Spatial distribution characteristics and influencing factors of  Tujia traditional villages in the Youshui River Basin：A Multiscale Geographically Weighted Regression  Approach

Spatial distribution characteristics and influencing factors of Tujia traditional villages in the Youshui River Basin：A Multiscale Geographically Weighted Regression 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 Article Spatial distribution characteristics and influencing factors of Tujia traditional villages in the Youshui River Basin：A Multiscale Geographically Weighted Regression Approach Gong Chen, Nianshuo Wen, Hui Chen, Shaoyao He, Min Xie, Guangyu Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7406001/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Traditional villages embody important elements of agricultural civilization and ethnic cultural heritage, yet they face growing pressure from rapid urbanization. Understanding the spatiotemporal differentiation and driving mechanisms of these villages is crucial for their preservation and sustainable development. Taking 168 Tujia traditional villages (TTV) in the Youshui River Basin (YRB) as the study sample, this study employs the Nearest Neighbor Index, Kernel Density Estimation, and Multiscale Geographically Weighted Regression to systematically analyze their spatiotemporal distribution characteristics and influencing factors. The results of the study show that: ( 1 ) Spatially, the villages exhibit a "west-dense, east-sparse" pattern and form a structure characterized by "two primary clusters accompanied by several secondary clusters." Temporally, the formation spans a wide era with distinct differences in quantity and aggregation across historical periods, the spatial evolution of TTV demonstrates a clear dependence on the river system. ( 2 ) The MGWR model outperforms the classic GWR by identifying the specific spatial action scales (bandwidths) of different variables. Natural factors (slope) and historical factors (distance to Tusi administrative centers) operate as macroscopic stable factors, revealing the long-term effects of environmental backgrounds and historical institutions on spatial patterns. In contrast, social factors (urbanization rate and road network density) exhibit strong local spatial heterogeneity. ( 3 ) The study reveals a four-dimensional coupled driving mechanism where natural factors establish the physical foundation and "passive protection" barriers; livelihood factors reflect adaptive survival wisdom; historical factors exert a profound institutional anchoring effect; and social factors play a dual role of screening and reshaping under modern development. By quantifying the multiscale impacts of these four types of factors, this study provides a solid empirical basis for the differentiated preservation, refined management, and coordinated regional development of traditional villages in multi-ethnic areas. Social science/Environmental studies Scientific community and society/Geography Social science/Geography Humanities/History Social science/History Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 10 Mar, 2026 Reviewers agreed at journal 17 Feb, 2026 Reviewers agreed at journal 15 Feb, 2026 Reviewers invited by journal 13 Feb, 2026 Submission checks completed at journal 06 Feb, 2026 First submitted to journal 06 Feb, 2026 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. 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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-7406001","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":592536907,"identity":"c9f90d78-e86f-4afc-9e96-d6c3b0bb3d62","order_by":0,"name":"Gong Chen","email":"","orcid":"","institution":"Hunan University","correspondingAuthor":false,"prefix":"","firstName":"Gong","middleName":"","lastName":"Chen","suffix":""},{"id":592536908,"identity":"d3fb631a-1f50-428d-a7eb-6a5b3c43f098","order_by":1,"name":"Nianshuo Wen","email":"","orcid":"","institution":"Wuhan 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Understanding the spatiotemporal differentiation and driving mechanisms of these villages is crucial for their preservation and sustainable development. Taking 168 Tujia traditional villages (TTV) in the Youshui River Basin (YRB) as the study sample, this study employs the Nearest Neighbor Index, Kernel Density Estimation, and Multiscale Geographically Weighted Regression to systematically analyze their spatiotemporal distribution characteristics and influencing factors. The results of the study show that: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Spatially, the villages exhibit a \"west-dense, east-sparse\" pattern and form a structure characterized by \"two primary clusters accompanied by several secondary clusters.\" Temporally, the formation spans a wide era with distinct differences in quantity and aggregation across historical periods, the spatial evolution of TTV demonstrates a clear dependence on the river system. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) The MGWR model outperforms the classic GWR by identifying the specific spatial action scales (bandwidths) of different variables. Natural factors (slope) and historical factors (distance to Tusi administrative centers) operate as macroscopic stable factors, revealing the long-term effects of environmental backgrounds and historical institutions on spatial patterns. In contrast, social factors (urbanization rate and road network density) exhibit strong local spatial heterogeneity. 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