{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T14:45:31Z","timestamp":1783867531475,"version":"3.55.0"},"reference-count":67,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,8,28]],"date-time":"2022-08-28T00:00:00Z","timestamp":1661644800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100016107","name":"Key Research Program of Science and Technology Department of Tibet","doi-asserted-by":"publisher","award":["XZ202001ZY0056G"],"award-info":[{"award-number":["XZ202001ZY0056G"]}],"id":[{"id":"10.13039\/501100016107","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100016107","name":"Key Research Program of Science and Technology Department of Tibet","doi-asserted-by":"publisher","award":["510201202076888"],"award-info":[{"award-number":["510201202076888"]}],"id":[{"id":"10.13039\/501100016107","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100016107","name":"Key Research Program of Science and Technology Department of Tibet","doi-asserted-by":"publisher","award":["0733 20180876\/2"],"award-info":[{"award-number":["0733 20180876\/2"]}],"id":[{"id":"10.13039\/501100016107","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Remote sensing identification and monitoring project of geologica hazards in Sichuan Province","award":["XZ202001ZY0056G"],"award-info":[{"award-number":["XZ202001ZY0056G"]}]},{"name":"Remote sensing identification and monitoring project of geologica hazards in Sichuan Province","award":["510201202076888"],"award-info":[{"award-number":["510201202076888"]}]},{"name":"Remote sensing identification and monitoring project of geologica hazards in Sichuan Province","award":["0733 20180876\/2"],"award-info":[{"award-number":["0733 20180876\/2"]}]},{"name":"Ministry of natural resources national geological hazard identification project in high risk areas","award":["XZ202001ZY0056G"],"award-info":[{"award-number":["XZ202001ZY0056G"]}]},{"name":"Ministry of natural resources national geological hazard identification project in high risk areas","award":["510201202076888"],"award-info":[{"award-number":["510201202076888"]}]},{"name":"Ministry of natural resources national geological hazard identification project in high risk areas","award":["0733 20180876\/2"],"award-info":[{"award-number":["0733 20180876\/2"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Landslide susceptibility evaluation is critical for landslide prevention and risk management. Based on the slope unit, this study uses the information value method- random forest (IV-RF) model to evaluate the landslide susceptibility in the deep valley area. First, based on the historical landslide data, a landslide inventory was developed by using remote sensing technology (InSAR and optical remote sensing) and field investigation methods. Twelve factors were then selected as the input data for a landslide susceptibility model. Second, slope units with different scales were obtained by the r.slopeunits method and the information value method- random forest (IV-RF) model is used to evaluate the landslide susceptibility. Finally, the spatial distribution characteristics of landslide susceptibility grade under the optimal scale are analyzed. The results showed that under the slope unit obtained when c = 0.1 and a = 3 \u00d7 105 m2, the internal homogeneity\/external heterogeneity of 8425 slope units extracted by the r.slopeunits method is the best, with an AUC of 0.905 and an F1 of 0.908. In this case, the accuracy of landslide susceptibility evaluation is the highest as well; it is shown that the finer slope units would not always lead to the higher accuracy of landslide susceptibility evaluation results; it is necessary to comprehensively consider the internal homogeneity and external heterogeneity of the slope units. Under the optimal slope unit scale, the number of landslides in the highly and extremely highly susceptible areas in the landslide susceptibility map accounted for 82.60% of the total number of landslides, which was consistent with the actual distribution of landslides; this study shows that the method, combining the slope unit and the information value method- random forest (IV-RF) model, for landslide susceptibility evaluation can obtain high accuracy.<\/jats:p>","DOI":"10.3390\/rs14174245","type":"journal-article","created":{"date-parts":[[2022,8,30]],"date-time":"2022-08-30T01:37:55Z","timestamp":1661823475000},"page":"4245","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":78,"title":["Slope-Unit Scale Landslide Susceptibility Mapping Based on the Random Forest Model in Deep Valley Areas"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1283-438X","authenticated-orcid":false,"given":"Hui","family":"Deng","sequence":"first","affiliation":[{"name":"College of Water Resource & Hydropower, Sichuan University, Chengdu 610065, China"},{"name":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiantan","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5361-4212","authenticated-orcid":false,"given":"Yansong","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3741-8801","authenticated-orcid":false,"given":"Weile","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangyu","family":"Li","sequence":"additional","affiliation":[{"name":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenhao","family":"Zhuo","sequence":"additional","affiliation":[{"name":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.geomorph.2015.03.016","article-title":"Spatial and temporal analysis of a global landslide catalog","volume":"249","author":"Kirschbaum","year":"2015","journal-title":"Geomorphology"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1411","DOI":"10.5194\/nhess-17-1411-2017","article-title":"Landslide susceptibility mapping on a global scale using the method of logistic regression","volume":"17","author":"Lin","year":"2017","journal-title":"Nat. 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