cheng Liu

    “This paper proposes a real-time water quality monitoring scheme, which is based on judging time-series motion trajectories of live fish acquired by a CCD camera. The proposed scheme includes a floating-grid method to extract patterns in the motion trajectories and a neural network mechanism to quickly determine the frequency of pattern changes in these trajectories. To validate the proposed methods, several experiments were conducted by changing pH values of the water that houses live fish. The experimental results showed that the proposed methods could effectively differentiate motion trajectories of the fish in an efficient manner. The proposed scheme could be employed as a precautionary warning system for aquatic farms, drinking water treatment plants, and other related industries.”

    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.”

    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.”

    Multitemporal Monitoring of Water Resources Degradation at Al-Azraq Oasis, Jordan, Using Remote Sensing and GIS Techniques

    In Climate Change, Environmental Science, GIS, Imagery, Statistics, Temporal Analysis on April 15, 2010 at 7:02 am

    International Journal of Global Warming, 2010 – Vol. 2, No.1 pp. 1 – 16

    Naser Kloub, Mohammed Matouq, Monzer Krishan, Saeid Eslamian, and Monther Abdelhadi

    “The historical topographic maps and satellite images of Al-Azraq Oasis of Jordan were collected from 1953 to 2005. These images are demonstrated for the first time. The satellite land image for 2005 is considered to be the most significant one. This is considered to be the highest level of degradation since 1953. The water degradation in the lake was fitted by linear regression and the best fitting for the calculated surface area for the water can be presented by a polynomial equation.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    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.”

    Ensemble Extraction for Classification and Detection of Bird Species

    In Environmental Science, Imagery, Temporal Analysis on March 18, 2010 at 9:42 am

    Ecological Informatics, In Press, Accepted Manuscript, Available online 1 March 2010

    Eric P. Kasten, Philip K. McKinley, Stuart H. Gage

    “Advances in technology have enabled new approaches for sensing the environment and collecting data about the world. Once collected, sensor readings can be assembled into data streams and transmitted over computer networks for storage and processing at observatories or to evoke an immediate response from an autonomic computer system. However, such automated collection of sensor data produces an immense quantity of data that is time consuming to organize, search and distill into meaningful information. In this paper, we explore the design and use of distributed pipelines for automated processing of sensor data streams. In particular, we focus on the detection and extraction of meaningful sequences, called ensembles, from acoustic data streamed from natural areas. Our goal is automated detection and classification of various species of birds.”

    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.”

    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.”

    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.”

    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.”

    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 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.”

    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.”

    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.”

    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. “

    Comparison of Interpolation Methods for Depth to Groundwater and its Temporal and Spatial Variations in the Minqin Oasis of Northwest China

    In Environmental Science, GIS, Statistics, Temporal Analysis on January 29, 2010 at 8:22 am

    Environmental Modelling & Software, Volume 24, Issue 10, October 2009, Pages 1163-1170

    Yue Sun, Shaozhong Kang, Fusheng Li, and Lu Zhang

    “Severe water shortages and dramatic declines in groundwater levels have resulted in environmental deterioration in the Minqin oasis, an arid region of northwest China. Understanding temporal and spatial variations in the depth to groundwater in the region is important for developing management strategies. Depth to groundwater records for 48 observation wells in the Minqin oasis were available for 22 years from 1981 to 2003, allowing us to compare three different interpolation methods based on three selected years (1981, 1990, 2002) as starting points. The three methods were inverse distance weighting (IDW), radial basis function (RBF), and kriging (including ordinary kriging (OK), simple kriging (SK), and universal kriging (UK)). Cross-validation was applied to evaluate the accuracy of the various methods, and two indices – the correlation coefficient (R2) and the root mean squared error (RMSE) – were used to compare the interpolation methods. Another two indices – deviation of estimation errors (σ) and 95% prediction interval (95 PPI) – were used to assess prediction errors. Comparison of interpolated values with observed values indicates that simple kriging is the optimal method for interpolating depth to groundwater in this region: it had the lowest standard deviation of estimation errors and smallest 95% prediction interval (95 PPI). By using the simple kriging method and an autoregressive model for depth to groundwater based on the data from 1981 to 2003, this work revealed systematic temporal and spatial variations in the depth to groundwater in the Minqin oasis. The water table has declined rapidly over the past 22 years, with the average depth to groundwater increasing from 4.95 m in 1981 to 14.07 m in 2002. We attribute the decline in the water table to excessive extraction and to decreases in irrigation channel leakage.”

    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.”

    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.”

    PhD Scholarship, Institute of Geomatics and Analysis of Risk (IGAR), University of Lausanne

    In Education, Environmental Science, GIS, Modeling, Statistics, Temporal Analysis on January 4, 2010 at 8:10 am

    IGAR opens a position in the field of application of machine learning algorithms (neural networks of different architectures, support vector machines, etc.) and geostatistics for geo/environmental sciences. The main tasks concern the development, adaptation, and programming of data mining (pattern recognition) models and tools. In particular, topics to be studied include modeling of data clustering, novelty detection, feature selection, manifold learning, risk mapping, and spatio-temporal simulations. In addition to the PhD the candidate is expected to assist in teaching (French, English) and other projects at the institute.

    Requires an MS degree in one of the following disciplines: statistics, machine learning, computer science, physics, geosciences, applied mathematics. Candidates should have a sound background in spatio-temporal data analysis using machine learning and geostatistical approaches. Knowledge of scientific programming languages as Matlab, C, or R is important.

    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.”

    Visualizing Time in GIS

    In ESRI, GIS, Temporal Analysis on December 30, 2009 at 5:54 am

    Time Awareness in ArcGIS 9.4 Leads to Better Understanding of Complex Geographies

    …from the Winter 2009/2010 issue of ArcNews…

    In his First Law of Geography, noted geographer and cartographer Waldo Tobler states, “Everything is related to everything else, but near things are more related than distant things.”

    GIS professionals are well versed in visualization of spatial relationships and dependencies, of the proximity of near things and distant things, as in things you can measure with a ruler or with mile markers. But often when studying geography and looking for relationships and dependencies, equally important is proximity in time, as in something that can be measured with a watch or calendar.

    Related articles:

    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.”

    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.”

    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.”

    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.”

    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

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    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

    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

    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.”

    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.

    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 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.”

    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.”

    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]

    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.”

    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.”

    Combining Ontologies to Automatically Generate Temporal Perspectives of Geospatial Domains

    In GIS, GIScience, Temporal Analysis on September 3, 2009 at 11:30 am

    cover-medium…from GeoInformatica…

    “This paper describes an approach for automatically combining geospatial and temporal ontologies such that a geospatial domain can be analyzed over multiple temporal granularities. Terms from a geospatial ontology are combined with terms from a temporal ontology to form cross products that provide an integrated spatiotemporal framework. This framework is multi-granular, highlighting elements from the geospatial ontology at different domain times. We show how pairs of ontologies represented in Protégé can be used as the input for deriving cross products and how the results of this technique can be used as a basis for querying and retrieving new perspectives on geospatial domains. Visualizations of cross product spaces highlight the geospatial–temporal combinations of terms as well as the different relations that link these terms and improve the understanding of the structure of the spatiotemporal framework. Methods for filtering terms from the cross products are also investigated in order to prune the resulting frameworks and remove irrelevant or unnecessary terms.”

    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

    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

    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.”