Reasoning about events causing geographic process using spatial and temporal relations

Geographic Information System (GIS) is storage and retrieval of remotely sensed spatio-temporal datasets of a geographic space at regular intervals. Spatial entities present in such datasets undergo change in their geographic location and other physical features such as size, color and type with respect to time. Knowledge engineering process involving spatial and temporal aspects of these datasets encompasses highly expressive representation to facilitate the inference of new knowledge to update this phenomenal change over a period of time. This necessitates formulation of knowledge base for inferring about spatial entity whose temporal attributes describe its time varying phenomena. Hence, Event Attributed Spatial Entity (EASE) Knowledge Base is proposed. Formal representation of spatial entities using RCC attributed with interval calculus is thus proposed so as to address the issue of inferring about events causing geographic process specific to geographic applications. Further, the significance of the proposed EASE based Spatio-Temporal reasoning is illustrated by evaluating event based queries. Finally, this work is concluded with direction for future enhancement.