The Dynamic Spatio-Temporal Evolution of Hot-Spots

Modelling and analysis of dynamic geospatial phenomena has emerged as a major research topic within the GIS community. Although present representational and analytical apparatus to examine the dynamics of such phenomena is nascent at best, the issue is increasingly being considered as a major research priority in the GIS area [Yuan et al., 2004]. In this context, our research is concerned with a macro-level analysis of a certain class of geospatial phenomena that can be modelled as clusters in space and time. We focus on the qualitative modelling and analysis of such spatial clusters (and their spatio-temporal evolution) that are representative of a wide range of geospatial phenomena in disparate domains such as crime analysis, wild-life biology, epidemiology, transportation planning, urban growth analysis etc. Clusters, popularly known as hot-spots, refer to the aggregation of raw locational data denoting sites of high incidence concentration, with an incidence typically denoting the spatio-temporal location of events