Monitoring Snowmelt in Mountainous Areas by Considering SAR Geometric Distortion From Ascending and Descending Orbits
Year: 2025
Type: article
Abstract: SAR multi-temporal and multi-polarization change detection method has been widely utilized for wet snow extraction. Although SAR terrain correction can alleviate the geometric distortion caused by foreshortening and layover, it fails to fully eliminate terrain shadows and great layover effects on steep slopes, presenting significant challenges for high-precision monitoring of snowmelt. This study proposes a method for identifying snowmelt in mountainous areas by combining Sentinel-1 ascending and descending orbits data, taking advantage of the significant differences in geometric distortion areas between two types of orbits that transit on the same day. Firstly, geometric distortion areas and reliable areas are identified on the Sentinel-1 ascending orbit images (evening) and descending orbit images (morning) using radar and local incidence angles, respectively. Wet snow is extracted from each reliable areas using SAR multi-temporal and multi-polarization change detection algorithm. Then, the Sentinel-1 images of the two orbits are combined to obtain the reliable areas with minimal geometric distortion, and wet snow information is obtained through wet snow priority method and reliable areas priority method. Using the Babao River Basin in the Qilian Mountains as the study area, the data was accessed through the Google Earth Engine (GEE) and analysis was run on GEE. At the same time, in order to accurately extract the snow cover range, the spatiotemporal data fusion model (ESTARFM) was employed to simulate Sentinel-2 images that transits on the same day as Sentinel-1. Finally, the extracted dry/wet snow was corrected using Digital Elevation Model (DEM) to determine the distribution of dry/wet snow in the Babao River Basin for a hydrological year from September 2021 to August 2022. Using 71 field measuremengts of snow water content for accuracy verification, the results indicated that the overall accuracy of using combined ascending and descending orbits data increased from 71.2% for descending orbit alone and 72.4% for ascending orbit alone to 81.7%.
Authors: Yanli Zhang, Yalong Ma, Kairui Lei, Gang Chen
Institution: Northwest Normal University
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $1,800
Awards: G1140459793, 中国西北山区雪面短波净辐射遥感估算研究
OpenAlex ID: W4411446481
