Multiple Bayesian models approach to assessing drivers of cultural heritage spatial distribution: Insights from Lushan County, China

Multiple Bayesian models approach to assessing drivers of cultural heritage spatial distribution: Insights from Lushan County, 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 Multiple Bayesian models approach to assessing drivers of cultural heritage spatial distribution: Insights from Lushan County, China Yuxi Liu, Xinyu Du, Yu Bai, Qibing Chen, Dong Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5491027/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Aug, 2025 Read the published version in npj Heritage Science → Version 1 posted 9 You are reading this latest preprint version Abstract Cultural heritage is a historical gift that connects the past and the present, carrying the material and cultural connotations of various historical periods. This study combines Bayesian modelling with geographic feature images to assess the general influence patterns and differential effects of drivers on the spatial distribution of cultural heritage in Lushan County. The results indicate that: (1) the hierarchical Bayesian model can effectively identify the potential heterogeneity of drivers across different heritage types and provide a quantification of the variations in the intensities of these drivers. (2) The spatial distribution of cultural heritage in Lushan County shows a "south-dense, north-sparse" pattern. The density of cultural heritage is generally negatively correlated with elevation, slope, and distances from water systems, settlements and cultural centers, while it is generally positively correlated with distance from geological hazard sites. (3) The effect of social factors on the spatial distribution of cultural heritage is significantly greater than that of natural factors, demonstrating that the formation and evolution of cultural heritage are profoundly shaped by human activities. (4) The effect of each driver varies in intensity for different types of cultural heritage, with significant differences in correlations. By comparing three Bayesian models, this study reveals the application potential of the hierarchical Bayesian model in research on the relationship between the spatial distribution of cultural heritage and its environment, with a view to providing data-driven methodological and theoretical references for research related to cultural heritage. Bayesian model Machine learning Cultural heritage Spatial distribution drivers Lushan County Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 21 Aug, 2025 Read the published version in npj Heritage Science → Version 1 posted Editorial decision: Revision requested 01 Jan, 2025 Reviews received at journal 01 Jan, 2025 Reviews received at journal 23 Dec, 2024 Reviewers agreed at journal 04 Dec, 2024 Reviewers agreed at journal 04 Dec, 2024 Reviewers invited by journal 03 Dec, 2024 Editor assigned by journal 22 Nov, 2024 Submission checks completed at journal 22 Nov, 2024 First submitted to journal 20 Nov, 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. 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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-5491027","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":386280488,"identity":"f586c739-8b77-4c9b-9855-63d8d2b3db4f","order_by":0,"name":"Yuxi Liu","email":"","orcid":"","institution":"Sichuan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yuxi","middleName":"","lastName":"Liu","suffix":""},{"id":386280489,"identity":"64113144-271a-4dfc-a727-173c1a5eb2e9","order_by":1,"name":"Xinyu Du","email":"","orcid":"","institution":"Sichuan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xinyu","middleName":"","lastName":"Du","suffix":""},{"id":386280490,"identity":"3f4957fb-76c8-460a-a3b3-1ea5d920b151","order_by":2,"name":"Yu Bai","email":"","orcid":"","institution":"Sichuan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Bai","suffix":""},{"id":386280491,"identity":"b5f6d022-fbcd-46f3-ada7-9832aa6dd4a9","order_by":3,"name":"Qibing Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtUlEQVRIiWNgGAWjYFACHsYHDAYQpgSxWpgNSNbCBldJnBb+9txjlT8K7OQNDjAfvM3DYJdHUIvEmXdpt3kMkg03HGBLtuZhSC4mqMVAIsfsNoPBAcYNB3jMpHkYDiQ2EKOl8IfBAfsNB/i/Ea+FgcfgQCLQFjbitAD9kiwN9EvyzMNsxpZzDJIJawGG2MGPP/7Y2fYdb354402FHWEtDAwJUJoZ7E7C6pG0jIJRMApGwSjABQCCrDcBqPfYNAAAAABJRU5ErkJggg==","orcid":"","institution":"Sichuan Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Qibing","middleName":"","lastName":"Chen","suffix":""},{"id":386280492,"identity":"6a48568e-bdae-48a3-856c-7f6db1f56cbe","order_by":4,"name":"Dong Liu","email":"","orcid":"","institution":"Primary school with nine years program in Sigong Town","correspondingAuthor":false,"prefix":"","firstName":"Dong","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-11-20 12:53:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5491027/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5491027/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s40494-025-01941-2","type":"published","date":"2025-08-21T15:56:57+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89847115,"identity":"d0a914e8-c2f5-4e0c-a85b-5c6048f5fa4d","added_by":"auto","created_at":"2025-08-25 16:40:26","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1270282,"visible":true,"origin":"","legend":"","description":"","filename":"MultipleBayesianmodelsapproachtoassessingdriversofculturalheritagespatialdistributionInsightsfromLushanCountyChina.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5491027/v1_covered_4e3fc548-0e45-4758-bfb6-d141ff349d5f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multiple Bayesian models approach to assessing drivers of cultural heritage spatial distribution: Insights from Lushan County, China","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-heritage-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hsci","sideBox":"Learn more about [Heritage Science](http://heritagesciencejournal.springeropen.com)","snPcode":"40494","submissionUrl":"https://submission.nature.com/new-submission/40494/3","title":"npj Heritage Science","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Bayesian model, Machine learning, Cultural heritage, Spatial distribution drivers, Lushan County","lastPublishedDoi":"10.21203/rs.3.rs-5491027/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5491027/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCultural heritage is a historical gift that connects the past and the present, carrying the material and cultural connotations of various historical periods. 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