Extracting water body data based on SDWI and threshold segmentation: A case study in permafrost area surrounding Salt Lake in Hoh Xil, Qinghai-Tibet Plateau, China

Abstract

There are a large number of lakes, rivers, and other natural water bodies distributed in the permafrost area of the Qinghai-Tibet Plateau (QTP). The changes in water bodies will affect the distribution of water resources in surrounding areas and downstream areas, resulting in environmental impact and bringing potential flood disasters, which will induce more serious issues and problems in alpine and high-altitude areas with a fragile habitat (such as the QTP in China). Generally, effective, reasonable, and scientific monitoring of large-scale water bodies can not only document the changes in water bodies intuitively, but also provide important theoretical reference for subsequent environmental impact prediction, and disaster prevention and mitigation in due course of time. The large-scale water extraction technology derived from the optical remote sensing (RS) image is seriously affected by clouds, bringing about large differences among the extracted water result products. Synthetic aperture radar (SAR) RS technology has the unique advantage characteristics of all-weather, all-day, strong penetration, and not being affected by clouds, which is hopeful in extracting water body data, especially for days with cloudy weather. The data extraction of large-scale water bodies based on SAR images can effectively avoid the errors caused by clouds that become prevalent at present. In this paper, the Hoh Xil Salt Lake on the QTP and its surrounding five lakes are taken as the research objects. The 2-scene Sentinel-1 SAR image data covering the whole area on 22 August 2022 was used to verify the feasibility of extracting water body data in permafrost zones. Furthermore, on 22 August 2022, the wealth here was cloudy, which made the optical RS images, e.g., Sentinel-2 images full of clouds. The results show that: using the Sentinel-1 image and threshold segmentation method to extract water body data is efficient and effective with excellent results in permafrost areas. Concretely, the Sentinel-1 dual-polarized water index (SDWI), calculated by combining dual vertical–vertical (VV) polarized and vertical–horizontal (VH) polarized data is a useful index for water extraction and the result is better than each of the VV or VH polarized images.