Title: A method for extracting submerged water bodies based on dual polarisation satellite SAR images used with SDWI, OTSU and DEM

Authors: Shaohua Wang; Biao Liu; Zhenguo Wang; Wei Zheng; Xiaoyan Cui; Lisen Yuan

Addresses: State Grid Zhejiang Electric Power Co., Ltd., Electric Power Science Research Institute, Hangzhou Zhejiang, 310014, China ' BeiJing Fangzhi Technology Co., Ltd., Beijing, 100020, China ' State Grid Zhejiang Electric Power Co., Ltd., Electric Power Science Research Institute, Hangzhou Zhejiang, 310014, China ' BeiJing Fangzhi Technology Co., Ltd., Beijing, 100020, China ' BeiJing Fangzhi Technology Co., Ltd., Beijing, 100020, China ' BeiJing Fangzhi Technology Co., Ltd., Beijing, 100020, China

Abstract: In the event of a flood disaster, the use of digital technology to quickly extract and analyse the affected area holds significant value. The impact of complex terrain resulting from flooding has an adverse effect on the accuracy of traditional single methods, such as SDWI and OTSU. This paper proposes a method for extracting flood inundation areas based on dual-polarisation satellite SAR imagery. This method differs from the traditional Sentinel-1 dual-polarised water index (SDWI) and maximum inter-class variance (OTSU) methods by incorporating the digital elevation model (DEM) topographic factor to eliminate its influence on the results. This method effectively compensates for the low accuracy of traditional single-method methods. The article presents experimental research conducted using real SAR image data collected from Poyang Lake. The research findings suggest that the method proposed in this article achieved a 96% detection rate and a 10% false alarm rate, surpassing the accuracy of traditional single SDWI or OTSU methods. The research method proposed in this paper fully combines the advantages of SDWI, OTSU and DEM. The technical points are considered comprehensive, progressive, and highly accurate. It is expected to provide an important auxiliary decision-making means for flood fighting and rescue.

Keywords: dual polarisation satellite SAR image; Sentinel-1 dual-polarised water index; SDWI; maximum interclass variance; OTSU; digital elevation model; DEM.

DOI: 10.1504/IJEWM.2026.151855

International Journal of Environment and Waste Management, 2026 Vol.39 No.2, pp.103 - 120

Received: 28 Nov 2023
Accepted: 26 Jun 2024
Published online: 23 Feb 2026 *

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