Renzhe Wu , Guoxiang Liu , Xin Bao , Jichao Lv , Age Shama , Bo Zhang , Wenfei Mao , Jie Chen , Zhihan Yang , Rui Zhang
{"title":"Eliminating geometric distortion with dual-orbit Sentinel-1 SAR fusion for accurate glacial lake extraction in Southeast Tibet Plateau","authors":"Renzhe Wu , Guoxiang Liu , Xin Bao , Jichao Lv , Age Shama , Bo Zhang , Wenfei Mao , Jie Chen , Zhihan Yang , Rui Zhang","doi":"10.1016/j.jag.2024.104329","DOIUrl":null,"url":null,"abstract":"<div><div>Glacial lakes (GLs), which serve as natural reservoirs, are also prospective sources of risk, and their risk levels are continuously increasing as a result of global climate warming. Nevertheless, GLs are situated in mountainous and valley regions, which are distinguished by their complex terrain and unpredictable weather conditions. This leads to restricted availability of optical imagery as a consequence of the frequent cloud cover. Synthetic Aperture Radar (SAR), however, encounters issues with geometric distortion. This paper introduces an unsupervised method based on geometric distortion detection (without orbit state information) and historical positioning using dual-orbit SAR imagery to research GL extraction effectively. This method detects low-quality pixels from dual-orbit SAR imagery through geometric distortion. It extracts GLs using a majority voting integration of unsupervised classification algorithms constrained by historical GL center points. The Southeastern Tibetan Plateau (SETP) was chosen as a representative region for the study, and experiments were conducted from July to August 2018 using dual-orbit Sentinel-1 imagery. A total of 600 refined samples were used for comparative verification. The results demonstrate that this method is capable of reliably identifying the active and passive geometric distortions in SAR imagery. The fusion of dual-orbit SAR based on geometric distortion can effectively enhance the classification performance of remote sensing imagery and achieve the acquisition of GL water storage area during the flood season. The geometric distortion rate was reduced from 29.9% to 7.9% after fusion correction, and the accuracy, recall rate, precision, Intersection over Union (IoU), and F1-Score were 0.989, 0.900, 0.908, 0.825, and 0.904, respectively. This serves as a reference for research that investigates the mechanisms of glacier-GL-climate change.</div></div>","PeriodicalId":73423,"journal":{"name":"International journal of applied earth observation and geoinformation : ITC journal","volume":"136 ","pages":"Article 104329"},"PeriodicalIF":7.6000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of applied earth observation and geoinformation : ITC journal","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1569843224006873","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0
Abstract
Glacial lakes (GLs), which serve as natural reservoirs, are also prospective sources of risk, and their risk levels are continuously increasing as a result of global climate warming. Nevertheless, GLs are situated in mountainous and valley regions, which are distinguished by their complex terrain and unpredictable weather conditions. This leads to restricted availability of optical imagery as a consequence of the frequent cloud cover. Synthetic Aperture Radar (SAR), however, encounters issues with geometric distortion. This paper introduces an unsupervised method based on geometric distortion detection (without orbit state information) and historical positioning using dual-orbit SAR imagery to research GL extraction effectively. This method detects low-quality pixels from dual-orbit SAR imagery through geometric distortion. It extracts GLs using a majority voting integration of unsupervised classification algorithms constrained by historical GL center points. The Southeastern Tibetan Plateau (SETP) was chosen as a representative region for the study, and experiments were conducted from July to August 2018 using dual-orbit Sentinel-1 imagery. A total of 600 refined samples were used for comparative verification. The results demonstrate that this method is capable of reliably identifying the active and passive geometric distortions in SAR imagery. The fusion of dual-orbit SAR based on geometric distortion can effectively enhance the classification performance of remote sensing imagery and achieve the acquisition of GL water storage area during the flood season. The geometric distortion rate was reduced from 29.9% to 7.9% after fusion correction, and the accuracy, recall rate, precision, Intersection over Union (IoU), and F1-Score were 0.989, 0.900, 0.908, 0.825, and 0.904, respectively. This serves as a reference for research that investigates the mechanisms of glacier-GL-climate change.
期刊介绍:
The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.