Integrating stratified best-worst method and GIS for landslide susceptibility assessment: A case study in Erzurum province (Turkey)

Integrating stratified best-worst method and GIS for landslide susceptibility assessment: A case study in Erzurum province (Turkey) | 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 Integrating stratified best-worst method and GIS for landslide susceptibility assessment: A case study in Erzurum province (Turkey) ZEKERİYA KONURHAN, Melih Yucesan, Muhammet Gul This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2244162/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Oct, 2023 Read the published version in Environmental Science and Pollution Research → Version 1 posted You are reading this latest preprint version Abstract Landslides are among the most destructive geological disasters that seriously damage human life and infrastructures. Landslides mostly occur in mountainous regions around the world. One of the key processes to reduce these damages is to uncover landslide-exposed areas through different data-driven methods such as Geographical Information System (GIS) and Multi-Criteria Decision-Making (MCDM). In the literature, there are many studies developed with these fundamental tools. In this study, unlike the literature, a new landslide susceptibility assessment model is proposed by integrating GIS with the stratified best-worst method (S-BWM). This model has four main dimensions and 16 sub-dimensions under topography, environment-land, location and hydrological factors, which are weighted with the S-BWM. Considering the different states that may arise in the importance weights of these dimensions in the future, a network was created. The transition probabilities of these states were predicted and injected into the classical BWM. Then maps were created for these dimensions and classifications were made for each sub-dimension according to the map characteristics. Finally, the most susceptive landslide locations were determined with GIS-based calculations. To demonstrate the model's applicability, a case study was conducted for the Erzurum region, one of Turkey's landslide-prone regions. In addition, besides the landslide map, an analysis and discussion about the spatial distribution of susceptibility classes was presented, contributing to the study's robustness. landslide susceptibility GIS Best-worst method stratification S-MCDM Erzurum Full Text Supplementary Files Graphicalabstract.docx Highlights.docx Cite Share Download PDF Status: Published Journal Publication published 18 Oct, 2023 Read the published version in Environmental Science and Pollution Research → 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. We do this by developing innovative software and high quality services for the global research community. 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