Dongting Lake is the second largest freshwater lake of China, and has an important ecological function and economic value for its abundant wetland resources. The fast鄄growing poplar trees have grown fast on the beach land in Dongting Lake during the past 20 years, especially in West Dongting Lake, where a dramatic wetland vegetation distribution change is observed with a high ecological risk. In this study, two fast growing poplar tree change extraction methods, which are the classification method and change detection method, are proposed using remote sensed data (Landsat ETM+ images and HJ鄄 1A / 1B CCD images, both with a resolution of 30 m) in two periods in West Dongting Lake. And comparisons of the results obtained by these two methods were analyzed. In the classification method, an object鄄oriented hierarchical information extraction approach was applied to extract the woods beach land information. Then the regions within a certain distance from the dike were classified as windbreaks fields. The change area of fast鄄growing poplar trees was extracted to be the difference between the results of the two periods. In the change detection method, the change area was firstly calculated based on the changed pixels. Then the change poplar trees were detected as the expansion information for the poplar trees

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