At present

the method of aggregation and splitting is used for spatial data classification and hierarchical analysis. The analysis speed is not high and the limitation is large. In order to speed up the spatial data clustering speed

improve the accuracy of data classification

this paper presents a spatial data clustering method based on support vector machine

firstly

spatial data preprocessing based on wavelet multi window feature pute filtering sieving redundant data

then filtered according to the number of divided subintervals

as defining data extraction condition query data when

according to the specific characteristics of spatial data

the spatial data describing the individual collection into a series of independent groups

determine the spatial distribution of the data set

to realize spatial data aggregation. The experimental results show that the proposed method has high classification efficiency and high accuracy.