Research Objectives
GIS Day Presentation about SPARCS Lab
  About GEOIDE
  About GIS
  About Computational Science
  Computer Science Department
  Department of Geography
Research Objectives
The focus of SPARCS Lab is on the development of new methodology based on the weighted distance function and autocorrelation analysis for study of the spatio-temporal phenomena on the example of health and socio-environmental factors. SPARCS Lab also focuses on the recent problems arising in the above areas, with the goal of identifying key issues, and providing efficient solution for research and industry.


The projects on which we are working on are focusing on the understanding the causes and the factors influencing instances and treatments of heart disease in Alberta using spatial analysis, autocorrelation, geometric models and 3-dimensional visualization techniques. The other related projects are investigating how population distribution, social and economical factors, and traffic influence the outcomes of the treatment accessibility and availability of the treatments. Among the other initiatives, we are focusing on satellite image real-time rendering and restoration, as well as marine traffic security and navigation issues.


 General Research Topics
  • Computational methods in spatial analysis
  • nInvestigation of spatio-temporal phenomena
  • nApplication of the spatial analysis to health and social sectors
  • nGIS real-time terrain modeling and visualization
  • nAutocorrelation studies using weighted distance functions
  • nMethods for selection of Lp norms for city planning
  • nDynamic grid-based approach to statistical analysis of census and population data
  • nPattern matching and point pattern analysis using computational geometry methods
  • nApplication of the Voronoi diagram and Delaunay triangulation methodology to GIS problems
  • n
These general research directions could be further classified and described as following:
 Spatial Analysis 

n To develop the methodology for spatial autocorrelation analysis based on the weighted metric functions
n To identify the set of applied problems for which the methodology would result in the significant improvement over existing methods for spatial analysis, as well as public/private sector agencies that would benefit from such developments
n To analyze the spatial variation of heart disease and investigate the relationship between disease incidence and lifestyle indicators
n To link socio-economic, geographic and environmental factors to enhances the predictive capacity of the model 
 Traffic modeling and navigation
apply the proposed metrics for the measurement of distance for route design and the provision of routine and emergency services, and optimal facility location using location-allocation models.
nTo implements the uni- and multi-variate (auto)correlation indices and to definition the topology based contiguity among different spatial objects.
nTo investigation spatial patterns of traffic routes using advanced computational methods, closely related to the methodology such as point and line patter Voronoi diagram.


 Data Structures and Visualization

To develop advanced 3D visualization too for adequate representation for the studies models

To develop methodology based on adaptive memory subdivisions and their topological properties to efficiently render the model

To process high-resolution satellite images containing geographical information and eliminate possibility of an error

To find an efficient representation for ship navigation routes based on graphs


 Social and Health Studies

 To study accessibility of health care facilities through the development of a  dynamic model for the detection of spatio-temporal trends. The model can serve for cross-temporal comparisons, and for studying the evolution of the functional parameters, their statistical significance, and their elasticity
To study the use alternative distance metrics for an accurate measurement of the spatial autocorrelation in the data
To investigate the dependence of socio-economic factors on accessibility and availability of the treatment and the relationship of the efficiency of the treatment on travel time

SPARCS Research methodology can be represented as the following flowchart;