| Summary: | In the recent decades, development of agricultural and human settlements have severely affected wetlands on the China-side of the Amur River Basin (CARB). A long-term holistic view of spatio-temporal variations of the wetlands on the CARB is essential for supporting sustainable conservation of wetlands in this region. In this study, a training sample migration method along with Random Forest classifier were adopted to map wetland and other land covers from two key seasons image collections. The proposed classification method was applied to Landsat images, and a 30-m resolution dataset was obtained, which reflected the dynamic changes of historical wetland distribution on the CARB region from 1990 to 2010. As the accuracy assessments showed, land cover maps of the CARB had high accuracies. The classification results indicated that the wetland area decreased from 89,432 km<sup>2</sup> to 75,061 km<sup>2</sup> between 1990 and 2010, with a net loss of 16%, which was mainly converted to paddy field and dry farmland, and the changes were most obvious in Sanjiang Plain and Songnen Plain. This suggests that agricultural activities are the main cause of wetland loss. The results can provide reliable information for the research on wetland management and sustainable development of the society and economy in the CARB.
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