Application Study Of Spatial Data Mining Method And Its Integration Modes With GIS

This paper places great emphasis on the study of the spatial data mining methods and their integration with GIS. Aiming at the large spatial data sets whose qualities are complex and the situation that non-linearity, continuity and noises exist commonly, the spatial data mining method based on fuzzy neural network is put forward. An improved nearest neighboring clustering algorithm is used to construct the structure of fuzzy neural network, and thus fuzzy rules are extracted from large amounts of data to go on unsupervised learning, and only one dimension parameter needs to be adjusted by BP algorithm. So the method is speeded up, high efficient, accurate precision and has an extensive and promising application. Aiming at the problem of the integration between the spatial data mining and GIS, the paper proposes three integrated modes. In the last part of the paper, we put the theory researched just now into practice, achieve the integration between SDM and GIS, and successively apply to the intelligent design of urban water supply GIS, which makes up for the lack of intelligent function in the present urban water supply GIS.