Ecological Suitability Evaluation of Traditional Village Locations in Jiangxi Province Based on Multi-Model Integration Using Artificial Intelligence

Ecological Suitability Evaluation of Traditional Village Locations in Jiangxi Province Based on Multi-Model Integration Using Artificial Intelligence | 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 Article Ecological Suitability Evaluation of Traditional Village Locations in Jiangxi Province Based on Multi-Model Integration Using Artificial Intelligence Cheng Zhang, Huimin Gong, Jinlin Teng, PeiLin Liu, Chunqing Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4749024/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 Traditional villages have evolved over time to adapt to their environmental characteristics, demonstrating high ecological suitability. Ideal village locations not only provide comfortable living spaces but also ensure safety and sustainability, reflecting the ancestors’ profound understanding of the natural environment and ecological wisdom. This study employs a multi-model integration approach using artificial intelligence to evaluate the ecological suitability of 413 traditional village sites in Jiangxi Province. It identifies key influencing factors and analyzes the ecological wisdom of ancestral site selection, resulting in an ecological suitability evaluation map for traditional village locations in Jiangxi Province. The study is based on environmental characteristic data of Jiangxi Province, including topography, climate, habitat quality, land use, air quality, vegetation cover, and river network density. GIS is used for spatial analysis and result visualization, and raster data are extracted and standardized. Machine learning methods such as Random Forest, Support Vector Machine, and Gradient Boosting Decision Trees, as well as deep learning methods such as Convolutional Neural Networks and Multilayer Perceptrons, are applied. Multi-model integration techniques are used to combine the predictions of various models, enhancing the accuracy and robustness of the ecological suitability evaluation. Experimental results indicate that elevation, slope, habitat quality, actual distance to water bodies, and average temperature are the main influencing factors for village site selection. The multi-model integration method performs excellently in evaluating ecological suitability, effectively identifying key ecological factors. The model’s accuracy and reliability are verified through confusion matrix, feature importance analysis, and ROC curve. This study evaluates the ecological suitability of traditional village sites in Jiangxi Province using a multi-model integration approach. By analyzing the impact weights of various ecological factors, it constructs a Composite Suitability Index (CSI) and generates an ecological suitability evaluation map, displaying suitability levels. This provides a scientific basis for the protection and rational development of traditional villages and serves as a reference for ecological site selection studies in other regions. Biological sciences/Ecology/Urban ecology Earth and environmental sciences/Environmental social sciences/Environmental impact Earth and environmental sciences/Environmental social sciences/Sustainability Full Text Additional Declarations No competing interests reported. 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. 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-4749024","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":340007059,"identity":"684db1eb-2cd8-45aa-95f9-b7a0607d8920","order_by":0,"name":"Cheng Zhang","email":"","orcid":"","institution":"College of Landscape Architecture and Art, Jiangxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Cheng","middleName":"","lastName":"Zhang","suffix":""},{"id":340007060,"identity":"ade103ca-b92f-48fe-beac-0f93187876a7","order_by":1,"name":"Huimin Gong","email":"","orcid":"","institution":"College of Landscape Architecture and Art, Jiangxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Huimin","middleName":"","lastName":"Gong","suffix":""},{"id":340007061,"identity":"2b766627-3123-4af6-9518-adcb146d862d","order_by":2,"name":"Jinlin Teng","email":"","orcid":"","institution":"College of Landscape Architecture and Art, Jiangxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Jinlin","middleName":"","lastName":"Teng","suffix":""},{"id":340007062,"identity":"400e1592-3e56-428c-a032-6f6bd5e65d47","order_by":3,"name":"PeiLin Liu","email":"","orcid":"","institution":"College of Landscape Architecture and Art, Jiangxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"PeiLin","middleName":"","lastName":"Liu","suffix":""},{"id":340007063,"identity":"f1b5b791-cece-4831-bd2d-e6144d169e88","order_by":4,"name":"Chunqing Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYBACPmYGBmYQg42BgfGBBETQAK8WNiQtzAbEaWGAagGxoToIaWHnMfxc2HZHtk+6/VqFZZtdYgN78zYJhpo7eBzGYyw9s+2ZcZvMmbIbEmeSExt4jpVJMBx7hk+LGTNv2+HENomctBsSFcyJDRI5ZhKMDYeJ01IgYVCf2CD/hmgt6ccYJCoOA23hIaSFrVia59xhY6AtzBISZ44bt/GkFVskHMOthZ//8MbPPGWHZefPSH/4WbKtWraf/fDGGx9qcGuBAcYGBh4DZlDEgGKKIYGgBrAW9geMH4hQOQpGwSgYBSMPAAAca0jbHwdJXwAAAABJRU5ErkJggg==","orcid":"","institution":"College of Landscape Architecture and Art, Jiangxi Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Chunqing","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-07-16 10:36:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4749024/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4749024/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":64273468,"identity":"6b10b1b3-acb0-4d49-95f1-2e6bde7c7a13","added_by":"auto","created_at":"2024-09-11 06:02:46","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5812783,"visible":true,"origin":"","legend":"","description":"","filename":"7.22EcologicalSuitabilityEvaluationofTraditionalVillageLocationsinJiangxiProvinceBasedonMultiModelIntegrationUsingArtificialIntelligence.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4749024/v1_covered_382a8297-0289-4f8f-b4d9-dae83d30b20c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Ecological Suitability Evaluation of Traditional Village Locations in Jiangxi Province Based on Multi-Model Integration Using Artificial Intelligence ","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"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},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4749024/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4749024/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Traditional villages have evolved over time to adapt to their environmental characteristics, demonstrating high ecological\nsuitability. Ideal village locations not only provide comfortable living spaces but also ensure safety and sustainability, reflecting\nthe ancestors’ profound understanding of the natural environment and ecological wisdom. This study employs a multi-model\nintegration approach using artificial intelligence to evaluate the ecological suitability of 413 traditional village sites in Jiangxi\nProvince. It identifies key influencing factors and analyzes the ecological wisdom of ancestral site selection, resulting in an\necological suitability evaluation map for traditional village locations in Jiangxi Province. The study is based on environmental\ncharacteristic data of Jiangxi Province, including topography, climate, habitat quality, land use, air quality, vegetation cover, and\nriver network density. GIS is used for spatial analysis and result visualization, and raster data are extracted and standardized.\nMachine learning methods such as Random Forest, Support Vector Machine, and Gradient Boosting Decision Trees, as well as\ndeep learning methods such as Convolutional Neural Networks and Multilayer Perceptrons, are applied. Multi-model integration\ntechniques are used to combine the predictions of various models, enhancing the accuracy and robustness of the ecological\nsuitability evaluation. Experimental results indicate that elevation, slope, habitat quality, actual distance to water bodies, and\naverage temperature are the main influencing factors for village site selection. The multi-model integration method performs\nexcellently in evaluating ecological suitability, effectively identifying key ecological factors. The model’s accuracy and reliability\nare verified through confusion matrix, feature importance analysis, and ROC curve. This study evaluates the ecological\nsuitability of traditional village sites in Jiangxi Province using a multi-model integration approach. By analyzing the impact\nweights of various ecological factors, it constructs a Composite Suitability Index (CSI) and generates an ecological suitability\nevaluation map, displaying suitability levels. This provides a scientific basis for the protection and rational development of\ntraditional villages and serves as a reference for ecological site selection studies in other regions.","manuscriptTitle":"Ecological Suitability Evaluation of Traditional Village Locations in Jiangxi Province Based on Multi-Model Integration Using Artificial Intelligence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-16 02:28:58","doi":"10.21203/rs.3.rs-4749024/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":"2fe5c33c-a384-4e7e-ad11-771df250babc","owner":[],"postedDate":"August 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":36019804,"name":"Biological sciences/Ecology/Urban ecology"},{"id":36019805,"name":"Earth and environmental sciences/Environmental social sciences/Environmental impact"},{"id":36019806,"name":"Earth and environmental sciences/Environmental social sciences/Sustainability"}],"tags":[],"updatedAt":"2024-09-11T05:54:33+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-16 02:28:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4749024","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4749024","identity":"rs-4749024","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}