Widely distributed in Guangxi, Karst landforms are characterized by heavy rainfall during the flood season, rapid hydrological dynamics, and notable spatiotemporal variations. A water is an important ecological foundation and natural resource, the timely and accurate acquisition of spatiotemporal changes in surface water bodies holds practical significance for the protection and management of water resources, rapid assessment of drought and flood disasters, and the realization of sustainable development across various economic industries. This dataset takes the Lijiang River Basin in Guilin, Guangxi as the research area. Addressing prevalent challenges such as infrequenct surface water monitoring, limited water body extraction methods due to sparse sample information, and low extraction accuracy in complex terrain areas, we combined the data from Sentinel-1 radar and Sentinel-2 in the study. Considering the different imaging principles of radar and optical sensors, we developed a vector classification method based on empirical thresholds for optical and other multi-source remote sensing data. The method can effectively eliminate interference of most ground object shadows, allowing for the construction of dataset of surface water area with 12-day resolution in Lijiang River Basin from 2015 to 2022. The dataset comprises a total of 196 periods of surface water body vector data. According to the results after verifying the spatial distribution and quantitative accuracy of the dataset, the dataset demonstrates its capability to accurately extract inlets and outlets of rivers, lakes and reservoirs, as well as small water bodies in complex terrain areas. The overall accuracy reaches 92.73%,with a Kappa coefficient of 0.85. This dataset can be used to support water resources protection and sustainable management of the ecological environment in the Lijiang River Basin. Additionally, it can provide reliable data for decision-making in areas such as emergency management, disaster prevention, water conservancy development, and economic development.
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