基于 Sentinel-1 卫星 SAR 数据的 2020 年巢湖洪涝监测及灾情分析

受持续降雨的影响,2020年6—8月巢湖流域水位超洪水设防的百年一遇标准,对巢湖流域的经济和生态环境造成严重危害。文章采用具有全天时、全天候、全覆盖优势的Sentinel-1卫星合成孔径雷达(synthetic aperture radar, SAR)影像数据,对比单阈值法、哨兵-1双极化水体指数(Sentinel-1 dual-polarized water index, SDWI)阈值法和支持向量机(support vector machine, SVM)分类算法3种方法的精度,选择最优方法来提取巢湖水体,实现对淹没区域面积的动态监测;同时利用Landsat 8、Sentinel-2卫星中、高空间分辨率光学影像对灾前研究区进行地物分类,分析灾情期间各类地物的受灾程度。结果显示:采用单阈值法可有效提取洪水淹没范围,总体精度达到98.43%以上,淹没面积为424.10 km²;淹没土地类型包括农用地、建成区和裸地等,其中淹没情况最严重的是农用地,淹没面积达到278.95 km²。

Affected by continuous rainfall, the water level in Chaohu Lake basin exceeded the 100-year flood control standard from June to August 2020, causing serious harm to the economy and ecological environment of Chaohu Lake basin. In this study, Sentinel-1 synthetic aperture radar (SAR) image data with the advantages of all-day, all-weather and full coverage were used to compare the accuracy of the single threshold method, Sentinel-1 dual-polarized water index (SDWI) threshold method, support vector machine (SVM) classification algorithm, and the optimal method was selected to extract Chaohu Lake water body, realizing dynamic monitoring of inundation area. Meanwhile, Landsat 8 and Sentinel-2 optical images with medium and high spatial resolution were used to classify the ground objects in the study area before the disaster and analyze the degree of damage of various ground objects during the disaster. The results show that using the single threshold method, the inundation area is effectively extracted, the overall accuracy is more than 98.43%, and the inundation area is 424.10 km². The submerged land types include agricultural land, built-up area and bare land, among which agricultural land is the most seriously submerged, with an area of 278.95 km².