李靖霖 1，2，張 文 1，郎豐鎧 2

　　(1.武漢大學遙感信息工程學院，湖北 武漢 430079;

　　2.中國礦業大學環境與測繪學院，江蘇 徐州 221000)

　　摘 要：為及時準確得到陰雨天氣下的洪水淹沒區域及受災情況，以巢湖流域作為研究區域，選擇災前、災后的 Sentinel-1 影像作為數據源，基于 SDWI 指數及直方圖雙峰法提取水體信息，結合 Landsat 8 數據對山體陰影進行去除，快速提取洪水淹沒范圍，分析洪澇災害前后時空變化特征，并結合 Landsat 8 數據獲取的土地利用類型分類圖，對受災地區進行災情評估。結果表明：2020 年 6—9 月巢湖流域重災區域集中于巢湖西部、東部、北部，耕地、居民地受災程度嚴重;利用多時相 Sentinel-1 影像快速提取洪澇受災情況，可為國家減災備災、應急救災、恢復重建工作提供有力的數據支撐。

　　關鍵詞：Sentinel-1;Landsat 8;洪水淹沒;遙感監測;洪澇;災害分析

　　Flood inundation disaster analysis in Chaohu Region based on Sentinel-1 and Landsat 8

　　LI Jinglin 1，2，ZHANG Wen 1，LANG Fengkai 2

　　(1.School of Remote Sensing Information Engineering，Wuhan University，Wuhan 430079，China;

　　2.School of environment and surveying and mapping，China University of Mining and Technology，

　　Xuzhou 221000，China)

　　Abstract：In order to timely and accurately obtain the flood inundation area and disaster situation under wet weather, this paper takes Chaohu Basin as the research area. The Sentinel-1 images before and after the disaster are selected as the data source. Surface water information is extracted based on SDWI index and histogram bimodal method, and the mountain shadow is removed in combination with Landsat 8 data, so as to quickly extract the flood inundation area and analyze the spatial-temporal variation features before and after the flood disaster. Based on the map of land use classification from Landsat 8 data, the disaster in the affected areas is evaluated. The results show that from June to September 2020, the heavily affected areas in Chaohu Basin are concentrated in the west, east and north of Chaohu Lake, where cultivated land and residential areas are seriously affected. Using multi-temporal sentinel-1 images, the flood disaster situation can be quickly extracted, which can provide strong data support for national disaster reduction and preparedness, emergency response, recovery and reconstruction.

　　Key words：Sentinel-1;Landsat 8;flood inundation;remote sensing monitoring;flood and water-logging;disaster analysis