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Due to the urgent requirement on SAR image interpretation, a method to extract building footprints from PolSAR image based on polarimetric scattering features and texture features was proposed. Firstly, polarimetric scattering features are extracted by Freeman decomposition and H/A/α decomposition method. Texture features are extracted based on gray level co-occurrence matrix (GLCM). Then, support vector machine (SVM) with Gaussian kernel function is trained to detect building regions by different features sets selected. At last, building polygons extraction is implemented: Line segments are extracted from obtained building regions by radon transform; cycles corresponding to the profiles of buildings in the graph are searched after determining line segment endpoints graph; building footprints are created by eliminating false cycles and connecting component cycles. The approach was demonstrated using airborne PolSAR image. Different features sets selected from experiment data were used to extract building footprints. Comparing the extraction results, the optimum features sets fitting for building footprints were extracted. Results show that the method provides a reliable way to extract building footprints comprehensively using multi-features and edge information.