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Moving forward, Peratining to the Nature of SPACE

 
 
OBJECTIVES of SIRG

SIRG aims to employ advanced spatial statistical tools. The ideas stem from the following set objectives:

  1. To spatially visualize phenomena that could be described mathematically.
  2. To categorize features, that could be together visualized spatially, via both logical and quantitative means.
  3.  To explain spatial relations between the categorized features across spatial and temporal scales.
  4. To generate continuous sequence of categorized information from discrete information.
  5. To quantify the complexity in dynamical behaviour of spatial phenomena.
  6. To generate phase space maps depicting trajectory of dynamically changing spatial phenomena.
  7. To decide an optimal location for a specific anthropogenic and/or natural event.
  8. To quantify the degree of heterogeneity of phenomena spread spatially.
  9. To quantify the degree of heterogeneity of dynamical phenomena spread spatially.

The scope of interests of the members covers areas from theoretical to applied aspects. The main sections of SIRG dealing with different areas of interest include:

  1. Spatial Information Retrieval
  2. Spatial Information Visualization: To collect and integrate various data types and information generated in the real world using spatio-temporal keys, researchers can recreate real world conditions and the changes that occur therein, generate information, mining spatial data, and integrate spatio-temporal data.
  3. Spatial Information Integration
  4. Spatial Information Base: This section also constructs phenomenon-specific databases that are of use to researchers in a variety of fields. This section reconstructs scattered spatial data and spatial knowledge to compile a spatial information base. This section also studies the environments, methods, and systems needed for promoting social applications of the spatial information base.
  5. Spatial Information Analysis: This section involves in developing methods to (i) analyze spatial distribution and (ii) show relationships of spatial objects via quantitative means across spatial and also temporal scales.
  6. Spatial Information Reasoning
  7. Spatial and temporal Information Modelling: The aim of this section is to promote theoretical and empirical studies into diverse social, economic, health geographic phenomena, paying special attention to their spatio-temporal characteristics. The ultimate goal is to develop models to understand spatio-temporal behaviour.
  8. Granular Computing: Information granulation, Granular information retrieval, Case reasoning and generation, Machine learning and computational intelligence techniques.

 

 
 
 

 

 

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