Assessment of Land Use/Land Cover Dynamics and Urban Growth Patterns Using Geospatial Technology: A Study of Sylhet Sadar Upazila, Bangladesh

Assessment of Land Use/Land Cover Dynamics and Urban Growth Patterns Using Geospatial Technology: A Study of Sylhet Sadar Upazila, Bangladesh | 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 Assessment of Land Use/Land Cover Dynamics and Urban Growth Patterns Using Geospatial Technology: A Study of Sylhet Sadar Upazila, Bangladesh Md. Iftaul Ahad, Syeda Ayshia Akter, Muhammad Jasim Uddin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5439045/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 Urban growth in developing nations, such as Bangladesh, is frequently rapid and unplanned due to inadequate Land Use Land Cover (LULC) management. This study examines the spatiotemporal dynamics of LULC changes and urban growth patterns in Sylhet Sadar Upazila, a rapidly urbanizing area in northeastern Bangladesh, from 1989 to 2019. Using Landsat satellite imagery and Geographic Information Systems (GIS) with remote sensing technologies, LULC classifications were performed via the supervised maximum likelihood algorithm. Shannon entropy analysis was applied to assess urban sprawl patterns. The results reveal significant transformations in the study area: built-up areas increased by 8.44%, while water bodies and vegetation declined by 7.8% and 18.7%, respectively. Arable land grew by 17.10%, reflecting agricultural expansion, and barren land saw a 0.99% rise. The most intense urbanization occurred between 2009 and 2019, where vegetation decreased by 10% and built-up areas surged by 4.46%. Urban growth expanded tenfold from Sylhet City Corporation (SCC)'s Central Business District (CBD) and demonstrated a scattered pattern across the first two buffer zones. The entropy values, consistently above 0.5, indicate increasingly dispersed urban expansion, with the highest entropy (0.81) observed in the Khadimnagar union. These trends pose challenges for sustainable urban management, including inefficient infrastructure use and environmental degradation. The study emphasizes the need for integrated land management strategies and compact urban growth to balance development with environmental sustainability. The findings provide crucial insights for urban planners and policymakers in rapidly developing regions facing similar urbanization pressures. Land Use/Land Cover (LULC) Urban Growth GIS and Remote Sensing Maximum Likelihood Classification Shannon’s entropy. 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. 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-5439045","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":414279779,"identity":"47257dc2-f03e-4d64-877e-2be966e2cc68","order_by":0,"name":"Md. 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