{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T13:47:44Z","timestamp":1774273664438,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,2,16]],"date-time":"2024-02-16T00:00:00Z","timestamp":1708041600000},"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":["52104158"],"award-info":[{"award-number":["52104158"]}],"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":["2022-KFJJ-005"],"award-info":[{"award-number":["2022-KFJJ-005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Research Fund of Laboratory of Target Microwave Properties","award":["52104158"],"award-info":[{"award-number":["52104158"]}]},{"name":"Open Research Fund of Laboratory of Target Microwave Properties","award":["2022-KFJJ-005"],"award-info":[{"award-number":["2022-KFJJ-005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Subsidence prediction is essential for preventing and controlling geohazards in coal mining areas. However, the Interferometric Synthetic Aperture Radar (InSAR) technique is limited in deriving the goaf displacements with a large gradient and fast deformation rates, hindering its application for potential risk evaluation over the mining areas. In this study, we proposed a three-dimensional and full parameter inversion (TDFPI) model to derive the large-gradient subsidence and then investigate its application for building damage assessment over coal mining areas. By taking the Guotun coal mine as the case study, the TDFPI model was demonstrated to have effectively predicted the large-gradient deformation of the mining areas and successfully evaluated the house damage in Chelou village, which agrees well with our field investigations. Specifically, the predicted subsidence results were validated with high fitting accuracy against field measurements, with RMSE of 0.083 m and 0.102 m, respectively, on observation line A and line F. In addition, the classified damage levels are highly consistent with in situ field surveys for the house cracks in Chelou village, presenting its practicality and effectiveness for building damage evaluation, and thus can provide a useful tool for potential risk assessment and prevention over the mining areas.<\/jats:p>","DOI":"10.3390\/rs16040698","type":"journal-article","created":{"date-parts":[[2024,2,16]],"date-time":"2024-02-16T06:00:25Z","timestamp":1708063225000},"page":"698","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["TDFPI: A Three-Dimensional and Full Parameter Inversion Model and Its Application for Building Damage Assessment in Guotun Coal Mining Areas, Shandong, China"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6560-193X","authenticated-orcid":false,"given":"Hui","family":"Liu","sequence":"first","affiliation":[{"name":"Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China"},{"name":"School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China"},{"name":"Laboratory of Target Microwave Properties, Deqing Academy of Satellite Applications, Zhejiang 313000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingze","family":"Yuan","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4763-1817","authenticated-orcid":false,"given":"Mei","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ben","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-9280-975X","authenticated-orcid":false,"given":"Ning","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinzheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Shandong Energy Group, Luxi Mining Co., Ltd., Heze 274700, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Li","sequence":"additional","affiliation":[{"name":"School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4283-9958","authenticated-orcid":false,"given":"Xiaohu","family":"Wu","sequence":"additional","affiliation":[{"name":"Shandong Institute of Advanced Technology, Jinan 250100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"111663","DOI":"10.1016\/j.rse.2020.111663","article-title":"Three-dimensional time-varying large surface displacements in coal exploiting areas revealed through integration of SAR pixel offset measurements and mining subsidence model","volume":"240","author":"Chen","year":"2020","journal-title":"Remote Sens. 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