{"paper_id":"17432439-07fd-49ca-a67b-3be1a43bbd67","body_text":"Determination of vegetation degradation using NDVI analysis in the Sundarbans from 1975 to 2025 | 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 Determination of vegetation degradation using NDVI analysis in the Sundarbans from 1975 to 2025 Md. Redwanur Rahman, Md. Imran Hossain, Mst. Tasnima Khatun, Mohammed Mukhlesur Rahman, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7442087/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 The world’s largest mangrove forest is situated in the southwestern part of Bangladesh, which is known as the Sundarbans. The Sundarbans was recognized as a world heritage in 1997. The Sundarbans plays a crucial role in biodiversity conservation, coastal protection, and carbon sequestration. Despite its ecological importance, day by day the famous forest is faced with biotic and abiotic interferences such as salinity intrusion, elevated mean sea level, and human-induced disturbances, etc. The aim of the study was to determine vegetation variations from 1975 to 2025 using Landsat-derived Normalized Difference Vegetation Index (NDVI) data and imagery from Landsat 2, 5, 8, and 9, etc. The total vegetation areas were classified into no vegetation, thin vegetation, and dense vegetation groups. Afforestation and deforestation trends were also detected from 1975 to 2025. The findings of the present study revealed that dense vegetation was dropped by over 34%, while non-vegetation areas expanded by 6% during five decades. The maximum deforestation occurred between 2015 and 2025 in the southern and southeastern zones of the Sundarbans, and the afforestation rate was also higher between 2005 and 2015. This study identified spatial hotspots of ecological change and underscores the limitations of NDVI only approaches while proposing a replicable remote sensing framework for mangrove monitoring. The results of the study will be helpful to offer critical insights for conservation planning and sustainable management of the Sundarbans and other vulnerable coastal ecosystems all over the world. Afforestation and deforestation Landsat imagery mangrove forest NDVI vegetation dynamics 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-7442087\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":504614818,\"identity\":\"0cee49b0-d0e0-4013-9252-c9f134e59981\",\"order_by\":0,\"name\":\"Md. Redwanur Rahman\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Rajshahi\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Md.\",\"middleName\":\"Redwanur\",\"lastName\":\"Rahman\",\"suffix\":\"\"},{\"id\":504614819,\"identity\":\"8bdaafaa-369d-404f-9be9-6abadfb03ab4\",\"order_by\":1,\"name\":\"Md. Imran Hossain\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Rajshahi\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Md.\",\"middleName\":\"Imran\",\"lastName\":\"Hossain\",\"suffix\":\"\"},{\"id\":504614820,\"identity\":\"86c93445-926e-4017-8fa4-db0fc635f187\",\"order_by\":2,\"name\":\"Mst. 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The Sundarbans was recognized as a world heritage in 1997. The Sundarbans plays a crucial role in biodiversity conservation, coastal protection, and carbon sequestration. Despite its ecological importance, day by day the famous forest is faced with biotic and abiotic interferences such as salinity intrusion, elevated mean sea level, and human-induced disturbances, etc. The aim of the study was to determine vegetation variations from 1975 to 2025 using Landsat-derived Normalized Difference Vegetation Index (NDVI) data and imagery from Landsat 2, 5, 8, and 9, etc. The total vegetation areas were classified into no vegetation, thin vegetation, and dense vegetation groups. Afforestation and deforestation trends were also detected from 1975 to 2025. The findings of the present study revealed that dense vegetation was dropped by over 34%, while non-vegetation areas expanded by 6% during five decades. 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