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Utility of GIS Application in Warehousing and Data MiningKeywords: GIS tool Arc viewer , Data mining tool WEKA , Spatial data mining , Dataware housing , Apriori Associative rule mining algo Clustring , jsp-servlets Abstract: Large amount of spatial data is obtained through satellite images, remote sensing and other sources which is useful in various geological applications like Location prediction, Mining Resource Management, other socio-economic applications like Disease control, Traffic Planning etc. There is a need to analyze this spatial data to help decision makers for decision making, strategic planning and other administrative tasks. Spatial data mining is a process of extracting hidden knowledge in form of rules and patterns from spatial databases which are not explicitly stored. There is need to apply spatial data mining techniques on real practical life spatial data like census data which can be used to help administrators in developing policies for better development.
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