Assessing Landslide Susceptibility in Indian Himalayas: Comparing Polygon and Point-Based Inventories with Modified Frequency Ratio Approach

Assessing Landslide Susceptibility in Indian Himalayas: Comparing Polygon and Point-Based Inventories with Modified Frequency Ratio Approach | 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 Assessing Landslide Susceptibility in Indian Himalayas: Comparing Polygon and Point-Based Inventories with Modified Frequency Ratio Approach IMRAN KHAN, Harish Bahuguna, Ashutosh Kainthola, D. P. Kanungo, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3944252/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study examines the effects of using point and polygon-based landslide inventory on the process of mapping landslide susceptibility in the Northwestern Indian Himalayas. The modified frequency ratio method was utilized to generate the landslide susceptibility map, applying classification through the define, equal, geometric, natural break, and quantile reclassification procedures. Comparative analyses were performed to compare the polygon-based and point-based landslide susceptibility maps using different reclassification methods. The polygon-based methodology achieved success rates/prediction rates of 75.0%/75.4%, 76.1%/76.4%, 77.9%/78.4%, 77.9%/78.4%, and 78.1%/78.6% for the define, equal, geometric, natural break, and quantile classification methods, respectively. On the other hand, the point-based strategy resulted in success rates/prediction rates of 81.8%/82.1%, 83.0%/83.2%, 84.2%/84.6%, 84.3%/84.6%, and 83.5%/83.7% for the respective categorization techniques. The results showed that the point-based landslide susceptibility map had a higher performance in terms of AUC values, but the polygon-based map was better at portraying ground conditions. Geometric, natural break, and quantile reclassification methods consistently shown superior performance compared to define and equal methods in both point and polygon-based approaches. Although both point and polygon-based inventories showed acceptable levels of accuracy, it is advisable to use the polygon-based technique, provided that the necessary data and computer resources are available. This research provides useful insights into the selection of inventory types and classification methods for the accurate mapping of landslide susceptibility in the rugged terrain of the Northwestern Indian Himalayas. Landslide Susceptibility Mapping Modified Frequency Ratio Northwestern Himalaya India Full Text Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-3944252","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":282073306,"identity":"bfbbfb5d-6f9b-4991-8338-87f65f5ac390","order_by":0,"name":"IMRAN KHAN","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIiWNgGAWjYFACxoYDIIqNvQFIGliQoIWPB0QZSJBgmZxEAogiQou8/+HGQzf32OWxST6/uuFHgQQDf3t3Al4thjcSGw7nPEsuZpPOKbvZA3SYxJmzG/BrmcEI1HKAObFNOiftBg9Qi4FELgEt/QdBWuoT2yTPpN38Q4wWeQaQww4cTmyTYD92myhbDCTAWo4ntvHksN2WMZDgIegX+f7jjz/nHKhOnN9+/NnNN39s5PjbewnYcgDO5DEAk3iVg21pgDPZHxBUPQpGwSgYBSMTAADYwEwHNZ1H7QAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-7377-5251","institution":"Banaras Hindu University","correspondingAuthor":true,"prefix":"","firstName":"IMRAN","middleName":"","lastName":"KHAN","suffix":""},{"id":282073307,"identity":"0a81703c-ac0c-4481-86f4-91a5c1abb2c9","order_by":1,"name":"Harish Bahuguna","email":"","orcid":"","institution":"Geological Survey of India","correspondingAuthor":false,"prefix":"","firstName":"Harish","middleName":"","lastName":"Bahuguna","suffix":""},{"id":282073308,"identity":"bbc1f5c2-bf1f-4908-8cd0-616791a34b49","order_by":2,"name":"Ashutosh Kainthola","email":"","orcid":"","institution":"Banaras Hindu University Faculty of Science","correspondingAuthor":false,"prefix":"","firstName":"Ashutosh","middleName":"","lastName":"Kainthola","suffix":""},{"id":282073309,"identity":"49b61425-efd5-4025-927a-963ce688b99c","order_by":3,"name":"D. 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The modified frequency ratio method was utilized to generate the landslide susceptibility map, applying classification through the define, equal, geometric, natural break, and quantile reclassification procedures. Comparative analyses were performed to compare the polygon-based and point-based landslide susceptibility maps using different reclassification methods. The polygon-based methodology achieved success rates/prediction rates of 75.0%/75.4%, 76.1%/76.4%, 77.9%/78.4%, 77.9%/78.4%, and 78.1%/78.6% for the define, equal, geometric, natural break, and quantile classification methods, respectively. On the other hand, the point-based strategy resulted in success rates/prediction rates of 81.8%/82.1%, 83.0%/83.2%, 84.2%/84.6%, 84.3%/84.6%, and 83.5%/83.7% for the respective categorization techniques. The results showed that the point-based landslide susceptibility map had a higher performance in terms of AUC values, but the polygon-based map was better at portraying ground conditions. 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This research provides useful insights into the selection of inventory types and classification methods for the accurate mapping of landslide susceptibility in the rugged terrain of the Northwestern Indian Himalayas.\u003c/p\u003e","manuscriptTitle":"Assessing Landslide Susceptibility in Indian Himalayas: Comparing Polygon and Point-Based Inventories with Modified Frequency Ratio Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-25 05:12:15","doi":"10.21203/rs.3.rs-3944252/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a3707a8e-cafa-4cd8-a75a-01e6ad62f622","owner":[],"postedDate":"March 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-18T13:40:59+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-25 05:12:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3944252","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3944252","identity":"rs-3944252","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}