{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T03:11:47Z","timestamp":1792293107141,"version":"4.4.0"},"reference-count":47,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T00:00:00Z","timestamp":1729814400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100012046","name":"Vietnam Academy of Science and Technology","doi-asserted-by":"publisher","award":["KHCBT\u0110.02\/24-25"],"award-info":[{"award-number":["KHCBT\u0110.02\/24-25"]}],"id":[{"id":"10.13039\/100012046","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Recurrent landslide events triggered by typhoons and tropical storms over Vietnam pose a longstanding threat to the nation\u2019s population and infrastructure. Changes in hydroclimatic conditions, especially the growing intensity and frequency of storms, have elevated landslide susceptibility in many parts of the country. This research examines the spatio-temporal variations in landslide susceptibility across central Vietnam over several years, using multi-temporal landslide inventories from Typhoon Ketsana (2009), Tropical Storm Podul (2013), and Typhoon Molave (2020). Additionally, the research explores the impact of individual landslide causative factors on the probabilistic occurrences of landslides. The post-event landslide susceptibility models of these three climate extreme events were developed using nine causative factors and a Random Forest machine learning algorithm. The results indicate a notable areal expansion of high to very high landslide susceptibility in the northern and eastern regions and a moderate reduction in the central and southern areas during the post-Molave period compared to the post-Ketsana period. These changes may be early indicators of increasing landslide susceptibility in response to changing hydro-climatic conditions. The research found that annual average rainfall and topographic elevation are the two most important variables influencing landslide prediction, showing a nonlinear relationship with landslide probability. The landslide susceptibility models achieved high Area Under the Receiver Operating Characteristic Curve (AUC) (&gt;95%), accuracy (&gt;89%), and sensitivity (&gt;90%) scores, signifying the robustness of the models. Additionally, the uncertainty of the models was quantified and spatially mapped. This multi-temporal analysis of landslide susceptibility is crucial for understanding the regional susceptibility trends and identifying areas with increasing, decreasing, and consistently high susceptibility to landslides. These insights are invaluable for prioritizing mitigation and risk reduction strategies in landslide-prone regions and guiding appropriate land use planning.<\/jats:p>","DOI":"10.1371\/journal.pone.0308494","type":"journal-article","created":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T13:23:03Z","timestamp":1729862583000},"page":"e0308494","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":21,"title":["Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-3220-8899","authenticated-orcid":true,"given":"Raja","family":"Das","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pham Van","family":"Tien","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8489-554X","authenticated-orcid":true,"given":"Karl W.","family":"Wegmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Madhumita","family":"Chakraborty","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,10,25]]},"reference":[{"key":"pone.0308494.ref001","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1016\/j.scitotenv.2019.03.415","article-title":"The human cost of global warming: Deadly landslides and their triggers (1995\u20132014)","volume":"682","author":"U Haque","year":"2019","journal-title":"Science of the Total Environment"},{"issue":"8","key":"pone.0308494.ref002","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":"MJ Froude","year":"2018","journal-title":"Natural Hazards and Earth System Sciences"},{"key":"pone.0308494.ref003","article-title":"Managing the risks of extreme events and disasters to advance climate change adaptation","volume":"582","author":"FC IPCC","year":"2012","journal-title":"A special report of working groups I and II of the intergovernmental panel on climate change"},{"key":"pone.0308494.ref004","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.earscirev.2016.08.011","article-title":"Landslides in a changing climate","volume":"162","author":"SL Gariano","year":"2016","journal-title":"Earth-Science Reviews"},{"key":"pone.0308494.ref005","unstructured":"Guha-Sapir D, Below R, Hoyois P. 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