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(Wuhan)","award":["GLAB2020ZR02"],"award-info":[{"award-number":["GLAB2020ZR02"]}]},{"name":"Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan)","award":["GLAB2022ZR02"],"award-info":[{"award-number":["GLAB2022ZR02"]}]},{"name":"Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan)","award":["GBL12107"],"award-info":[{"award-number":["GBL12107"]}]},{"name":"Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan)","award":["CUG2642022006"],"award-info":[{"award-number":["CUG2642022006"]}]},{"name":"Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan)","award":["2021JC0009"],"award-info":[{"award-number":["2021JC0009"]}]},{"name":"Hunan Provincial Natural Science Foundation of China","award":["42311530065"],"award-info":[{"award-number":["42311530065"]}]},{"name":"Hunan Provincial Natural Science Foundation of 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China","award":["CUG2642022006"],"award-info":[{"award-number":["CUG2642022006"]}]},{"name":"Hunan Provincial Natural Science Foundation of China","award":["2021JC0009"],"award-info":[{"award-number":["2021JC0009"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Earthquake-triggered landslides (ETLs) feature large quantities, extensive distributions, and enormous losses to human lives and critical infrastructures. Near-real spatial prediction of ETLs can rapidly predict the locations of coseismic landslides just after a violent earthquake and is a vital technical support for emergency response. However, near-real prediction of ETLs has always been a great challenge with relatively low accuracy. This work proposes an ensemble prediction model of EnPr by integrating machine learning tree models and a deep learning convolutional neural network. EnPr exhibits relatively strong prediction and generalization performance and achieves relatively accurate prediction of ETLs. Six great seismic events occurring from 2008 to 2022 on the southeastern margin of the Tibetan Plateau are selected to conduct ETL prediction. In a chronological order, the 2008 Ms 8.0 Wenchuan, 2010 Ms 7.1 Yushu, 2013 Ms 7.0 Lushan, and 2014 Ms 6.5 Ludian earthquakes are employed for model training and learning. The 2017 Ms 7.0 Jiuzhaigou and 2022 Ms 6.1 Lushan earthquakes are adopted for ETL prediction. The prediction accuracy merits of ACC and AUC attain 91.28% and 0.85, respectively, for the Jiuzhaigou earthquake. The values of ACC and AUC achieve 93.78% and 0.88, respectively, for the Lushan earthquake. The proposed EnPr algorithm outperforms the algorithms of XGBoost, random forest (RF), extremely randomized trees (ET), convolutional neural network (CNN), and Transformer. Moreover, this work reveals that seismic intensity, high and steep relief, pre-seismic fault tectonics, and pre-earthquake road construction have played significant roles in coseismic landslide occurrence and distribution. The EnPr model uses globally accessible open datasets and can therefore be used worldwide for new large seismic events in the future.<\/jats:p>","DOI":"10.3390\/rs16101683","type":"journal-article","created":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T10:31:16Z","timestamp":1715250676000},"page":"1683","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Near-Real Prediction of Earthquake-Triggered Landslides on the Southeastern Margin of the Tibetan Plateau"],"prefix":"10.3390","volume":"16","author":[{"given":"Aomei","family":"Zhang","sequence":"first","affiliation":[{"name":"Hubei Subsurface Multi-Scale Imaging Key Laboratory, School of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China"}]},{"given":"Xianmin","family":"Wang","sequence":"additional","affiliation":[{"name":"Hubei Subsurface Multi-Scale Imaging Key Laboratory, School of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China"},{"name":"State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan 430074, China"},{"name":"Key Laboratory of Geological and Evaluation of Ministry of Education, China University of Geosciences, Wuhan 430074, China"},{"name":"Laboratory of Natural Disaster Risk Prevention and Emergency Management, School of Economics and Management, China University of Geosciences, Wuhan 430074, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3956-4925","authenticated-orcid":false,"given":"Chong","family":"Xu","sequence":"additional","affiliation":[{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China"},{"name":"Key Laboratory of Compound and Chained Natural Hazards Dynamics, Ministry of Emergency Management of China, Beijing 100085, China"}]},{"given":"Qiyuan","family":"Yang","sequence":"additional","affiliation":[{"name":"Hubei Subsurface Multi-Scale Imaging Key Laboratory, School of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China"}]},{"given":"Haixiang","family":"Guo","sequence":"additional","affiliation":[{"name":"Laboratory of Natural Disaster Risk Prevention and Emergency Management, School of Economics and Management, China University of Geosciences, Wuhan 430074, China"}]},{"given":"Dongdong","family":"Li","sequence":"additional","affiliation":[{"name":"College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.geomorph.2018.10.022","article-title":"A Global Slope Unit-Based Method for the Near Real-Time Prediction of Earthquake-Induced Landslides","volume":"327","author":"Tanyas","year":"2019","journal-title":"Geomorphology"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1007\/s10346-013-0404-6","article-title":"Three (nearly) complete inventories of landslides triggered by the May 12, 2008 Wenchuan Mw 7.9 earthquake of China and their spatial distribution statistical analysis","volume":"11","author":"Xu","year":"2014","journal-title":"Landslides"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Karagianni, A., Lazos, I., and Chatzipetros, A. 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