Automated Estimation of Urban Vertical Greenery Potential

Automated Estimation of Urban Vertical Greenery Potential | 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 Automated Estimation of Urban Vertical Greenery Potential Aruscha Kramm, Isabel Holler, Eric Peukert, André Ludwig, Bogdan Franczyk This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8548920/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 Cities are increasingly threatened by the effects of rising temperatures. Due to the heat island effect, cities experience greater heat stress, leading to increased energy demand and reduced quality of life. Vertical greenery systems (VGSs), such as green facades and living walls, offer a spatially efficient strategy to mitigate these impacts. The environmental and social benefits of vertical greenery are well established. However, large-scale implementation is lacking methods that integrate relevant data to compute the variety of factors determining a surface’s suitability. This paper aims to fill this gap by introducing a computational method for evaluating the potential of individual building walls for vertical greening. Using the city of Leipzig as a case study, the approach integrates 3D building data (LoD2) with street view imagery to compute key factors such as orientation or Window-to-Wall Ratio (WWR). These factors are then integrated into a composite index prioritizing walls with high potential for reducing urban heat stress. The study thus provides a practical tool for urban planners and policymakers to support targeted climate adaptation strategies. Artificial Intelligence and Machine Learning heat stress vertical greenery climate change smart city street view images digital twins Full Text Additional Declarations The authors declare no competing interests. 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-8548920","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":571333877,"identity":"0af97625-4580-4a38-b7e5-a9438af7f79d","order_by":0,"name":"Aruscha 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Due to the heat island effect, cities experience greater heat stress, leading to increased energy demand and reduced quality of life. Vertical greenery systems (VGSs), such as green facades and living walls, offer a spatially efficient strategy to mitigate these impacts. The environmental and social benefits of vertical greenery are well established. However, large-scale implementation is lacking methods that integrate relevant data to compute the variety of factors determining a surface’s suitability.\u003c/p\u003e\n\u003cp\u003eThis paper aims to fill this gap by introducing a computational method for evaluating the potential of individual building walls for vertical greening. Using the city of Leipzig as a case study, the approach integrates 3D building data (LoD2) with street view imagery to compute key factors such as orientation or Window-to-Wall Ratio (WWR). 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