{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T17:28:35Z","timestamp":1774718915736,"version":"3.50.1"},"reference-count":151,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,5,18]],"date-time":"2024-05-18T00:00:00Z","timestamp":1715990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Comprehensive Remote Sensing for Refined Investigation and Risk Assessment of Geological Hazards in Yunnan Province","award":["YCZH[2020]-68"],"award-info":[{"award-number":["YCZH[2020]-68"]}]},{"name":"Comprehensive Remote Sensing for Refined Investigation and Risk Assessment of Geological Hazards in Yunnan Province","award":["YCZH[2021]-23"],"award-info":[{"award-number":["YCZH[2021]-23"]}]},{"name":"Comprehensive Remote Sensing for Refined Investigation and Risk Assessment of Geological Hazards in Yunnan Province","award":["YNGH[2021]-168F"],"award-info":[{"award-number":["YNGH[2021]-168F"]}]},{"name":"Construction of Yunnan Geological Hazard Identification Center","award":["YCZH[2020]-68"],"award-info":[{"award-number":["YCZH[2020]-68"]}]},{"name":"Construction of Yunnan Geological Hazard Identification Center","award":["YCZH[2021]-23"],"award-info":[{"award-number":["YCZH[2021]-23"]}]},{"name":"Construction of Yunnan Geological Hazard Identification Center","award":["YNGH[2021]-168F"],"award-info":[{"award-number":["YNGH[2021]-168F"]}]},{"name":"Fine investigation and risk assessment of geological hazards in key regions of Yunnan Province","award":["YCZH[2020]-68"],"award-info":[{"award-number":["YCZH[2020]-68"]}]},{"name":"Fine investigation and risk assessment of geological hazards in key regions of Yunnan Province","award":["YCZH[2021]-23"],"award-info":[{"award-number":["YCZH[2021]-23"]}]},{"name":"Fine investigation and risk assessment of geological hazards in key regions of Yunnan Province","award":["YNGH[2021]-168F"],"award-info":[{"award-number":["YNGH[2021]-168F"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Against the backdrop of global warming and increased rainfall, the hazards and potential risks of landslides are increasing. The rapid generation of a landslide inventory is of great significance for landslide disaster prevention and reduction. Deep learning has been widely applied in landslide identification due to its advantages in terms of its deeper model structure, high efficiency, and high accuracy. This article first provides an overview of deep learning technology and its basic principles, as well as the current status of landslide remote sensing databases. Then, classic landslide deep learning recognition models such as AlexNet, ResNet, YOLO, Mask R-CNN, U-Net, Transformer, EfficientNet, DeeplabV3+ and PSPNet were introduced, and the advantages and limitations of each model were extensively analyzed. Finally, the current constraints of deep learning in landslide identification were summarized, and the development direction of deep learning in landslide identification was analyzed. The purpose of this article is to promote the in-depth development of landslide identification research in order to provide academic references for the prevention and mitigation of landslide disasters and post-disaster rescue work. The research results indicate that deep learning methods have the characteristics of high efficiency and accuracy in automatic landslide recognition, and more attention should be paid to the development of emerging deep learning models in landslide recognition in the future.<\/jats:p>","DOI":"10.3390\/rs16101787","type":"journal-article","created":{"date-parts":[[2024,5,20]],"date-time":"2024-05-20T03:36:42Z","timestamp":1716176202000},"page":"1787","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Advances in Deep Learning Recognition of Landslides Based on Remote Sensing Images"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9371-9473","authenticated-orcid":false,"given":"Gong","family":"Cheng","sequence":"first","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}]},{"given":"Zixuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center for Exploration of Nonferrous Metal Deposits and Efficient Utilization of Resources by the Province and Ministry, Guilin University of Technology, Guilin 541004, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2022-071X","authenticated-orcid":false,"given":"Cheng","family":"Huang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area, Ministry of Natural Resources, People\u2019s Republic of China, Kunming 650216, China"},{"name":"Yunnan Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area, Kunming 650216, China"},{"name":"Yunnan Institute of Geological Environment Monitoring, Kunming 650216, China"}]},{"given":"Yingdong","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area, Ministry of Natural Resources, People\u2019s Republic of China, Kunming 650216, China"},{"name":"Yunnan Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area, Kunming 650216, China"},{"name":"Yunnan Institute of Geological Environment Monitoring, Kunming 650216, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5412-2703","authenticated-orcid":false,"given":"Jun","family":"Hu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}]},{"given":"Xiangsheng","family":"Yan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area, Ministry of Natural Resources, People\u2019s Republic of China, Kunming 650216, China"},{"name":"Yunnan Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area, Kunming 650216, China"},{"name":"Yunnan Institute of Geological Environment Monitoring, Kunming 650216, China"}]},{"given":"Yilun","family":"Tan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}]},{"given":"Lingyi","family":"Liao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}]},{"given":"Xingwang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}]},{"given":"Yufang","family":"Li","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center for Exploration of Nonferrous Metal Deposits and Efficient Utilization of Resources by the Province and Ministry, Guilin University of Technology, Guilin 541004, China"}]},{"given":"Syed","family":"Hussain","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3173-0455","authenticated-orcid":false,"given":"Mohamed","family":"Faisal","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5211-8324","authenticated-orcid":false,"given":"Huan","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,18]]},"reference":[{"key":"ref_1","unstructured":"Wei, D.M. 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