Abstract: Radar remote sensing can overcome the complex terrain and weather conditions,not only during severe weather conditions,but also can play a role in day and night,with a strong ability to work round-the-clock,all-weather.This feature is better than visible light and infrared detection system.In Great Khingan Mountains with cloudy summers,the optical image is difficult to obtain,affecting farming recognition in remote sensing.Selected parts of the Great Khingan Mountains west of the study area and single-polarization and multi-temporal Sentienl-1A for the data source,using maximum likelihood methods and CART decision trees,crop types were extracted to study and analyze its results.Data by classification,the results as follows:CART decision tree in crop identification classification method can provide a high classification accuracy;crop identification accuracy was 80.257%and Kappa coefficient was 0.733.Optical imaging can be a good secondary radar images which are used to distinguish non-arable land information.SAR data had good identify effect to the Great Khingan Mountains west of spring-wheat.