{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T10:34:50Z","timestamp":1774434890969,"version":"3.50.1"},"reference-count":64,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2024,8,17]],"date-time":"2024-08-17T00:00:00Z","timestamp":1723852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Guangxi Science and Technology Major Project","award":["AA22068072"],"award-info":[{"award-number":["AA22068072"]}]},{"name":"Guangxi Science and Technology Major Project","award":["ZRZY2024KJ02"],"award-info":[{"award-number":["ZRZY2024KJ02"]}]},{"name":"Guangxi Science and Technology Major Project","award":["CX2023352"],"award-info":[{"award-number":["CX2023352"]}]},{"name":"Hubei Provincial Natural Resources Research Program","award":["AA22068072"],"award-info":[{"award-number":["AA22068072"]}]},{"name":"Hubei Provincial Natural Resources Research Program","award":["ZRZY2024KJ02"],"award-info":[{"award-number":["ZRZY2024KJ02"]}]},{"name":"Hubei Provincial Natural Resources Research Program","award":["CX2023352"],"award-info":[{"award-number":["CX2023352"]}]},{"name":"15th Graduate Education Innovation Fund of Wuhan Institute of Technology","award":["AA22068072"],"award-info":[{"award-number":["AA22068072"]}]},{"name":"15th Graduate Education Innovation Fund of Wuhan Institute of Technology","award":["ZRZY2024KJ02"],"award-info":[{"award-number":["ZRZY2024KJ02"]}]},{"name":"15th Graduate Education Innovation Fund of Wuhan Institute of Technology","award":["CX2023352"],"award-info":[{"award-number":["CX2023352"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Landslide susceptibility maps (LSMs) are valuable tools typically used by local authorities for land use management and planning activities, supporting decision-makers in urban and infrastructure planning. To address this, we proposed a refined method for landslide susceptibility assessment, which comprehensively considered both static and dynamic factors. Neural network methods were used for susceptibility analysis. Land use and land cover (LULC) change and InSAR deformation were then integrated into the traditional susceptibility zoning to obtain a refined susceptibility map with higher accuracy. Validation was conducted on the improved landslide susceptibility map using site landslide data. The results showed that the LULC were proven to be the core driving factors for landslide occurrence in the study area. The GRU model achieved the highest model performance (AUC = 0.886). The introduction of InSAR surface deformation and land use and land cover change data could rationalize the inappropriateness of traditional landslide susceptibility zoning, correcting the false positive and false negative areas in the traditional landslide susceptibility map caused by human activities. Ultimately, 12.25% of the study area was in high-susceptibility zones, with 3.10% of false positive and 0.74% of false negative areas being corrected. The proposed method enabled refined analysis of landslide susceptibility over large areas, providing technical support and disaster prevention and mitigation references for geological hazard susceptibility assessment and land management planning.<\/jats:p>","DOI":"10.3390\/rs16163016","type":"journal-article","created":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T05:19:36Z","timestamp":1724044776000},"page":"3016","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Refined Landslide Susceptibility Mapping Considering Land Use Changes and InSAR Deformation: A Case Study of Yulin City, Guangxi"],"prefix":"10.3390","volume":"16","author":[{"given":"Pengfei","family":"Li","sequence":"first","affiliation":[{"name":"School of Civil Engineering and Architecture, Wuhan Institute of Technology, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huini","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Civil Engineering and Architecture, Wuhan Institute of Technology, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongli","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zixuan","family":"Ni","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongxing","family":"Deng","sequence":"additional","affiliation":[{"name":"Geological Environment Monitoring Station of Guangxi Zhuang Autonomous Region, Nanning 530201, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haigang","family":"Sui","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guilin","family":"Xu","sequence":"additional","affiliation":[{"name":"Guangxi Academy of Sciences, Nanning 530007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2161","DOI":"10.5194\/nhess-18-2161-2018","article-title":"Global fatal landslide occurrence from 2004 to 2016","volume":"18","author":"Froude","year":"2018","journal-title":"Nat. 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