Abstract: 【Objective】 The spatiotemporal fusion technology was used to generate high spatiotemporal resolution images,which provides an idea and method for the research of crop type identification.【Methods】 Taking part of the Hetao Irrigation Area（40°10′N-41°25′N,106°23′E-108°47′E）as the study area,based on MODIS and Landsat fusion images,using enhanced adaptive reflectance spatiotemporal fusion model（ESTARFM）,to predict Landsat images and build NDVI time series image data set. Combining the ground sample data,the real image and predicted image data sets were imported into the random forest classifier,and the main crop types in the study area were compared and analyzed.【Results】 The ESTARFM model fusion image had a clearer spatial expression ability,the predicted image and the real image had a better correlation between the bands,and the R value could reach more than 0.6. The overall accuracy of crop type identification using NDVI time series prediction image data set was 93.03%,which was 12.07% higher than the real image accuracy,and the Kappa coefficient was 0.89.【Conclusion】 The ESTARFM model could effectively solve the difficulty of image missing in a specific window period of crops,and provide a better application method for crop type identification research.

Key words: ESTARFM model, Spatiotemporal fusion, NDVI, Crop, Type identification