{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T01:47:46Z","timestamp":1778809666920,"version":"3.51.4"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T00:00:00Z","timestamp":1739923200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T00:00:00Z","timestamp":1739923200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"The Natural Science Research Key Project of University in Anhui Province","award":["2022AH050232"],"award-info":[{"award-number":["2022AH050232"]}]},{"name":"The Natural Science Foundation of Anhui Province","award":["2108085QD151"],"award-info":[{"award-number":["2108085QD151"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Earth Sci Inform"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1007\/s12145-025-01783-3","type":"journal-article","created":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T05:24:34Z","timestamp":1739942674000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Spatial and temporal evolution characteristics of land subsidence in Fuyang: time series InSAR monitoring and analysis of impacting factors"],"prefix":"10.1007","volume":"18","author":[{"given":"Huaming","family":"Xie","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zixian","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ting","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianjiao","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chukun","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Shu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiadong","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liangjun","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,19]]},"reference":[{"key":"1783_CR1","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1016\/j.isprsjprs.2024.07.006","volume":"215","author":"M Ao","year":"2024","unstructured":"Ao M, Wei L, Liao M, Zhang L, Dong J, and Shanjun Liu (2024a) Incremental multi temporal InSAR analysis via recursive sequential estimator for long-term landslide deformation monitoring. ISPRS J Photogrammetry Remote Sens 215:313\u2013330. https:\/\/doi.org\/10.1016\/j.isprsjprs.2024.07.006","journal-title":"ISPRS J Photogrammetry Remote Sens"},{"issue":"6693","key":"1783_CR2","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1126\/science.adl4366","volume":"384","author":"Z Ao","year":"2024","unstructured":"Ao Z, Xie XHST, Wang HG, Li M, Wang F et al (2024b) A National-Scale Assessment of Land Subsidence in China\u2019s Major cities. Science 384(6693):301\u2013306. https:\/\/doi.org\/10.1126\/science.adl4366","journal-title":"Science"},{"key":"1783_CR3","doi-asserted-by":"publisher","first-page":"146193","DOI":"10.1016\/j.scitotenv.2021.146193","volume":"778","author":"M Bagheri-Gavkosh","year":"2021","unstructured":"Bagheri-Gavkosh M (2021) Land Subsidence: A Global Challenge. Sci Total Environ 778:146193. https:\/\/doi.org\/10.1016\/j.scitotenv.2021.146193","journal-title":"Sci Total Environ"},{"issue":"11","key":"1783_CR4","doi-asserted-by":"publisher","first-page":"2375","DOI":"10.1109\/TGRS.2002.803792","volume":"40","author":"P Berardino","year":"2002","unstructured":"Berardino P, Fornaro G, Lanari R, Sansosti E (2002) A New Algorithm for Surface Deformation Monitoring based on small baseline Differential SAR interferograms. IEEE Trans Geosci Remote Sens 40(11):2375\u20132383. https:\/\/doi.org\/10.1109\/TGRS.2002.803792","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"1783_CR5","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.rse.2013.08.038","volume":"140","author":"E Chaussard","year":"2014","unstructured":"Chaussard E, Wdowinski S, Cabral-Cano E, and Falk Amelung (2014) Land Subsidence in Central Mexico detected by ALOS InSAR Time-Series. Remote Sens Environ 140:94\u2013106. https:\/\/doi.org\/10.1016\/j.rse.2013.08.038","journal-title":"Remote Sens Environ"},{"key":"1783_CR6","doi-asserted-by":"publisher","first-page":"139111","DOI":"10.1016\/j.scitotenv.2020.139111","volume":"735","author":"B Chen","year":"2020","unstructured":"Chen B, Gong H, Chen Y, Li X, Zhou C, Lei K, Zhu L, Duan L, Zhao X (2020) Land Subsidence and its relation with Groundwater aquifers in Beijing Plain of China. Sci Total Environ 735:139111. https:\/\/doi.org\/10.1016\/j.scitotenv.2020.139111","journal-title":"Sci Total Environ"},{"key":"1783_CR7","doi-asserted-by":"publisher","unstructured":"Cigna F (2022) and Deodato Tapete. Urban Growth and Land Subsidence: Multi-Decadal Investigation Using Human Settlement Data and Satellite InSAR in Morelia, Mexico. Science of The Total Environment 811:152211. https:\/\/doi.org\/10.1016\/j.scitotenv.2021.152211","DOI":"10.1016\/j.scitotenv.2021.152211"},{"key":"1783_CR8","doi-asserted-by":"publisher","first-page":"752","DOI":"10.1016\/j.scitotenv.2018.03.244","volume":"633","author":"C Da Lio","year":"2018","unstructured":"Da Lio C, and Luigi Tosi (2018) Land Subsidence in the Friuli Venezia Giulia Coastal Plain, Italy: 1992\u20132010 results from SAR-Based interferometry. Sci Total Environ 633:752\u2013764. https:\/\/doi.org\/10.1016\/j.scitotenv.2018.03.244","journal-title":"Sci Total Environ"},{"key":"1783_CR9","doi-asserted-by":"publisher","first-page":"477","DOI":"10.3390\/su12020477","volume":"12","author":"Y Ding","year":"2020","unstructured":"Ding Y, and Shouzhang Peng (2020) Spatiotemporal trends and Attribution of Drought across China from 1901\u20132100. Sustainability 12:477. https:\/\/doi.org\/10.3390\/su12020477","journal-title":"Sustainability"},{"key":"1783_CR10","doi-asserted-by":"publisher","first-page":"113446","DOI":"10.1016\/j.rse.2022.113446","volume":"286","author":"J Dong","year":"2023","unstructured":"Dong J, Guo S, Wang N, Zhang L, Ge D, Liao M, and Jianya Gong (2023) Tri-decadal evolution of Land Subsidence in the Beijing Plain revealed by Multi-epoch Satellite InSAR observations. Remote Sens Environ 286:113446. https:\/\/doi.org\/10.1016\/j.rse.2022.113446","journal-title":"Remote Sens Environ"},{"issue":"3","key":"1783_CR11","doi-asserted-by":"publisher","first-page":"e0151331","DOI":"10.1371\/journal.pone.0151331","volume":"11","author":"Z Du","year":"2016","unstructured":"Du Z, Xu X, Zhang H, Wu Z, and Yong Liu (2016) Geographical detector-based identification of the impact of major determinants on aeolian desertification risk. Edited by Vanesa Magar. PLoS ONE 11(3):e0151331. https:\/\/doi.org\/10.1371\/journal.pone.0151331","journal-title":"PLoS ONE"},{"key":"1783_CR12","doi-asserted-by":"publisher","first-page":"137125","DOI":"10.1016\/j.scitotenv.2020.137125","volume":"717","author":"Z Du","year":"2020","unstructured":"Du Z, Ge L, Ng AH-M, Zhu Q, Finbarr G, Horgan, Zhang Q (2020) Risk Assessment for tailings dams in Brumadinho of Brazil using InSAR Time Series Approach. Sci Total Environ 717:137125. https:\/\/doi.org\/10.1016\/j.scitotenv.2020.137125","journal-title":"Sci Total Environ"},{"key":"1783_CR13","doi-asserted-by":"crossref","unstructured":"Ferretti A, Prati C, Rocca F (2000) Nonlinear Subsidence Rate Estimation Using Permanent Scatterers in Differential SAR Interferometry. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 38 (5)","DOI":"10.1109\/36.868878"},{"key":"1783_CR14","unstructured":"Fuyang Statistical Yearbook 2023"},{"key":"1783_CR15","doi-asserted-by":"publisher","first-page":"104238","DOI":"10.1016\/j.jaridenv.2020.104238","volume":"181","author":"A Goorabi","year":"2020","unstructured":"Goorabi A, Karimi M, Yamani M, and Daniele Perissin (2020) Land Subsidence in Isfahan Metropolitan and its relationship with geological and geomorphological settings revealed by Sentinel-1A InSAR observations. J Arid Environ 181:104238. https:\/\/doi.org\/10.1016\/j.jaridenv.2020.104238","journal-title":"J Arid Environ"},{"key":"1783_CR16","doi-asserted-by":"publisher","unstructured":"Guzy A (2020) and Agnieszka Malinowska. State of the Art and Recent Advancements in the Modelling of Land Subsidence Induced by Groundwater Withdrawal. Water 12 (7): 2051. https:\/\/doi.org\/10.3390\/w12072051","DOI":"10.3390\/w12072051"},{"issue":"22","key":"1783_CR17","doi-asserted-by":"publisher","first-page":"3788","DOI":"10.3390\/rs12223788","volume":"12","author":"Y Han","year":"2020","unstructured":"Han Y, Zou J, Lu Z, Qu F, Ya Kang, and, Li J (2020) Ground Deformation of Wuhan, China, revealed by Multi-temporal InSAR Analysis. Remote Sens 12(22):3788. https:\/\/doi.org\/10.3390\/rs12223788","journal-title":"Remote Sens"},{"key":"1783_CR18","doi-asserted-by":"publisher","first-page":"101531","DOI":"10.1016\/j.ejrh.2023.101531","volume":"50","author":"J Han","year":"2023","unstructured":"Han J, Gong H, Guo L, Li X, Zhu L, Chen B, Zhang Q, Wu L, Jinyu Lei, and, Zhu X (2023) Mechanism the land subsidence from multiple spatial scales and hydrogeological conditions \u2013 A case study in Beijing-Tianjin-Hebei, China. J Hydrology: Reg Stud 50:101531. https:\/\/doi.org\/10.1016\/j.ejrh.2023.101531","journal-title":"J Hydrology: Reg Stud"},{"key":"1783_CR19","doi-asserted-by":"publisher","unstructured":"Herrera-Garc\u00eda G, Ezquerro P, Tom\u00e1s R, Marta B\u00e9jar-Pizarro, Juan L\u00f3pez-Vinielles, Mauro Rossi, Mateos RM et al (2021) Mapping the Global Threat of Land Subsidence. Science 371 (6524): 34\u201336. https:\/\/doi.org\/10.1126\/science.abb8549","DOI":"10.1126\/science.abb8549"},{"key":"1783_CR20","doi-asserted-by":"publisher","first-page":"101886","DOI":"10.1016\/j.jag.2019.05.019","volume":"82","author":"L Hu","year":"2019","unstructured":"Hu L, Dai K, Xing C, Li Z, Tom\u00e1s R, Clark B, Xianlin Shi, et al (2019) Land Subsidence in Beijing and its relationship with geological faults revealed by Sentinel-1 InSAR observations. Int J Appl Earth Obs Geoinf 82:101886. https:\/\/doi.org\/10.1016\/j.jag.2019.05.019","journal-title":"Int J Appl Earth Obs Geoinf"},{"key":"1783_CR21","doi-asserted-by":"publisher","first-page":"103936","DOI":"10.1016\/j.jag.2024.103936","volume":"131","author":"L Hu","year":"2024","unstructured":"Hu L, Tang X, Tom\u00e1s R, Li T, Zhang X, Li Z, Yao J, and Jing Lu (2024) Monitoring Surface Deformation dynamics in the mining subsidence area using LT-1 InSAR Interferometry: a case study of Datong, China. Int J Appl Earth Obs Geoinf 131:103936. https:\/\/doi.org\/10.1016\/j.jag.2024.103936","journal-title":"Int J Appl Earth Obs Geoinf"},{"key":"1783_CR22","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1016\/j.ejrs.2023.02.001","volume":"26","author":"SD Khan","year":"2023","unstructured":"Khan SD (2023) Study of Land Subsidence by Radar Interferometry and Hot Spot Analysis techniques in the Peshawar Basin. Pakistan Egypt J Remote Sens Space Sci 26:173\u2013184. https:\/\/doi.org\/10.1016\/j.ejrs.2023.02.001","journal-title":"Pakistan Egypt J Remote Sens Space Sci"},{"issue":"2","key":"1783_CR23","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1016\/j.geog.2021.09.007","volume":"13","author":"S Li","year":"2022","unstructured":"Li S, Xu W, Li Z (2022) Review of the SBAS InSAR Time-Series Algorithms, Applications, and challenges. Geodesy Geodyn 13(2):114\u2013126. https:\/\/doi.org\/10.1016\/j.geog.2021.09.007","journal-title":"Geodesy Geodyn"},{"key":"1783_CR24","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1016\/j.catena.2016.06.023","volume":"145","author":"P Liang","year":"2016","unstructured":"Liang P, and Xiaoping Yang (2016) Landscape spatial patterns in the Maowusu (Mu us) Sandy Land, Northern China and their impact factors. CATENA 145:321\u2013333. https:\/\/doi.org\/10.1016\/j.catena.2016.06.023","journal-title":"CATENA"},{"key":"1783_CR25","doi-asserted-by":"publisher","first-page":"103228","DOI":"10.1016\/j.jag.2023.103228","volume":"118","author":"Z Liu","year":"2023","unstructured":"Liu Z, Ng AH-M, Wang H, Chen J, Du Z, and Linlin Ge (2023) Land subsidence modeling and Assessment in the West Pearl River Delta from Combined InSAR Time Series, Land Use and Geological Data. Int J Appl Earth Obs Geoinf 118:103228. https:\/\/doi.org\/10.1016\/j.jag.2023.103228","journal-title":"Int J Appl Earth Obs Geoinf"},{"key":"1783_CR26","doi-asserted-by":"publisher","first-page":"169502","DOI":"10.1016\/j.scitotenv.2023.169502","volume":"913","author":"K Liu","year":"2024","unstructured":"Liu K, Zhang J, Liu J, Wang M, and Qingrui Yue (2024) Projection of Land susceptibility to Subsidence Hazard in China using an interpretable CNN Deep Learning Model. Sci Total Environ 913:169502. https:\/\/doi.org\/10.1016\/j.scitotenv.2023.169502","journal-title":"Sci Total Environ"},{"key":"1783_CR27","doi-asserted-by":"publisher","first-page":"928","DOI":"10.3390\/ijerph13100928","volume":"13","author":"C-R Lou","year":"2016","unstructured":"Lou C-R, Liu H-Y, Li Y-F, Yu-Ling Li (2016) Socioeconomic drivers of PM2.5 in the Accumulation Phase of Air Pollution episodes in the Yangtze River Delta of China. Int J Environ Res Public Health 13:928. https:\/\/doi.org\/10.3390\/ijerph13100928","journal-title":"Int J Environ Res Public Health"},{"key":"1783_CR28","doi-asserted-by":"publisher","first-page":"103076","DOI":"10.1016\/j.jag.2022.103076","volume":"114","author":"P Ma","year":"2022","unstructured":"Ma P, Zheng Y, Zhang Z, Wu Z, and Chang Yu (2022) Building risk monitoring and prediction using Integrated Multi-temporal InSAR and Numerical modeling techniques. Int J Appl Earth Obs Geoinf 114:103076. https:\/\/doi.org\/10.1016\/j.jag.2022.103076","journal-title":"Int J Appl Earth Obs Geoinf"},{"key":"1783_CR29","doi-asserted-by":"publisher","unstructured":"Mani Murali R, Reshma KN, Santhosh Kumar S, Agrawal R, Ramakrishnan R, Sreejith KM, Rajawat AS (2023) Land Subsidence Studies in the Godavari Delta Regions of the East Coast of India Using ALOS and Sentinel 1 Data. Ecol Inf 78:102373. https:\/\/doi.org\/10.1016\/j.ecoinf.2023.102373","DOI":"10.1016\/j.ecoinf.2023.102373"},{"issue":"1","key":"1783_CR30","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1186\/s44147-024-00402-0","volume":"71","author":"N Mehra","year":"2024","unstructured":"Mehra N, Janaki Ballav S (2024a) Assessment of Land Use Land Cover Change and its effects using Artificial neural network-based Cellular automation. J Eng Appl Sci 71(1):70. https:\/\/doi.org\/10.1186\/s44147-024-00402-0","journal-title":"J Eng Appl Sci"},{"key":"1783_CR31","doi-asserted-by":"publisher","unstructured":"Mehra N, Janaki Ballav S (2024b) Geospatial Assessment Of Urban Sprawl Using Remote Sensing And GIS: A Case Study of Western Himalayan City of Dharmashala, Himachal Pradesh, India. IOP Conference Series: Earth and Environmental Science 1327 (1): 012031. https:\/\/doi.org\/10.1088\/1755-1315\/1327\/1\/012031","DOI":"10.1088\/1755-1315\/1327\/1\/012031"},{"issue":"15","key":"1783_CR32","doi-asserted-by":"publisher","first-page":"2461","DOI":"10.3390\/rs12152461","volume":"12","author":"G Meldebekova","year":"2020","unstructured":"Meldebekova G, Yu C, Li Z, and Chuang Song (2020) Quantifying Ground Subsidence Associated with Aquifer Overexploitation using space-borne Radar Interferometry in Kabul, Afghanistan. Remote Sens 12(15):2461. https:\/\/doi.org\/10.3390\/rs12152461","journal-title":"Remote Sens"},{"key":"1783_CR33","doi-asserted-by":"publisher","first-page":"102373","DOI":"10.1016\/j.ecoinf.2023.102373","volume":"78","author":"RM Murali","year":"2023","unstructured":"Murali RM, Reshma KN, Santhosh Kumar S, Agrawal R, Ramakrishnan R, Sreejith KM, Rajawat AS (2023) Land Subsidence studies in the Godavari Delta regions of the East Coast of India Using ALOS and Sentinel 1 Data. Ecol Inf 78:102373. https:\/\/doi.org\/10.1016\/j.ecoinf.2023.102373","journal-title":"Ecol Inf"},{"key":"1783_CR34","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/j.agrformet.2016.11.129","volume":"233","author":"S Peng","year":"2017","unstructured":"Peng S (2017) Spatiotemporal Change and Trend Analysis of Potential Evapotranspiration over the Loess Plateau of China during 2011\u20132100. Agric for Meteorol 233:183\u2013194. https:\/\/doi.org\/10.1016\/j.agrformet.2016.11.129","journal-title":"Agric for Meteorol"},{"issue":"5","key":"1783_CR35","doi-asserted-by":"publisher","first-page":"2250","DOI":"10.1002\/joc.5331","volume":"38","author":"S Peng","year":"2018","unstructured":"Peng S, Gang C, Cao Y, Chen Y (2018) Assessment of Climate Change trends over the Loess Plateau in China from 1901 to 2100. Int J Climatol 38(5):2250\u20132264. https:\/\/doi.org\/10.1002\/joc.5331","journal-title":"Int J Climatol"},{"key":"1783_CR36","doi-asserted-by":"publisher","unstructured":"Peng S, Ding Y, Wenzhao Liu, and, Li Z (2019) 1 Km Monthly Temperature and Precipitation Dataset for China from 1901 to 2017. Earth System Science Data 11 (4): 1931\u201346. https:\/\/doi.org\/10.5194\/essd-11-1931-2019","DOI":"10.5194\/essd-11-1931-2019"},{"key":"1783_CR37","doi-asserted-by":"publisher","first-page":"102835","DOI":"10.1016\/j.jag.2022.102835","volume":"111","author":"C Pu","year":"2022","unstructured":"Pu C, Xu Q, Zhao K, Chen W, Wang X, Li H, Liu J, and Pinglang Kou (2022) Spatiotemporal evolution and surface response of Land Subsidence over a large-Scale Land Creation Area on the Chinese Loess Plateau. Int J Appl Earth Obs Geoinf 111:102835. https:\/\/doi.org\/10.1016\/j.jag.2022.102835","journal-title":"Int J Appl Earth Obs Geoinf"},{"key":"1783_CR38","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1016\/j.jenvman.2019.02.020","volume":"236","author":"O Rahmati","year":"2019","unstructured":"Rahmati O, Golkarian A, Biggs T, Keesstra S, Mohammadi F, Ioannis ND (2019) Land subsidence hazard modeling: machine learning to identify predictors and the role of human activities. J Environ Manage 236:466\u2013480. https:\/\/doi.org\/10.1016\/j.jenvman.2019.02.020","journal-title":"J Environ Manage"},{"key":"1783_CR39","doi-asserted-by":"publisher","first-page":"512","DOI":"10.1016\/j.envpol.2016.06.004","volume":"216","author":"Y Ren","year":"2016","unstructured":"Ren Y (2016) Quantifying the influences of various ecological factors on Land Surface temperature of urban forests. Environ Pollut 216:512\u2013529. https:\/\/doi.org\/10.1016\/j.envpol.2016.06.004","journal-title":"Environ Pollut"},{"key":"1783_CR40","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.rse.2016.10.037","volume":"188","author":"Q Sun, He","year":"2017","unstructured":"Sun, He Q, Zhang C, Zhao C, Yang QS, Chen W (2017) Monitoring land subsidence in the Southern Part of the Lower Liaohe Plain, China with a multi-track PS-InSAR technique. Remote Sens Environ 188:73\u201384. https:\/\/doi.org\/10.1016\/j.rse.2016.10.037","journal-title":"Remote Sens Environ"},{"issue":"1","key":"1783_CR41","doi-asserted-by":"publisher","first-page":"2391056","DOI":"10.1080\/10106049.2024.2391056","volume":"39","author":"L Tan","year":"2024","unstructured":"Tan L, Xie Y, Chen C, Bagan H, and Takahiro Yoshida (2024) Urbanization and land Subsidence: Multi-decadal Investigation Combined SBAS-InSAR and Multi-factors in Shanghai, China. Geocarto Int 39(1):2391056. https:\/\/doi.org\/10.1080\/10106049.2024.2391056","journal-title":"Geocarto Int"},{"key":"1783_CR42","doi-asserted-by":"publisher","first-page":"112792","DOI":"10.1016\/j.rse.2021.112792","volume":"269","author":"W Tang","year":"2022","unstructured":"Tang W, Zhao X, Motagh M, Bi G, Li J, Chen M, Chen H, and Mingsheng Liao (2022) Land Subsidence and Rebound in the Taiyuan Basin, Northern China, in the Context of Inter-basin Water Transfer and Groundwater Management. Remote Sens Environ 269:112792. https:\/\/doi.org\/10.1016\/j.rse.2021.112792","journal-title":"Remote Sens Environ"},{"key":"1783_CR43","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.enggeo.2015.10.009","volume":"199","author":"TT Thoang","year":"2015","unstructured":"Thoang TT, Giao PH (2015) Subsurface characterization and prediction of Land Subsidence for HCM City, Vietnam. Eng Geol 199:107\u2013124. https:\/\/doi.org\/10.1016\/j.enggeo.2015.10.009","journal-title":"Eng Geol"},{"issue":"8","key":"1783_CR44","doi-asserted-by":"publisher","first-page":"2464","DOI":"10.3390\/s18082464","volume":"18","author":"H Tien Bui, Dieu","year":"2018","unstructured":"Tien Bui, Dieu H, Shahabi A, Shirzadi K, Chapi B, Pradhan W, Chen K, Khosravi M, Panahi BB, Ahmad, and Lee Saro (2018) Land Subsidence susceptibility mapping in South Korea using machine learning algorithms. Sensors 18(8):2464. https:\/\/doi.org\/10.3390\/s18082464","journal-title":"Sensors"},{"issue":"1\u20132","key":"1783_CR45","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1016\/j.enggeo.2010.06.004","volume":"115","author":"R Tomas","year":"2010","unstructured":"Tomas R, Herrera G, Lopez-Sanchez JM, Vicente F, Cuenca A, Mallorqu\u00ed JJ (2010) Study of the Land Subsidence in Orihuela City (SE Spain) using PSI Data: distribution, evolution and correlation with conditioning and triggering factors. Eng Geol 115(1\u20132):105\u2013121. https:\/\/doi.org\/10.1016\/j.enggeo.2010.06.004","journal-title":"Eng Geol"},{"issue":"1","key":"1783_CR46","doi-asserted-by":"publisher","first-page":"116","DOI":"10.11821\/dlxb201701010","volume":"72","author":"J Wang","year":"2017","unstructured":"Wang J, Chengdong Xu (2017) Geodetector: principles and prospects. J Geogr 72(1):116\u2013134. https:\/\/doi.org\/10.11821\/dlxb201701010","journal-title":"J Geogr"},{"issue":"6","key":"1783_CR47","doi-asserted-by":"publisher","first-page":"101890","DOI":"10.1016\/j.gsf.2024.101890","volume":"15","author":"Y Wei","year":"2024","unstructured":"Wei Y, Qiu H, Liu Z, Huangfu W, Zhu Y, Liu Y, Yang D, and Ulrich Kamp (2024) Refined and Dynamic Susceptibility Assessment of landslides using InSAR and Machine Learning models. Geosci Front 15(6):101890. https:\/\/doi.org\/10.1016\/j.gsf.2024.101890","journal-title":"Geosci Front"},{"key":"1783_CR48","doi-asserted-by":"publisher","first-page":"113934","DOI":"10.1016\/j.rse.2023.113934","volume":"301","author":"WT Witkowski","year":"2024","unstructured":"Witkowski WT, \u0141ucka M, Guzy A, Sudhaus H, Bara\u0144ska A, and Ryszard Hejmanowski (2024) Impact of Mining-Induced seismicity on land subsidence occurrence. Remote Sens Environ 301:113934. https:\/\/doi.org\/10.1016\/j.rse.2023.113934","journal-title":"Remote Sens Environ"},{"key":"1783_CR49","doi-asserted-by":"publisher","unstructured":"Xu J, Boota CYMW, Chen X, Li Z, Liu W (2024) and Xu Yan. Research on Automatic Identification of Coal Mining Subsidence Area Based on InSAR and Time Series Classification. Journal of Cleaner Production, July, 143293. https:\/\/doi.org\/10.1016\/j.jclepro.2024.143293","DOI":"10.1016\/j.jclepro.2024.143293"},{"key":"1783_CR50","doi-asserted-by":"publisher","first-page":"139405","DOI":"10.1016\/j.scitotenv.2020.139405","volume":"738","author":"H Yu","year":"2020","unstructured":"Yu H, Gong H, Chen B, Liu K, Gao M (2020) Analysis of the influence of Groundwater on Land Subsidence in Beijing Based on the geographical weighted regression (GWR) model. Sci Total Environ 738:139405. https:\/\/doi.org\/10.1016\/j.scitotenv.2020.139405","journal-title":"Sci Total Environ"},{"key":"1783_CR51","doi-asserted-by":"publisher","first-page":"112778","DOI":"10.1016\/j.measurement.2023.112778","volume":"214","author":"L Zhang","year":"2023","unstructured":"Zhang L, Li Y, Li R (2023) Driving Forces Analysis of Urban Ground Deformation using Satellite Monitoring and Multiscale geographically weighted regression. Measurement 214:112778. https:\/\/doi.org\/10.1016\/j.measurement.2023.112778","journal-title":"Measurement"},{"key":"1783_CR52","doi-asserted-by":"publisher","first-page":"114105","DOI":"10.1016\/j.rse.2024.114105","volume":"305","author":"G Zhang","year":"2024","unstructured":"Zhang G, Xu Z, Chen Z, Wang S, Liu Y, and Xuhui Gong (2024a) Analyzing Surface Deformation throughout China\u2019s Territory using Multi-temporal InSAR Processing of Sentinel-1 Radar Data. Remote Sens Environ 305:114105. https:\/\/doi.org\/10.1016\/j.rse.2024.114105","journal-title":"Remote Sens Environ"},{"key":"1783_CR53","doi-asserted-by":"publisher","first-page":"114387","DOI":"10.1016\/j.measurement.2024.114387","volume":"228","author":"L Zhang","year":"2024","unstructured":"Zhang L, Su Y, Li Y, and Penghui Lin (2024b) Estimating Urban Land Subsidence with Satellite Data using a spatially Multiscale geographically weighted Regression Approach. Measurement 228:114387. https:\/\/doi.org\/10.1016\/j.measurement.2024.114387","journal-title":"Measurement"},{"key":"1783_CR54","doi-asserted-by":"publisher","first-page":"113102","DOI":"10.1016\/j.rse.2022.113102","volume":"279","author":"C Zhou","year":"2022","unstructured":"Zhou C (2022) Application of an Improved Multi-temporal InSAR Method and Forward Geophysical Model to Document Subsidence and Rebound of the Chinese Loess Plateau Following Land Reclamation in the Yan\u2019an New District. Remote Sens Environ 279:113102. https:\/\/doi.org\/10.1016\/j.rse.2022.113102","journal-title":"Remote Sens Environ"}],"container-title":["Earth Science Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-025-01783-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12145-025-01783-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-025-01783-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:02:13Z","timestamp":1760216533000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12145-025-01783-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,19]]},"references-count":54,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["1783"],"URL":"https:\/\/doi.org\/10.1007\/s12145-025-01783-3","relation":{},"ISSN":["1865-0473","1865-0481"],"issn-type":[{"value":"1865-0473","type":"print"},{"value":"1865-0481","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,19]]},"assertion":[{"value":"11 October 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 February 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 February 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"271"}}