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Obtaining planted area of crop has important significance for guaranteeing nation grain safety. The Farm NO.597, located in Baoqing County, Shuangyashan City, Heilongjiang Province was selected as an example to extract rice and maize planted area by taking WFV (Wide field view) sensor carried on GF-1 satellite with the spatial resolution of 16 m as data source, using the image produced on October 30, 2014, and calculating different characteristic bands. Firstly, the multi-characteristic data set was established based on the NDVI (Normalized difference vegetation index) calculated from the source image and the first three principal components analyzed by PCA (Principal component transform). Then, using the difference between different surface features in each characteristic band, the decision tree was built based on CART (Classification and regression trees) to classify rice and maize. The results showed that the overall classification accuracy was 96.15% and the Kappa coefficient was 0.94. Producer accuracy of rice was 98.41% and user accuracy was 97.64%. Producer accuracy of maize was 95.38% and user accuracy was 97.89%. This method provides the reference value for crop type mapping using GF-1 data in other agricultural areas.