The First National-Scale High-Resolution Land Use Land Cover Map of Bangladesh Using Multi-Temporal Optical and SAR Imagery
Rattachement africain : jp, in, au, bd. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Bangladesh is highly susceptible to land use land cover (LULC) changes due to its geographical location and dense population. These changes have significant effects on food security, urban development, and natural resource management. Policy planning and resource management largely depend on accurate and detailed LULC maps. However, Bangladesh does not have its own national scale detailed high-resolution LULC maps. This study aims to develop high-resolution land use land cover (HRLULC) maps for Bangladesh for the years 2020 and 2023 using a deep learning method based on convolutional neural network (CNN), and to analyze LULC changes between these years. We used an advanced LULC classification algorithm, namely SACLASS2, that was developed by JAXA to work on multi-temporal satellite data from different sensors. Our HRLULC maps with 14 categories achieved an overall accuracy of 94.55 ± 0.41% with Kappa coefficient 0.93 for 2020 and 94.32 ± 0.42% with Kappa coefficient 0.93 for 2023, which is higher than the commonly accepted standard of around 87 overall accuracy for 14 category LULC map. Between 2020 and 2023, the most notable LULC increase were observed in single cropland (17 ± 4%), aquaculture (20 ± 5%), and brickfield (56 ± 25%). Conversely, decrease occurred for salt pans (47 ± 16%), bare land (24 ± 3%), and built-up (13 ± 3%). These findings offer valuable insights into the spatio-temporal patterns of LULC in Bangladesh, which can support policymakers in making informed decisions and developing effective conservation strategies aimed at promoting sustainable land management and urban planning.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- The First National-Scale High-Resolution Land Use Land Cover Map of Bangladesh Using Multi-Temporal Optical and SAR Imagery
- Date Crossref
- 06/11/2025
- Éditeur
- MDPI AG
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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University of Tsukuba Institute of Life and Environmental Sciences pays non établi dans la noticeUniversité ou école supérieure
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Department of Higher Education pays non établi dans la noticeOrganisme public
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Japan Aerospace Exploration Agency pays non établi dans la noticeStructure de recherche
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The University of Adelaide pays non établi dans la noticeUniversité ou école supérieure
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Ministry of Public Administration pays non établi dans la noticeOrganisme public
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Remote Sensing Technology Center of Japan pays non établi dans la noticeStructure de recherche
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Ministry of Agriculture Department of Agricultural Extension (DAE) pays non établi dans la noticeOrganisme public
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Graduate School of Science and Technology pays non établi dans la noticeUniversité ou école supérieure
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Secondary and Higher Education pays non établi dans la noticeInstitution
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Independent Researcher pays non établi dans la noticeInstitution
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Earth Observation Research Center pays non établi dans la noticeStructure de recherche
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School of Chemical Engineering pays non établi dans la noticeUniversité ou école supérieure
Institute of Life and Environmental Sciences — University of Tsukuba, Department of Higher Education et Japan Aerospace Exploration Agency, avec 9 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.