{"title":"InSAR estimates of excess ground ice concentrations near the permafrost table","authors":"S. Zwieback , G. Iwahana , Q. Chang , F. Meyer","doi":"10.1016/j.isprsjprs.2025.03.004","DOIUrl":null,"url":null,"abstract":"<div><div>Ground ice melt can reshape permafrost environments, with repercussions for Northern livelihoods and infrastructure. However, fine-scale permafrost ground ice products are lacking, limiting environmental change predictions. We propose an InSAR-based approach for estimating ground ice near the permafrost table in sparsely vegetated terrain underlain by continuous permafrost. The Bayesian inversion retrieves ice content by matching the subsidence predicted by a forward model to InSAR observations, accounting for atmospheric, decorrelation, and model parameter uncertainty. We specifically estimate the excess ice concentration of materials that thaw at the end of summer; in summers with deep thaw, these materials overlap with the previous years’ upper permafrost. In a very warm summer in Northwestern Alaska, Sentinel-1 retrievals showed average excess ice concentrations of, respectively, 0.4 and 0.0 in locations independently determined to be ice-rich and ice-poor. In ice-rich locations, the estimates were lower in the preceding warm summer, indicating the thaw front rarely penetrated deep into the ice-rich intermediate layer. Performance was sensitive to the density of stable reference points for atmospheric correction, with deviations of up to 0.3 and increased uncertainty when fewer reference points were used. Toward filling gaps and mitigating InSAR retrieval errors far from reference points, we determined the predictability of the InSAR ice concentrations from topographic and optical surface proxies, finding a moderate <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> of 0.6, with slope being the most important predictor. In summary, the InSAR inversion provides quantitative ice concentration estimates near the permafrost table independent of surface manifestations of ground ice, in-situ observations and geological information. Its combination with optical remote sensing and geological information has the potential to provide seamless, fine-scale permafrost ground ice products.</div></div>","PeriodicalId":50269,"journal":{"name":"ISPRS Journal of Photogrammetry and Remote Sensing","volume":"223 ","pages":"Pages 261-273"},"PeriodicalIF":10.6000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISPRS Journal of Photogrammetry and Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0924271625001029","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Ground ice melt can reshape permafrost environments, with repercussions for Northern livelihoods and infrastructure. However, fine-scale permafrost ground ice products are lacking, limiting environmental change predictions. We propose an InSAR-based approach for estimating ground ice near the permafrost table in sparsely vegetated terrain underlain by continuous permafrost. The Bayesian inversion retrieves ice content by matching the subsidence predicted by a forward model to InSAR observations, accounting for atmospheric, decorrelation, and model parameter uncertainty. We specifically estimate the excess ice concentration of materials that thaw at the end of summer; in summers with deep thaw, these materials overlap with the previous years’ upper permafrost. In a very warm summer in Northwestern Alaska, Sentinel-1 retrievals showed average excess ice concentrations of, respectively, 0.4 and 0.0 in locations independently determined to be ice-rich and ice-poor. In ice-rich locations, the estimates were lower in the preceding warm summer, indicating the thaw front rarely penetrated deep into the ice-rich intermediate layer. Performance was sensitive to the density of stable reference points for atmospheric correction, with deviations of up to 0.3 and increased uncertainty when fewer reference points were used. Toward filling gaps and mitigating InSAR retrieval errors far from reference points, we determined the predictability of the InSAR ice concentrations from topographic and optical surface proxies, finding a moderate of 0.6, with slope being the most important predictor. In summary, the InSAR inversion provides quantitative ice concentration estimates near the permafrost table independent of surface manifestations of ground ice, in-situ observations and geological information. Its combination with optical remote sensing and geological information has the potential to provide seamless, fine-scale permafrost ground ice products.
期刊介绍:
The ISPRS Journal of Photogrammetry and Remote Sensing (P&RS) serves as the official journal of the International Society for Photogrammetry and Remote Sensing (ISPRS). It acts as a platform for scientists and professionals worldwide who are involved in various disciplines that utilize photogrammetry, remote sensing, spatial information systems, computer vision, and related fields. The journal aims to facilitate communication and dissemination of advancements in these disciplines, while also acting as a comprehensive source of reference and archive.
P&RS endeavors to publish high-quality, peer-reviewed research papers that are preferably original and have not been published before. These papers can cover scientific/research, technological development, or application/practical aspects. Additionally, the journal welcomes papers that are based on presentations from ISPRS meetings, as long as they are considered significant contributions to the aforementioned fields.
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