{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T18:34:19Z","timestamp":1770143659045,"version":"3.49.0"},"reference-count":27,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,5,8]],"date-time":"2024-05-08T00:00:00Z","timestamp":1715126400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52274169"],"award-info":[{"award-number":["52274169"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52174160"],"award-info":[{"award-number":["52174160"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["E2020402086"],"award-info":[{"award-number":["E2020402086"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["BBJ2023021"],"award-info":[{"award-number":["BBJ2023021"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ecological-Smart Mines Joint Research Fund of the Natural Science Foundation of Hebei Province","award":["52274169"],"award-info":[{"award-number":["52274169"]}]},{"name":"Ecological-Smart Mines Joint Research Fund of the Natural Science Foundation of Hebei Province","award":["52174160"],"award-info":[{"award-number":["52174160"]}]},{"name":"Ecological-Smart Mines Joint Research Fund of the Natural Science Foundation of Hebei Province","award":["E2020402086"],"award-info":[{"award-number":["E2020402086"]}]},{"name":"Ecological-Smart Mines Joint Research Fund of the Natural Science Foundation of Hebei Province","award":["BBJ2023021"],"award-info":[{"award-number":["BBJ2023021"]}]},{"name":"China University of Mining &amp; Technology\u2014Beijing Cultivation Fund for Doctoral Students\u2019 Top Innovative Talents","award":["52274169"],"award-info":[{"award-number":["52274169"]}]},{"name":"China University of Mining &amp; Technology\u2014Beijing Cultivation Fund for Doctoral Students\u2019 Top Innovative Talents","award":["52174160"],"award-info":[{"award-number":["52174160"]}]},{"name":"China University of Mining &amp; Technology\u2014Beijing Cultivation Fund for Doctoral Students\u2019 Top Innovative Talents","award":["E2020402086"],"award-info":[{"award-number":["E2020402086"]}]},{"name":"China University of Mining &amp; Technology\u2014Beijing Cultivation Fund for Doctoral Students\u2019 Top Innovative Talents","award":["BBJ2023021"],"award-info":[{"award-number":["BBJ2023021"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>With the increasing availability of satellite monitoring data, the demand for storage and computational resources for updating the results of monitoring the surface subsidence in a mining area continues to rise. Sequential adjustment (SA) models are considered effective for rapidly updating time series interferometry synthetic aperture radar (TS-InSAR) measurements. However, the accuracy of surface subsidence values estimated through traditional sequential adjustment is highly sensitive to abnormal observations or prior information on anomalies. Moreover, the surface subsidence associated with mining exhibits nonlinear and large gradient characteristics, making general InSAR methods challenging for obtaining reliable monitoring results. In this study, we employ the phase unwrapping network (PUNet) to obtain unwrapped values of differential interferograms. To mitigate the impact of abnormal errors in the near real-time small baseline subset InSAR (SBAS-InSAR) sequential updating process in mining areas, a robust sequential adjustment method based on M-estimation is proposed to estimate the temporal deformation parameters by using the equivalent weight model. Using a coal backfilling mining face in Shanxi, China, as the study area and the Sentinel-1 SAR dataset, we comprehensively evaluate the performance of unwrapping methods and subsidence time series estimation techniques and evaluate the effect of filling mining on surface subsidence control. The results are validated using leveling measurements within the study area. The relative error of the proposed method is less than 5%, which can meet the requirements of monitoring the surface subsidence in mining areas. The method proposed in this study not only enhances computational efficiency but also addresses the issue of underestimation encountered by InSAR methods in mining area applications. Furthermore, it also mitigates unwrapping phase anomalies on the monitoring results.<\/jats:p>","DOI":"10.3390\/rs16101664","type":"journal-article","created":{"date-parts":[[2024,5,8]],"date-time":"2024-05-08T09:58:56Z","timestamp":1715162336000},"page":"1664","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Near Real-Time Monitoring of Large Gradient Nonlinear Subsidence in Mining Areas: A Hybrid SBAS-InSAR Method Integrating Robust Sequential Adjustment and Deep Learning"],"prefix":"10.3390","volume":"16","author":[{"given":"Yuanjian","family":"Wang","sequence":"first","affiliation":[{"name":"College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2736-9102","authenticated-orcid":false,"given":"Ximin","family":"Cui","sequence":"additional","affiliation":[{"name":"College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China"}]},{"given":"Yuhang","family":"Che","sequence":"additional","affiliation":[{"name":"College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China"}]},{"given":"Yuling","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Mining and Surveying, Hebei University of Engineering, Handan 056038, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6648-8473","authenticated-orcid":false,"given":"Peixian","family":"Li","sequence":"additional","affiliation":[{"name":"College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China"}]},{"given":"Xinliang","family":"Kang","sequence":"additional","affiliation":[{"name":"Geology Department, Xishan Coal Electricity Group Co., Ltd., Taiyuan 030053, China"}]},{"given":"Yue","family":"Jiang","sequence":"additional","affiliation":[{"name":"Disciplinary Development Office, Qingdao University, Qingdao 266071, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4516405","DOI":"10.1109\/LGRS.2022.3223627","article-title":"Large-gradient interferometric phase unwrapping over coal mining areas assisted by a 2-D elliptical gaussian function","volume":"19","author":"Shi","year":"2022","journal-title":"IEEE Geosci. 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