In this paper, based on the analysis of spectrum and texture information from the IKONOS image of the study area, eight types of training samples are selected and the spectral angle technology (SAM) is applied to perform classification. These eight types of surface include water body, shadow, thick pumice, thin pumice, trachyte, soil, vegetation and forest. The primary results of such classification are not satisfactory through confusion matrix evaluation, which may be due to a serious loss of spectrum information in the synthesizing process. Therefore, the authors introduce the texture analysis of the ENVI probability matrix method which takes advantage of dissimilarity texture feature to establish the symbol of texture interpretation. The final results indicate that the accuracy of classification may be greatly improved by using the combination of spectrum and texture analysis.