Assessing Elderly Walkability to Urban Parks Using Mobility Analysis and Multi-Source Data: A Case Study of Central Fuzhou, China

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Abstract Ensuring equitable park access amid rapid urbanization and population ageing is essential. We propose an integrated framework that couples street-network impedance modelling with streetscape visual perception to assess elderly walkability to parks in central Fuzhou, China. A multi-source dataset—street networks, Street-View images, park polygons and demographic data—was compiled. Physical accessibility was calculated via weighted path impedance, whereas perceived accessibility was estimated by semantic segmentation of images and machine-learning calibration against expert scores. Combining the two yields a composite walkability index that exposes areas where dense networks coexist with poor visual environments and vice versa, delineating green corridors and under-served neighbourhoods. By fusing objective and subjective dimensions, the framework pinpoints priority zones for age-friendly design and scalable park-planning interventions.
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Assessing Elderly Walkability to Urban Parks Using Mobility Analysis and Multi-Source Data: A Case Study of Central Fuzhou, 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 Article Assessing Elderly Walkability to Urban Parks Using Mobility Analysis and Multi-Source Data: A Case Study of Central Fuzhou, China Min Wu¹², Kaige Zheng¹, Jiaxing Zhang¹³, Junhong Chen¹, Mingfei Li¹² This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7190867/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Ensuring equitable park access amid rapid urbanization and population ageing is essential. We propose an integrated framework that couples street-network impedance modelling with streetscape visual perception to assess elderly walkability to parks in central Fuzhou, China. A multi-source dataset—street networks, Street-View images, park polygons and demographic data—was compiled. Physical accessibility was calculated via weighted path impedance, whereas perceived accessibility was estimated by semantic segmentation of images and machine-learning calibration against expert scores. Combining the two yields a composite walkability index that exposes areas where dense networks coexist with poor visual environments and vice versa, delineating green corridors and under-served neighbourhoods. By fusing objective and subjective dimensions, the framework pinpoints priority zones for age-friendly design and scalable park-planning interventions. Physical sciences/Engineering Scientific community and society/Geography Social science/Geography Physical sciences/Mathematics and computing Elderly walkability Urban parks Streetscape perception Semantic segmentation Age-friendly cities Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 01 Sep, 2025 Reviews received at journal 01 Sep, 2025 Reviewers agreed at journal 24 Aug, 2025 Reviews received at journal 24 Aug, 2025 Reviewers agreed at journal 23 Aug, 2025 Reviewers agreed at journal 19 Aug, 2025 Reviewers invited by journal 18 Aug, 2025 Editor invited by journal 30 Jul, 2025 Editor assigned by journal 25 Jul, 2025 Submission checks completed at journal 24 Jul, 2025 First submitted to journal 22 Jul, 2025 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. 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