Urban Green Space Accessibility and its Spatial Relationship with Appearance Parameters, Surface Temperature and Heat Fluxes

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Abstract This study aims to assess the spatial distribution of urban green areas on a citywide scale, utilizing Moran's Index to analyze spatial correlations within the city center. The results indicate that green spaces are clustered, with a Moran's Index of 0.49 when analyzed by average integration value and 0.36 based on population distribution. Anselin Local Moran's I cluster analysis reveals that 12% of green areas in the Low-Low Cluster are co-located in regions accessed by a smaller population, while 23.3% in the High-High Cluster are located in areas accessed by a larger population. Hot-cold spot analysis determined the optimal fixed distance for urban green space to be 849.83 meters, with 29.4% of green areas having fewer than eight neighboring areas within this distance band. A similar analysis based on street integration identified 1661.15 meters as the ideal fixed distance. Furthermore, the study examines the influence of urban geometry on environmental factors by analyzing the effects of sky, building, and tree view factors (SVF, BVF, TVF) on surface temperature (LST) and heat fluxes (SHF, LHF). Notably, Heydar Aliyev Park exhibited high integration and vegetation-related values but lower LST and accessibility scores.
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Urban Green Space Accessibility and its Spatial Relationship with Appearance Parameters, Surface Temperature and Heat Fluxes | 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 Urban Green Space Accessibility and its Spatial Relationship with Appearance Parameters, Surface Temperature and Heat Fluxes Ömer ÜNSAL, Başak AYATLI, Ali Can KUZULUGİL This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5721756/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 This study aims to assess the spatial distribution of urban green areas on a citywide scale, utilizing Moran's Index to analyze spatial correlations within the city center. The results indicate that green spaces are clustered, with a Moran's Index of 0.49 when analyzed by average integration value and 0.36 based on population distribution. Anselin Local Moran's I cluster analysis reveals that 12% of green areas in the Low-Low Cluster are co-located in regions accessed by a smaller population, while 23.3% in the High-High Cluster are located in areas accessed by a larger population. Hot-cold spot analysis determined the optimal fixed distance for urban green space to be 849.83 meters, with 29.4% of green areas having fewer than eight neighboring areas within this distance band. A similar analysis based on street integration identified 1661.15 meters as the ideal fixed distance. Furthermore, the study examines the influence of urban geometry on environmental factors by analyzing the effects of sky, building, and tree view factors (SVF, BVF, TVF) on surface temperature (LST) and heat fluxes (SHF, LHF). Notably, Heydar Aliyev Park exhibited high integration and vegetation-related values but lower LST and accessibility scores. Space syntax Spatial statistics Urban green space (UGS) SVF BVF TVF LHF SHF LST NDVI Moran's Index Anselin Local Moran's I analysis Optimized Hot Spot analysis 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. 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