More and more interest has been paid on Geodata mining and knowledge discovery from large database with the rapid growth of Geodata volume and eagerness for the Geoknowledge. This paper presents a dataset partition model based on information entropy and mutual information. The author argued that the largest information entropy deduction is in accordance with the significant Geodata pattern. With this kernel theoretical base

information entropy based decision tree model and spatial temopral clustering by partition model were developed.