Abstract: In order to make undergraduates to master the remote sensing image processing technology，and combination with college student innovation training program in Jilin University，a land classification project of campus based on high-resolution satellite remote sensing image is designed． In this paper，GF-2 satellite image data of the central campus of Jilin University on September 20，2015 is used as experimental data． Spectral index and SVM ( Support Vector Machines) are used to get the buildings，vegetation，water，bare land and playground of the campus based on high resolution remote sensing image． In addition，the classification result is analyzed statistically to get campus vegetation coverage，campus building area，and land area to be developed． What’s more，the statistical results are compared with ground truth data to improve the classification accuracy． The experimental results show that the experiment can effectively help students to master knowledge of remote sensing，and get the expected teaching result．

Key words: high resolution, spectral index, campus, classification