Modelling spatial dependencies for mining geospatial data
Widespread use of spatial databases (Guting 1994; Shekhar and Chawla 2000; Shekhar et al. 1999; Worboys 1995) is leading to an increasing interest in mining interesting and useful, but implicit, spatial patterns (Greenman 2000; Koperski et al. 1996; Mark 1999; Roddick and Spiliopoulou 1999). Efficient tools for extracting information from geospatial data, the focus of this work, are crucial to organizations which make decisions based on large spatial data sets. These organizations are spread across many domains including ecology and environment management, public safety, transportation, public health, business, travel and tourism. (Albert and McShane 1995; Haining 1989; Hohn and Liebhold 1993; Issaks et al. 1989; Krugman 1995; Shekhar et al. 1993; Yasui and Lele 1997).