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Spatial data mining is the extraction of implicit knowledge, spatial relations and discovery of interesting characteristics and patterns that are not explicitly represented in the databases. It has a promising future in such fields as remote sensing, geographical information systems, medical imagery and information fusion systems etc. From the view of the crossover of knowledge discovery, cognition science and intelligent systems, the paper proposes a theoretical model of spatial data mining based on the double-bases cooperating mechanism of knowledge base and database, and systematically introduces knowledge types which can be obtained from spatial databases and the methods of spatial data mining. Finally, the future directions of spatial data mining are discussed.