The invention provides a method for detecting the change of urban surface features in remote sensing image based on Siamese convolution network, the Siamese convolution network is a twin convolution neural network SCNN, Based on the data enhancement technique, the initial sample set is selected from the registered two-phase city images, the twin convolution neural network (SCNN) is set up, the twin convolution neural network (SCNN) is trained based on the initial sample set, and the initial sample set is expanded by the data enhancement technique. The twin convolution neural network (SCNN) istrained based on the expanded sample set, and the trained SCNN model is obtained to detect the change of urban terrain. The invention realizes the expansion of the sample through the data enhancementtechnology, and designs a Siamese convolution neural network, avoids the tedious steps of artificially designed features in the traditional change detection method, and realizes the end-to-end operation; Fully considering the spatial attributes of the image, the accuracy and reliability of the change detection are improved.