Spatial Data Mining: Progress and Challenges
Spatial data mining, i.e., mining knowledge from large amounts of spatial data, is a highly demanding field because huge amounts of spatial data have been collected in various applications, ranging from remote sensing, to Geographical Information Systems (GIS), computer cartography, environ-mental assessment and planning, etc. The collected data for exceeded human's ability to analyze. Recent studies on data mining have extended the scope of data mining from relational and transactional databases to spatial databases. This paper summarizes recent works on spatial data mining, from spatial data generalization, to spatial data clustering, mining spatial association rules, etc.