To monitor crop residue area, three ESA Sentinel-1A synthetic aperture radar (SAR) VV and VH polarization data were generated at 25m spatial resolution for Siping in Jilin Province, China, from September to November. In this study, we analyzed the backscattering characteristics of the residue area and other typical objects. The difference of the objects under different polarizations combination mode were compared. The experimental results show that a high recognition accuracy of crop residue area can be obtained using the support vector machine (SVM) method if appropriate phase is selected. Specifically, classification result obtained from VH and VV polarization radar images combinations has higher classification accuracy. In this combination, the identification accuracy of crop residue area is 90.26% and the overall identification accuracy is 86.15%.