Landslide susceptibility assessment based on ConvNext in Longyang district of Baoshan city, China

Landslide susceptibility assessment based on ConvNext in Longyang district of Baoshan city, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Landslide susceptibility assessment based on ConvNext in Longyang district of Baoshan city, China Xiangwei Zhao, Haoquan Ma, Chong Niu, Lei Gao, Xianghui Kong This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4897122/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Landslide is a common type of geological disaster in the world, which causes great harm to people's life and financial security. The evaluation of landslide susceptibility plays an important role in the prevention of landslide disaster, and has always been the focus of research in this field. In order to establish an accurate landslide susceptibility evaluation model, this paper takes Longyang District, Baoshan City, Yunnan Province, China as the research area, and comprehensively considers 10 evaluation factors such as elevation, slope, slope direction, lithology, water system, residential area, highway, terrain, Normalized Difference Vegetation Index(NDVI) and rainfall to establish a landslide susceptibility evaluation model based on ConvNeXt. More than 27000 sample data were used for model training, and the spatial distribution map of landslide susceptibility was obtained by using the trained model to predict the study area. Comparing this model with three typical landslide susceptibility evaluation models based on ResNet and Support Vector Machine(SVM), the performance indicators Area Under Curve(AUC) values of the three models were 0.97, 0.77, and 0.65, respectively, with accuracies of 0.92, 0.70, and 0.69, indicating that the landslide susceptibility evaluation model based on ConvNeXt proposed in this paper has significant advantages.The landslide susceptibility can be accurately evaluated, and the scientific basis for the prevention and control of landslide disasters can be provided. Landslide Susceptibility Assessment Landslide-inducing factors ConvNeXt ResNet SVM Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 14 Nov, 2024 Reviewers invited by journal 29 Aug, 2024 Editor assigned by journal 19 Aug, 2024 First submitted to journal 16 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4897122","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":346769759,"identity":"f0bba337-3c47-47aa-9ef1-6cb0682831ab","order_by":0,"name":"Xiangwei Zhao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYDACdhBhYCPHz97Y+PADMTp4mEFkQZqxZM/hZmMJ4rV8OJS4YUZ6mwAPMVrsmdmfSfMYHEjcIPmwjUGCwU5Ot4GwLcnGPAZ3jLdLJ7Y9KAByzA4Q1nLwcY7BM9mdsxPbDSQYDiRuI6yFseFwjsFhxg03D7ZJ8BCnhZkRaMthxQ03GInVcpiN2fiPASiQE4GBbECEX9jb259JzvgDisrjDx9+qLCTI6gFDRiQpnwUjIJRMApGAQ4AAKzfP4+iGvakAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-2077-0390","institution":"Shandong University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Xiangwei","middleName":"","lastName":"Zhao","suffix":""},{"id":346769760,"identity":"b2d1ad6b-4dca-46ac-b510-2443e5fce17e","order_by":1,"name":"Haoquan Ma","email":"","orcid":"","institution":"Shandong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Haoquan","middleName":"","lastName":"Ma","suffix":""},{"id":346769761,"identity":"911ec7cd-25a1-42f7-a96e-394aecb7d9a8","order_by":2,"name":"Chong Niu","email":"","orcid":"","institution":"Shandong Geo-Survey and Mapping Institute","correspondingAuthor":false,"prefix":"","firstName":"Chong","middleName":"","lastName":"Niu","suffix":""},{"id":346769762,"identity":"b49c545d-a670-4433-a015-54f7cec8e875","order_by":3,"name":"Lei Gao","email":"","orcid":"","institution":"Lanzhou Resources \u0026 Environment Voc-Tech University","correspondingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Gao","suffix":""},{"id":346769763,"identity":"bca1a55a-3f2b-48d6-b278-18673f674648","order_by":4,"name":"Xianghui Kong","email":"","orcid":"","institution":"Shandong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Xianghui","middleName":"","lastName":"Kong","suffix":""}],"badges":[],"createdAt":"2024-08-12 02:42:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4897122/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4897122/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":65462884,"identity":"2944967e-d71b-4d7f-bf6c-bec26e91ad6e","added_by":"auto","created_at":"2024-09-27 18:24:36","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5503401,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript816.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4897122/v1_covered_6926f6f1-2498-4dcf-9f82-cbee23fae17d.pdf"}],"financialInterests":"","formattedTitle":"Landslide susceptibility assessment based on ConvNext in Longyang district of Baoshan city, China","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"natural-hazards","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nhaz","sideBox":"Learn more about [Natural Hazards](https://www.springer.com/journal/11069)","snPcode":"11069","submissionUrl":"https://submission.nature.com/new-submission/11069/3","title":"Natural Hazards","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Landslide Susceptibility Assessment, Landslide-inducing factors, ConvNeXt, ResNet, SVM","lastPublishedDoi":"10.21203/rs.3.rs-4897122/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4897122/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Landslide is a common type of geological disaster in the world, which causes great harm to people's life and financial security. 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