The application of compact polarization SAR in the detection and classification of oil spill was analyzed in this study. First, we perfomed a comprehensive analysis of the performance of 36 features of compact polarization SAR in oil spill detection and classification by using Euclidean distance, and found that the odd-order scattering coefficient had best performance on oil spill detection, and the compact polarization entropy achieved better performance on oil spill lookalikes identification. Then, we proposed a compact polarization SAR oil spill detection and classification algorithm based on the binary tree idea, and the fully-polarimetric data of RADARSAT-2 and SIR-C were used to reconstruct the reduced polarized data and experiments. Results showed that the detection accuracy of oil spill detection is 95.67%, and the identification accuracy of oil spill lookalikes can reach 95.71%, which is 2% higher than the classic Wishart supervised classification method, indicating that the compact polarization SAR has a better application prospect in oil spill detection and classification.