Based on not only the basic data of total 9-phase Landsat8 OLI remote sensing images from 2013 to 2016 in Heishan District, Jinzhou City, Liaoning Province, also the supplementary data of high-resolution remote sensing images and elevation data in Heishan District, as well as phenology data in Northeast of China, the remote sensing images of the studied areas were classified by various methods and the classification results were evaluated accurately. The results show that the method of object-oriented classification obtains the best effect and highest precision on the information extraction of autumn grain crops. Its overall spatial distribution accuracy is about 95.2091%, and the Kappa coefficient is 0.9360. The method of object-oriented classification was applied to the dynamic monitoring of autumn crops in the researched areas in recent years, and then the analysis of the main autumn crops in there from 2013 to 2016 showed that the rice areas increased significantly in the past four years, while the com areas have shrunk by nearly one-fifth.
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