Housing Development Optimization: A Generalizable Framework with Case Studies for Toronto, Houston, and Perth

Housing Development Optimization: A Generalizable Framework with Case Studies for Toronto, Houston, and Perth | 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 Housing Development Optimization: A Generalizable Framework with Case Studies for Toronto, Houston, and Perth Jesse Ward-Bond, Elias B. Khalil, Shoshanna Saxe This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9087554/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 Housing development planning increasingly demands quantitative methods that can balance its many potential environmental and economic impacts. Existing planning tools are hand-tailored to particular geographic regions, thus limiting adaptability, and use data models that don’t reflect the actual urban form. Herein, we develop a generalizable mathematical programming framework for optimizing housing form and location at the spatial resolution of individual development sites. We show the adaptability of this framework by finding sustainable “gentle density” housing development plans in Toronto (Canada), Houston (USA), and Perth (Australia) under diverse sustainability objectives. We first focus on minimizing embodied greenhouse gas (GHG) emissions from housing construction, and find that these three cities can theoretically house their projected populations with minimums of 3.0, 12.4, and 15.7 Mt CO2-eq of embodied GHG emissions (respectively) from housing architectural and structural materials. We examine the trade off between embodied carbon emissions and spatial accessibility (Toronto), flood risk (Houston), and climate damage risk (Perth), and find that these multi-objective optimization scenarios can increase the embodied carbon emissions up to 166% above the single-objective scenarios. This work advances data-driven housing development optimization models by improving both spatial resolution and cross-city applicability. Earth and environmental sciences/Climate sciences Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Environmental social sciences Social science/Environmental studies Scientific community and society/Geography Social science/Geography housing optimization embodied GHG sustainability 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. 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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-9087554","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":607272225,"identity":"c8942470-e5c1-48be-8506-2323fdad29e1","order_by":0,"name":"Jesse Ward-Bond","email":"data:image/png;base64,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","orcid":"","institution":"University of Toronto","correspondingAuthor":true,"prefix":"","firstName":"Jesse","middleName":"","lastName":"Ward-Bond","suffix":""},{"id":607272226,"identity":"06ab4daf-cbc8-4065-b7e8-7df4911f4d59","order_by":1,"name":"Elias B. 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