1. College of Geo-exploration Science and Technology，Jilin University，Changchun 130026;

 In the research，the landuse in part of Kuancheng District，Changchun City is classified by using GF － 2 image as data source and self-made image labels． A method of combining the traditional Unet convolutional neural network model with fully connected conditional random fields ( CＲF) is proposed． Compared with the Segnet model，the results show that the Kappa coefficient of the Unet + CＲF classification method is 0. 711，and the F1 － score is 0. 795，indicating good accuracy and high consistency with the real objects．