Impact of Land Use Land Cover Change on Land Surface Temperature in Small and Medium Sized Cities in South Asia: A Remote Sensing Approach

Impact of Land Use Land Cover Change on Land Surface Temperature in Small and Medium Sized Cities in South Asia: A Remote Sensing Approach | 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 Impact of Land Use Land Cover Change on Land Surface Temperature in Small and Medium Sized Cities in South Asia: A Remote Sensing Approach Faiyad H Rishal, Chandana Mitra, Al Artat Bin Ali, Sheikh Tawhidul Islam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7586805/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 Rapid urbanization impacts the surrounding urban environment in multiple ways, with the Urban Heat Island (UHI) effect being one of the most critical, driven by concrete surfaces and anthropogenic activities that create a rural–urban temperature difference. Climate change, coupled with these land use changes, increases the vulnerability of city dwellers to extreme heat. South Asia, home to millions of urban residents, faces heatwaves that are rising in both intensity and frequency. This study examines Land Use Land Cover (LULC) change in nine cities across five South Asian countries between 2003 and 2023 and explores its correlation with Land Surface Temperature (LST). Using the Random Forest machine learning model on the Google Earth Engine (GEE) platform, LULC classification was performed with 70–120 training points per land type for the year 2003 and 2023. Results show that built-up areas expanded in all cities, while vegetation, water, and other land types declined, except in Ahmedabad, where greenery increased due to planned vegetation. The LULC classification achieved high overall accuracy (>96%) with moderate validation accuracy. Mean annual LST increased across all cities, averaging 3.2°C. Correlation analysis indicates that built-up areas exert the strongest influence on LST, vegetation provides moderate cooling, and water has little impact due to its limited extent. Urban Heat Island South Asia Land Use Land Cover Change Land Surface Temperature Google Earth Engine Small and Medium Sized Cities 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. 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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-7586805","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":513361927,"identity":"328cb6a9-812a-4807-8324-3865710adf4d","order_by":0,"name":"Faiyad H Rishal","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYBAC9hkMDAcSDGzkGBh4oEIHCGjhucHA+OBDRZoxSVqYDWecOZzYQLwW6d5n0rxtzOn9M3KPSVfuYJDju5FAQIvMcTOgFrbcGTfy0iTPnmEwliSkxV4ijQ2ohSe34UaOmWRjG0PiBoK2QLRIpMtDtdQTowXkfYMEA6gWIIOwFlAgJxhuPPMu2bKxTcJw5pkHBLWAovK/vNzx3IM3G9ts5PmOE7AFHUiQpnwUjIJRMApGAXYAAOOJRBH8nzcyAAAAAElFTkSuQmCC","orcid":"","institution":"Auburn University","correspondingAuthor":true,"prefix":"","firstName":"Faiyad","middleName":"H","lastName":"Rishal","suffix":""},{"id":513361928,"identity":"5fd736c7-76c8-4444-9f25-547379c70d07","order_by":1,"name":"Chandana Mitra","email":"","orcid":"","institution":"Auburn University","correspondingAuthor":false,"prefix":"","firstName":"Chandana","middleName":"","lastName":"Mitra","suffix":""},{"id":513361929,"identity":"6b164c04-c776-423b-af5c-babd31c3aa2c","order_by":2,"name":"Al Artat Bin Ali","email":"","orcid":"","institution":"Auburn University","correspondingAuthor":false,"prefix":"","firstName":"Al","middleName":"Artat Bin","lastName":"Ali","suffix":""},{"id":513361930,"identity":"19ddb489-c012-464a-b291-562861f30de1","order_by":3,"name":"Sheikh Tawhidul Islam","email":"","orcid":"","institution":"Jahangirnagar University","correspondingAuthor":false,"prefix":"","firstName":"Sheikh","middleName":"Tawhidul","lastName":"Islam","suffix":""}],"badges":[],"createdAt":"2025-09-11 02:08:15","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7586805/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7586805/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91219379,"identity":"f7056fd5-db56-4d53-9155-c4a0badee1da","added_by":"auto","created_at":"2025-09-12 20:42:02","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1722565,"visible":true,"origin":"","legend":"","description":"","filename":"ESEVS2501562.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7586805/v1_covered_0c8a9b4b-33e2-4310-8945-7571780e0429.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eImpact of Land Use Land Cover Change on Land Surface Temperature in Small and Medium Sized Cities in South Asia: A Remote Sensing Approach\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Auburn University","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":"Urban Heat Island, South Asia, Land Use Land Cover Change, Land Surface Temperature, Google Earth Engine, Small and Medium Sized Cities","lastPublishedDoi":"10.21203/rs.3.rs-7586805/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7586805/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRapid urbanization impacts the surrounding urban environment in multiple ways, with the Urban Heat Island (UHI) effect being one of the most critical, driven by concrete surfaces and anthropogenic activities that create a rural–urban temperature difference. Climate change, coupled with these land use changes, increases the vulnerability of city dwellers to extreme heat. South Asia, home to millions of urban residents, faces heatwaves that are rising in both intensity and frequency. This study examines Land Use Land Cover (LULC) change in nine cities across five South Asian countries between 2003 and 2023 and explores its correlation with Land Surface Temperature (LST). Using the Random Forest machine learning model on the Google Earth Engine (GEE) platform, LULC classification was performed with 70–120 training points per land type for the year 2003 and 2023. Results show that built-up areas expanded in all cities, while vegetation, water, and other land types declined, except in Ahmedabad, where greenery increased due to planned vegetation. The LULC classification achieved high overall accuracy (\u0026gt;96%) with moderate validation accuracy. Mean annual LST increased across all cities, averaging 3.2°C. Correlation analysis indicates that built-up areas exert the strongest influence on LST, vegetation provides moderate cooling, and water has little impact due to its limited extent.\u003c/p\u003e","manuscriptTitle":"Impact of Land Use Land Cover Change on Land Surface Temperature in Small and Medium Sized Cities in South Asia: A Remote Sensing Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-12 20:33:54","doi":"10.21203/rs.3.rs-7586805/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"d8e23538-4773-46f5-b9bd-03093baf8b31","owner":[],"postedDate":"September 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-12T20:33:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-12 20:33:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7586805","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7586805","identity":"rs-7586805","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}