Spatial Data Mining is a branch of data mining. Based on spatial databases, it comprehensively utilizes various technical methods to automatically mine previously unknown and potentially useful knowledge from a large amount of spatial data, and extract non-explicit knowledge. It can reveal the essential laws, internal connections and development trends of the objective world behind the data, realize the automatic acquisition of knowledge, and provide the basis for technical and operational decisions. It can be used to understand or reorganize spatial data, discover the relationship between spatial and non-spatial data, build a spatial knowledge base, optimize queries, etc. In the established GIS spatial database, there is a large amount of knowledge that can be used for analysis and classification, such as spatial location distribution rules, spatial association rules, morphological feature distinction rules, etc. They are not directly stored in the spatial database and must be passed through Mining technology can dig it out. Therefore, spatial data mining technology is particularly important.
Expand
