Urban Heat and Vegetation Dynamics in Rajshahi City: A Google Earth Engine- Based Analysis from 2005 to 2024

Urban Heat and Vegetation Dynamics in Rajshahi City: A Google Earth Engine- Based Analysis from 2005 to 2024 | 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 Heat and Vegetation Dynamics in Rajshahi City: A Google Earth Engine- Based Analysis from 2005 to 2024 Roni Roy This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8949028/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 Understanding the spatiotemporal dynamics of urban surface temperature and vegetation health is vital for sustainable urban planning, particularly in rapidly developing cities such as Rajshahi. This study analyzes long-term changes in Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Health Vegetation Index (HVI), Urban Heat Island (UHI), and Urban Thermal Field Variance Index (UTFVI) within Rajshahi City Corporation over 20 years, from 2005 to 2024. Multitemporal Landsat imagery and the cloud-based Google Earth Engine (GEE) platform were employed to examine three key time points 2005, 2015, and 2024, and assess the impacts of urban expansion and vegetation loss on the urban thermal environment. Results reveal a consistent increase in both LST and UHI intensity. In 2005, LST ranged from 23.49°C to 38.57°C, rising to 24.21°C to 41.34°C by 2024. Correspondingly, UHI values intensified from a range of –1.063 to 2.458 in 2005 to –3.79 to 4.97 in 2024. NDVI and HVI values declined in the urban core, indicating vegetation degradation, while UTFVI patterns reflected increasing ecological thermal stress, especially in densely built-up areas. Spatial analyses confirmed that impervious surfaces are associated with higher heat stress, whereas vegetated zones help mitigate thermal impact. The integration of remote sensing indices with GEE’s processing capabilities offers an efficient and scalable approach for monitoring urban climate dynamics. These findings provide actionable insights for urban planners and policymakers to implement nature-based solutions, improve thermal comfort, and enhance ecological resilience in Rajshahi’s evolving urban landscape. LST UHI UTFVI Google Earth Engine Rajshahi City Corporation 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. 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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-8949028","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":598889766,"identity":"2772d894-dfdb-42e7-8d45-80dd572de75b","order_by":0,"name":"Roni Roy","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYJCCA1Ca8QGQ4OEjRQuzAUgLGym2sUmASULKzNt7Dx6uqDjMIO/efKzya46dDBsD88NHN/BokTlzLuHgmTOHGQzPHEu7LbstGegwNmPjHDxaJCRyDA42tgG1zMgxuy25jRmohYdNmjgt89+YFUtuqydBi7wEjxnjx22HidDCc8bgYMOZdB4DnrRkacZtx3nYmAn5hb3H+GNDhbWcfPvhgx9/bqu252dvfvgYnxYoaOYxOACMSx4Qm5mwchCoY5BvAKaYH8SpHgWjYBSMghEGAAg2RDjvZSU/AAAAAElFTkSuQmCC","orcid":"","institution":"University of Rajshahi","correspondingAuthor":true,"prefix":"","firstName":"Roni","middleName":"","lastName":"Roy","suffix":""}],"badges":[],"createdAt":"2026-02-23 16:12:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8949028/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8949028/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104400700,"identity":"69a7769c-3805-41fa-bedf-87d307c6b11e","added_by":"auto","created_at":"2026-03-11 12:10:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1859266,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8949028/v1_covered_a6660ebc-2735-4f00-a129-6261ffe697c2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Urban Heat and Vegetation Dynamics in Rajshahi City: A Google Earth Engine- Based Analysis from 2005 to 2024","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"LST, UHI, UTFVI, Google Earth Engine, Rajshahi City Corporation","lastPublishedDoi":"10.21203/rs.3.rs-8949028/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8949028/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Understanding the spatiotemporal dynamics of urban surface temperature and vegetation health is vital for sustainable urban planning, particularly in rapidly developing cities such as Rajshahi. This study analyzes long-term changes in Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Health Vegetation Index (HVI), Urban Heat Island (UHI), and Urban Thermal Field Variance Index (UTFVI) within Rajshahi City Corporation over 20 years, from 2005 to 2024. Multitemporal Landsat imagery and the cloud-based Google Earth Engine (GEE) platform were employed to examine three key time points 2005, 2015, and 2024, and assess the impacts of urban expansion and vegetation loss on the urban thermal environment. Results reveal a consistent increase in both LST and UHI intensity. In 2005, LST ranged from 23.49°C to 38.57°C, rising to 24.21°C to 41.34°C by 2024. Correspondingly, UHI values intensified from a range of –1.063 to 2.458 in 2005 to –3.79 to 4.97 in 2024. NDVI and HVI values declined in the urban core, indicating vegetation degradation, while UTFVI patterns reflected increasing ecological thermal stress, especially in densely built-up areas. Spatial analyses confirmed that impervious surfaces are associated with higher heat stress, whereas vegetated zones help mitigate thermal impact. The integration of remote sensing indices with GEE’s processing capabilities offers an efficient and scalable approach for monitoring urban climate dynamics. 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