{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T05:19:18Z","timestamp":1772601558726,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T00:00:00Z","timestamp":1618272000000},"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":["61427802, 41330634, 41374016, 41804027"],"award-info":[{"award-number":["61427802, 41330634, 41374016, 41804027"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the science and technology project of State Grid (Research and application on intelligent monitoring and early warning technology of geological hazard for power transmission line based on InSAR)","award":["GCB17201700121"],"award-info":[{"award-number":["GCB17201700121"]}]},{"name":"the Open Fund of State Key Laboratory of Coal Resources and Safe Mining","award":["Grant No.SKLCRSM20KFA12"],"award-info":[{"award-number":["Grant No.SKLCRSM20KFA12"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Coal-mining subsidence causes ground fissures and destroys surface structures, which may lead to severe casualties and economic losses. Time series interferometric synthetic aperture radar (TS-InSAR) plays an important role in surface deformation detection and monitoring without the restriction of weather and sunlight conditions. In addition, the probability integral method (PIM) is a surface movement model that is widely used in the field of mining subsidence. In recent years, the integration of TS-InSAR and the PIM has been extensively studied. In this paper, we propose a new method to estimate mining subsidence with the PIM based on TS-InSAR results. This study focuses on the improvement of a boundary constraint and dynamic parameter estimation in the PIM through the inversion of the line-of-sight (LOS) time series deformation derived by TS-InSAR. In addition, 45 Sentinel-1A images from 17 June 2015 to 27 December 2017 of a coal mine in Jiaozuo are utilized to acquire the surface displacement. We apply a time series deformation analysis using small baseline subsets (SBAS) and place the results into an improved PIM to estimate the mining parameters. The simulated mining subsidence is highly consistent with the leveling data, exhibiting an RMSE of 0.0025 m. Compared with the conventional method, the proposed method is more accurate in discovering displacement in mining areas. In the final section of this paper, some sources of error that affect the experiment are discussed.<\/jats:p>","DOI":"10.3390\/rs13081497","type":"journal-article","created":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T22:55:09Z","timestamp":1618354509000},"page":"1497","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Improving Boundary Constraint of Probability Integral Method in SBAS-InSAR for Deformation Monitoring in Mining Areas"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2236-6981","authenticated-orcid":false,"given":"Mengyao","family":"Shi","sequence":"first","affiliation":[{"name":"School of Land Science and Technology, China University of Geosciences, Beijing 100083, China"},{"name":"Shanxi Key Laboratory of Resources, Environment and Disaster Monitoring, Jinzhong 030600, China"}]},{"given":"Honglei","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Land Science and Technology, China University of Geosciences, Beijing 100083, China"},{"name":"Shanxi Key Laboratory of Resources, Environment and Disaster Monitoring, Jinzhong 030600, China"}]},{"given":"Baocun","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Surveying Mapping and Geo-Information of Henan Provincial Bureau of Geo-Exploration and Mineral Development, Zhengzhou 450006, China"}]},{"given":"Junhuan","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Land Science and Technology, China University of Geosciences, Beijing 100083, China"},{"name":"Shanxi Key Laboratory of Resources, Environment and Disaster Monitoring, Jinzhong 030600, China"}]},{"given":"Zhouzheng","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Land Science and Technology, China University of Geosciences, Beijing 100083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3452-1413","authenticated-orcid":false,"given":"Bin","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Engineering and Technology, China University of Geosciences, Beijing 100083, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1109\/36.752187","article-title":"Multibaseline InSAR DEM reconstruction: The wavelet approach","volume":"37","author":"Ferretti","year":"1999","journal-title":"IEEE Trans. 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