2015–2022年漓江流域12天时间分辨率地表水体面积数据集

Using Sentinel-1 radar data and Sentinel-2 optical data, combined with auxiliary data such as land cover data and river and lake vector data, based on the different imaging principles of radar and optical sensors, the topological relationship of vectors was applied to finely extract surface water bodies. A remote sensing monitoring dataset of water body area with a time resolution of 12 days and a spatial resolution of 10 meters in the Li River Basin from 2015 to 2022 was constructed, including 196 periods of surface water distribution vector data. Through spatial distribution and quantitative accuracy verification of the dataset, the results show that the dataset can effectively eliminate factors such as terrain shadows and building shadows, with an overall accuracy of 94.15% and a Kappa coefficient of 0.8796. This set of data can be used to support the sustainable development of water resources and ecological environment in the watershed, and is of great significance in emergency management, disaster prevention and control, water conservancy development, water resource utilization, and ecological environment tourism.

本数据集以哨兵1号（Sentinel-1）雷达数据与哨兵2号（Sentinel-2）光学数据为核心数据源，辅以土地覆盖数据、河湖矢量数据等辅助资料，基于雷达与光学传感器迥异的成像原理，借助矢量拓扑关系完成地表水体的精细提取。构建了2015至2022年漓江流域水体面积遥感监测数据集，该数据集时间分辨率为12天、空间分辨率为10米，包含196期地表水体分布矢量数据。通过对该数据集开展空间分布特征分析与定量精度验证，结果显示其可有效消除地形阴影、建筑阴影等干扰因素，总体精度达94.15%，Kappa系数为0.8796。该数据集可支撑流域水资源与生态环境的可持续发展，在应急管理、防灾减灾、水利开发、水资源利用及生态环境旅游等领域均具有重要应用意义。