GEOG-AN-MOD 2011: Sixth International Workshop on Geographical Analysis, Urban Modeling, Spatial Statistics

20-23 June 2011, University of Cantabria, Santander, Spain

During the past decades the main problem in geographical analysis was the lack of spatial data availability. Nowadays the wide diffusion of electronic devices containing geo-referenced information generates a great production of spatial data. Volunteered geographic information activities (e.g. Wikimapia, OpenStreetMap), public initiatives (e.g. Spatial Data Infrastructures, Geo-portals) and private projects (e.g. Google Earth, Microsoft Virtual Earth, etc.) produced an overabundance of spatial data, which, in many cases, does not help the efficiency of decision processes. The increase of geographical data availability has not been fully coupled by an increase of knowledge to support spatial decisions. The inclusion of spatial simulation techniques in recent GIS software favoured the diffusion of these methods, but in several cases led to the mechanism based on which buttons have to pressed without having geography or processes in mind. Spatial modelling, analytical techniques and geographical analyses are therefore required in order to analyse data and to facilitate the decision process at all levels, with a clear identification of the geographical information needed and reference scale to adopt. Old geographical issues can find an answer thanks to new methods and instruments, while new issues are developing, challenging the researchers for new solutions. This workshop aims at contributing to the development of new techniques and methods to improve the process of knowledge acquisition.

The programme committee especially requests high quality submissions on the following Conference Themes:

  • Geostatistics and spatial simulation;
  • Agent-based spatial modelling;
  • Cellular automata spatial modelling;
  • Spatial statistical models;
  • Space-temporal modelling;
  • Space-temporal modelling;
  • Environmental Modelling;
  • Geovisual analytics, geovisualisation, visual exploratory data analysis;
  • Visualisation and modelling of track data;
  • Spatial Optimization;
  • Interaction Simulation Models;
  • Data mining, spatial data mining;
  • Spatial Data Warehouse and Spatial OLAP;
  • Integration of Spatial OLAP and Spatial data mining;
  • Spatial Decision Support Systems;
  • Spatial Multicriteria Decision Analysis;
  • Spatial Rough Set;
  • Spatial extension of Fuzzy Set theory;
  • Ontologies for Spatial Analysis;
  • Urban modeling;
  • Applied geography;
  • Spatial data analysis;
  • Dynamic modelling;
  • Simulation, space-time dynamics, visualization and virtual reality.

Each paper will be independently reviewed by 3 programme committee members. Their individual scores will be evaluated by a small sub-committee and result in one of the following final decisions: accepted, or accepted on the condition that suggestions for improvement will be incorporated, or rejected. Notification of this decision will take place on February 2011.
Individuals and groups should submit complete papers (10 to 16 pages).
Accepted contributions will be published in the Springer-Verlag Lecture Notes in Computer Science (LNCS) volumes.

Spatially Varying Relationships between Land Use and Water Quality across an Urbanization Gradient Explored by Geographically Weighted Regression

Applied Geography, In Press, Corrected Proof, Available online 3 September 2010

Jun Tu

“Significant relationships between land use and water quality have been found in watersheds around the world. The relationships are commonly examined by conventional statistical methods, such as ordinary least squares regression (OLS) and Spearman’s rank correlation analysis, which assume the relationships are constant across space. However, the relationships often might vary over space because watershed characteristics and pollution sources are not the same in different places. This study applies an exploratory spatial data analysis (ESDA) technique, geographically weighted regression (GWR), to analyze the spatially varying relationships between six land use and fourteen water quality indicators across watersheds with different levels of urbanization in eastern Massachusetts, USA. The study finds that the relationships between water quality and land use and the abilities of land use indicators to explain water quality vary across the urbanization gradient in the studied watersheds. Percentages of commercial and industrial lands have stronger positive relationships with the concentrations of water pollutants in less-urbanized areas than in highly-urbanized areas. Percentages of agricultural land, residential land, and recreation use show significant positive relationships with the concentrations of water pollutants at some sampling sites within less-urbanized areas, whereas they have significant negative relationships at some sampling sites within highly-urbanized areas. Thus, the adverse impact of land use changes on water quality is more substantial in less-urbanized suburban areas than that in highly-urbanized central cities. Pollution control policies should be adjusted in different areas based on the spatially varying pollution sources and good predictors of water quality.

“Research highlights

  • This study extends the application of geographically weighted regression (GWR) to water resources research. This study applies GWR to analyze the spatially varying relationships between land use and water quality across watersheds with different levels of urbanization in eastern Massachusetts, USA.
  • The study has several novel findings: 1) It finds that the relationships between water quality and land use and the abilities of land use indicators to explain water quality vary across the urbanization gradient in the studied watersheds. 2) Percentages of commercial and industrial lands have stronger positive relationships with the concentrations of water pollutants in less-urbanized areas than in highly-urbanized areas. Percentages of agricultural land, residential land, and recreation use show significant positive relationships with the concentrations of water pollutants at some sampling sites within less-urbanized areas, whereas they have significant negative relationships at some sampling sites within highly-urbanized areas. Thus, the adverse impact of land use changes on water quality is more substantial in less-urbanized suburban areas than that in highly-urbanized central cities.
  • This study has important policy implications for choosing urbanization pattern. The findings of this study suggest that smart growth that promotes high-density development in the center of a city has less adverse impact on water quality than urban sprawl that encourages low-density suburban.
  • The study suggests that GWR can serve as a useful tool for policy makers, regional and local agencies, and researchers to unveil the local pollution causes, to improve the understanding of local pollution status, and to adopt appropriate environmental and land use planning policies suitable to the local watershed conservation and management.”

More information

Seismic Inversion for Reservoir Properties Combining Statistical Rock Physics and Geostatistics: A Review

Geophysics, October 2010; v. 75; no. 5; p. 75A165-75A176

Miguel Bosch, Tapan Mukerji, and Ezequiel F. Gonzalez

“There are various approaches for quantitative estimation of reservoir properties from seismic inversion. A general Bayesian formulation for the inverse problem can be implemented in two different work flows. In the sequential approach, first seismic data are inverted, deterministically or stochastically, into elastic properties; then rock-physics models transform those elastic properties to the reservoir property of interest. The joint or simultaneous work flow accounts for the elastic parameters and the reservoir properties, often in a Bayesian formulation, guaranteeing consistency between the elastic and reservoir properties. Rock physics plays the important role of linking elastic parameters such as impedances and velocities to reservoir properties of interest such as lithologies, porosity, and pore fluids. Geostatistical methods help add constraints of spatial correlation, conditioning to different kinds of data and incorporating subseismic scales of heterogeneities.”

Scaling Effect for the Quantification of Soil Loss using GIS Spatial Analysis

KSCE Journal of Civil Engineering, Volume 14, Number 6, 897-904

Geun Sang Lee and In Ho Choi

“Accurate estimation of soil loss/deposition forced by rainfall events plays a major role in water resources management, which directly affects the quality of agricultural land and water storage capacity in reservoirs. In this paper, the soil loss model, Geographic Information System (GIS) based Universal Soil Loss Equation (USLE) was used to quantify soil loss in a small basin located in the southern part of Korea. The surface characteristics, such as soil texture, elevation and vegetation type, are needed to run the USLE model. Geospatial data has been successfully used to derive suitable model factors for this purpose. However, it is difficult to select the grid size of elements for the best fit, which is often decided in a subjective and intuitive way. A GIS spatial analysis was performed to investigate the scaling effect to estimate the soil loss in the USLE model using remotely sensed geospatial data. The results showed that the slope length factor (L) and slope steepness factor (S) were sensitive to the grid size; the optimal resolution for quantifying soil loss in the USLE model for the study site was 125 m. This approach presents a method for the selection of a suitable scale for estimating soil loss using remotely sensed geospatial data, which eventually improves the prediction of soil loss on a basin scale.”

Applying and Extending Sensor Web Enablement to a Telecare Sensor Network Architecture

COMSWARE ’09 — Proceedings of the Fourth International ICST Conference on COMmunication System softWAre and middlewaRE, 2009

Gavin E. Churcher and Jeff Foley

“The standards being proposed by the Sensor Web Enablement Working Group offer methods for virtualizing sensor data into a common, self-describing format, utilizing access mechanisms based on HTTP. An external application is able to discover and access different sensor offerings, understand the data format used and even specify that it should be notified of certain conditions in the sensor data. This paper examines how an existing sensor network platform in the telecare domain can make use of these standards and in particular provides a case for a proposed extension to the publish/subscribe model, the Sensor Alert Service. Concepts taken from Complex Event Processing engines are explored in the context of this particular telecare platform, where it is shown that there are clear advantages to extending the standard.”

Spatial-temporal Understanding of Urban Scenes through Large Camera Network

MPVA ’10: Proceedings of the 1st ACM International Workshop on Multimodal Pervasive Video Analysis, 2010

Jiejun Xu, Zefeng Ni, Carter De Leo, Thomas Kuo, and Bangalore Manjunath

“Outdoor surveillance cameras have become prevalent as part of the urban infrastructure, and provided a good data source for studying urban dynamics. In this work, we provide a spatial-temporal analysis of 8 weeks of video data collected from the large outdoor camera network at UCSB campus, which consists of 27 cameras. We first apply simple vision algorithm to extract the crowdedness information in the scene. Then we further explore the relationship between the traffic pattern observed from the cameras with activities in the nearby area using additional knowledge such as campus class schedule. Finally we investigate the potential of discovering aggregated human movement pattern by assuming a simple probabilistic model. Experiment has shown promising results using the proposed method.”

Residential Proximity to Freeways and Autism in the CHARGE Study

Environmental Health Perspectives, published online 16 December 2010

Heather E. Volk, Irva Hertz-Picciotto, Lora Delwiche, Fred Lurmann, and Rob McConnell

“Background: Little is known about environmental causes and contributing factors for autism. Basic science and epidemiological research suggest that oxidative stress and inflammation may play a role in disease development. Traffic-related air pollution, a common exposure with established effects on these pathways, contains substances found to have adverse prenatal effects.

“Objectives: To examine the association between autism and residence proximity, during pregnancy and near the time of delivery, to freeways and major roadways as a surrogate for air pollution exposure.

“Methods: Data were from 304 autism cases and 259 typically developing controls enrolled in the Childhood Autism Risks from Genetics and the Environment (CHARGE) Study. The mother’s address recorded on the birth certificate and trimester specific addresses derived from a residential history obtained by questionnaire were geo-coded and measures of distance to freeways and major roads were calculated using ArcGIS software. Logistic regression models compared residential proximity to freeways and major roads for autism cases and typically developing controls.

“Results: Adjusting for sociodemographic factors and maternal smoking, maternal residence at the time of delivery was more likely be near a freeway (≤309 meters) for cases, as compared to controls (odds ratio (OR), 1.86, 95% confidence interval (CI) 1.04-3.45). Autism was also associated with residential proximity to a freeway during the third trimester (OR, 2.22, CI, 1.16-4.42). After adjustment for socio-economic and demographic characteristics, these associations were unchanged. Living near other major roads at birth was not associated with autism.

“Conclusions: Living near a freeway was associated with autism. Examination of associations with measured air pollutants is needed.”

Site-specific Management Zones Based on the Rasch Model and Geostatistical Techniques

Computers and Electronics in Agriculture, Article in Press, Available Online 13 December 2010

F.J. Moral, J.M. Terrón, and F.J. Rebollo

“Delineation of management zones (MZ), i.e. areas within the field which represent subfield regions of similar production potential, is the first stage to implement site-specific management. During the last years different algorithms have been proposed to define MZ, with different results. In this work, the use of an objective method, the formulation of the Rasch model, which synthesizes data with different units into a uniform analytical framework, is considered to get representative measures of soil fertility potential which could be used to delimit MZ.

“To illustrate the method, a case study was conducted in a experimental field using five soil properties: clay, sand and silt content, and deep (ECd) and shallow (ECs) soil apparent electrical conductivity (approximately 0–90 and 0–30 cm depths, respectively). Two main results were obtained after applying this method: (1) a classification of all locations according to the soil fertility potential, which was the value of the Rasch measure and (2) the influence on the soil fertility of each individual soil property, being ECs the most influential and silt content the less influential property.

“Later, from the measures of soil fertility potential at sampled points, estimates were carried out using the ordinary kriging technique. Consequently, kriged estimates were utilized to map soil fertility potential and MZ were delimited using an equal-size classification method, which practically coincided with the MZ determined by a unsupervised classification.

“It is also shown the possibility of using probability maps to delimit MZ or provide information for hazard assessment of soil fertility in a field.”

Mapping Global Change: 1st Conference on Spatial Statistics 2011

23-25 March 2011, University of Twente, Enschede, The Netherlands

Spatial statistics is a rapidly developing field which involves the quantitative analysis of spatial data and the statistical modelling of spatial variability and uncertainty. Applications of spatial statistics are for a broad range of environmental disciplines such as agriculture, geology, soil science, hydrology, ecology, oceanography, forestry, meteorology and climatology, but also for socio-economic disciplines such as human geography, spatial econometrics, epidemiology and spatial planning.

The aim of the meeting is to present interdisciplinary research where applicability in other disciplines is a central core concept.

Conference Themes

  • Mapping global change
  • Spatial and spatio-temporal statistical methodology
  • Environmental issues
  • Ecological and habitat changes
  • Health and epidemiology
  • Economy and energy
  • Image use and analysis
  • Developing countries

More information

City of Lévis, Quebec to Expand Use of GIS Technology for Increased Efficiency

Enterprise License Provides Unlimited Access to ESRI GIS, Supporting the Use of Geographic Data and Analysis across the City

ESRI Canada today announced that the City of Lévis has signed a three-year enterprise license agreement (ELA) that will enable the municipality to cost-effectively expand its use of ESRI technology and establish an enterprise geographic information system (GIS). The GIS will help optimize the use of the City’s land information and other location-based data by enabling hundreds of internal users to apply the data and the system’s powerful analysis tools to enhance decision making. This, in turn, is expected to significantly increase efficiencies in municipal planning, operations and service delivery.

The City of Lévis was formed in 2001 through the amalgamation of eight cities in Québec and currently serves a population of 137,000. Previously, municipal geographic information was managed using Computer-Aided Design (CAD) technology that only allowed for data searches, without providing any tools for spatial analysis. Realizing the limitations of their CAD system, the City adopted an ESRI-based technology approach in 2006 as part of its GIS Strategic Plan. Since their initial deployment of ESRI’s ArcGIS technology, they have realized significant productivity gains, as well as time and cost savings. To expand efficiencies throughout the City, they began the development of an enterprise GIS called “GOcité” in 2008, which will support continuous improvements in city planning, zoning, engineering, public works, property assessment, parks management, public safety and economic development.

“We moved to a GIS-centric environment built on ESRI because the technology meets all our requirements for managing, analyzing and sharing data,” said Sébastien Roy, Geomatics coordinator, City of Lévis. “As our City’s geomatics needs continue to grow, our enterprise license will allow us to deploy GIS solutions flexibly across the organization while controlling system integration costs. It will help increase our users’ productivity by providing them with powerful data management and analysis tools to make better decisions and achieve our efficiency targets.”

The agreement will help the City to affordably establish an enterprise GIS by enabling large GIS deployments while lowering the cost per user. It simplifies technology acquisition by allowing them to avail of unlimited ESRI licenses through a fixed annual subscription. This makes it easier for the City to manage its GIS budget as the cost of technology and maintenance is predictable. It also increases user productivity and satisfaction by providing them access to the full suite of ESRI technology to support their work.

“In creating an enterprise GIS, users at the City of Lévis will gain an effective decision support system,” said Alex Miller, president, ESRI Canada. “The ability to combine land information with other types of business data will help them gain new insights on community concerns and enable them to make service delivery more efficient. It will allow them to enhance communications and effectively share information for more collaborative decision making. We’re pleased that through our enterprise license program, we’ve made it easier and more affordable for the City to access the technology and support they need to realize their vision of an enterprise GIS.”

The system will allow Lévis to extend their current GIS applications, such as the GOcité, to hundreds of users in the municipality, regardless of how familiar they are with geomatics tools and concepts. GOcité is an ESRI-based GIS solution for inventory management initially developed through a partnership of six major cities in Québec, which has grown to 10 cities today. It enables members to achieve economies of scale by leveraging a common GIS platform for managing and sharing basemaps, infrastructure, environmental and other spatial data.

In addition, the City will use the enterprise GIS to develop custom data analysis models and data distribution applications based on the needs of each department. It will also be used to create standards for maintaining geographic data throughout the municipality.

[Source: ESRI Canada press release]