Region multi-center method for land use classification of multispectral RS imagery

A convenient multivariate statistical model is in general not available for the multi-spectral feature of land use(LU) class of remote sensing(RS) image,as one LU class is made up of several ground objects.Analyzing the spectral characteristics of LU of multispectral RS imagery,this paper presents a rule-based region multi-center(RMC) method.In the method,the clas-sification cell is pixel region,the classificatory pattern is a set of the classificatory intra-class centers which is confirmed by clustering the training samples,and the classification rules are the type amounts of intra-class center and the percentage of the pixels belonged to the class from the whole region pixels.RMC method can also be used to recognize the individual LU class from multi-spectral RS image.This method deals with the distribution problem by multi-center and based on rule method.There are much difference of the classificatory center amount and the pixel's percentage among different LU class,so the selection of training area and the determinants of rules are easy.The results of experiment indicate that the LU classification accuracy is increased between 4%and 6%with this method.