The RS image shows a very promising perspective for urban land-cover and land-use classification

particularly with very high resolution（1—4m） satellite images

while the traditional extraction methods of the high spatial resolution image has the shortcomings of the low accuracy and classification efficiency.This paper deals with the high spatial resolution image（IKONOS） classification based on the SVM method integrating the information of spectral

texture and structure.And comparing to the results based on Maximum Likelihood and SVM method with single-source data

this shows that the high spatial resolution RS image classification based on SVM Method with multi-source data can solve the image classification fragmentation which is based on the single-source data

spectrum

and has the good generalization ability with the high dimension vector.It has more accuration than the maximum likelihood method and SVM based on the single source data

adapts to the high spatial resolution RS Image classification.