Spatiotemporal assessment of environmental change in Kushtia, Bangladesh (1998–2023) using remote sensing-based environmental indices
Bangladesh’s rapidly evolving environment, influenced by land use and climate dynamics, requires effective monitoring systems. This study examines spatiotemporal environmental changes in Kushtia from 1998 to 2023, utilizing NDVI, NDWI, NDMI, and LST derived from multi-spectral satellite imagery. A P...
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Elsevier
2025-06-01
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| Series: | Environmental Challenges |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667010025000861 |
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| author | Md. Anik Hossain Md. Rahedul Islam Tamanna Yesmin Rabeya Sultana Md. Kamrul Hossain Rafiquel Islam |
| author_facet | Md. Anik Hossain Md. Rahedul Islam Tamanna Yesmin Rabeya Sultana Md. Kamrul Hossain Rafiquel Islam |
| author_sort | Md. Anik Hossain |
| collection | DOAJ |
| description | Bangladesh’s rapidly evolving environment, influenced by land use and climate dynamics, requires effective monitoring systems. This study examines spatiotemporal environmental changes in Kushtia from 1998 to 2023, utilizing NDVI, NDWI, NDMI, and LST derived from multi-spectral satellite imagery. A PCA-based weighted overlay method integrates these indices into a composite index to evaluate each year's overall environmental condition. Satellite images were processed in ENVI 5.3 and analyzed in ArcGIS 10.8, while PCA determined the weights of the indices. The weighted indices were overlaid in ArcGIS Pro 3.01, and image differencing was applied to detect environmental changes over time. The results represent a decline in the highest NDVI value from 0.72 in 1998 to 0.47 in 2023, reflecting an 18.23 % decrease in vegetated area coverage, while water availability (NDWI) and moisture content (NDMI) declined by 57.64 % and 47.01 %, respectively. Daulatpur experienced the highest reductions, with NDWI decreasing by 72.89 % and NDMI decreasing by 83.25 %, followed by Kumarkhali, which experienced a 51.16 % decline in NDWI. LST remained stable at 32.84 °C in 2023, with weak correlations to vegetation and water indices (R² < 0.13), indicating non-climatic drivers. PCA results suggest that PC1 (55.6 %) and PC2 (38.58 %) collectively account for 94.2 % of the environmental variation, with NDWI (weight: 0.312) and NDVI (weight: 0.298) as the dominant factors. PCA-weighted analysis reveals that degraded areas have shown improvement, while high-performing zones have experienced a decline. Environmental change was more significant from 1998 to 2010 than from 2010 to 2023, with notable degradation and recovery in Mirpur and Daulatpur. The findings emphasize the importance of adequate water governance, afforestation, and adaptive policies in addressing vegetation health and water stress. |
| format | Article |
| id | doaj-art-19eb5cfb976a4c30acb24a55358bf8e4 |
| institution | OA Journals |
| issn | 2667-0100 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Environmental Challenges |
| spelling | doaj-art-19eb5cfb976a4c30acb24a55358bf8e42025-08-20T02:20:09ZengElsevierEnvironmental Challenges2667-01002025-06-011910116710.1016/j.envc.2025.101167Spatiotemporal assessment of environmental change in Kushtia, Bangladesh (1998–2023) using remote sensing-based environmental indicesMd. Anik Hossain0Md. Rahedul Islam1Tamanna Yesmin2Rabeya Sultana3Md. Kamrul Hossain4Rafiquel Islam5Department of Geography and Environment, Islamic University, Kushtia 7003, BangladeshDepartment of Geography and Environment, Islamic University, Kushtia 7003, BangladeshDepartment of Geography and Environment, Islamic University, Kushtia 7003, BangladeshDepartment of Geography and Environment, Islamic University, Kushtia 7003, BangladeshDepartment of Geography and Environment, Islamic University, Kushtia 7003, BangladeshDepartment of Applied Chemistry and Chemical Engineering, Islamic University, Kushtia 7003, Bangladesh; School of Environmental and Life Sciences, The University of Newcastle, Callaghan, NSW 2308, Australia; Corresponding author.Bangladesh’s rapidly evolving environment, influenced by land use and climate dynamics, requires effective monitoring systems. This study examines spatiotemporal environmental changes in Kushtia from 1998 to 2023, utilizing NDVI, NDWI, NDMI, and LST derived from multi-spectral satellite imagery. A PCA-based weighted overlay method integrates these indices into a composite index to evaluate each year's overall environmental condition. Satellite images were processed in ENVI 5.3 and analyzed in ArcGIS 10.8, while PCA determined the weights of the indices. The weighted indices were overlaid in ArcGIS Pro 3.01, and image differencing was applied to detect environmental changes over time. The results represent a decline in the highest NDVI value from 0.72 in 1998 to 0.47 in 2023, reflecting an 18.23 % decrease in vegetated area coverage, while water availability (NDWI) and moisture content (NDMI) declined by 57.64 % and 47.01 %, respectively. Daulatpur experienced the highest reductions, with NDWI decreasing by 72.89 % and NDMI decreasing by 83.25 %, followed by Kumarkhali, which experienced a 51.16 % decline in NDWI. LST remained stable at 32.84 °C in 2023, with weak correlations to vegetation and water indices (R² < 0.13), indicating non-climatic drivers. PCA results suggest that PC1 (55.6 %) and PC2 (38.58 %) collectively account for 94.2 % of the environmental variation, with NDWI (weight: 0.312) and NDVI (weight: 0.298) as the dominant factors. PCA-weighted analysis reveals that degraded areas have shown improvement, while high-performing zones have experienced a decline. Environmental change was more significant from 1998 to 2010 than from 2010 to 2023, with notable degradation and recovery in Mirpur and Daulatpur. The findings emphasize the importance of adequate water governance, afforestation, and adaptive policies in addressing vegetation health and water stress.http://www.sciencedirect.com/science/article/pii/S2667010025000861Remote sensingEnvironmental changeSpatiotemporal analysisEnvironmental indicesPrincipal component analysis (PCA)Kushtia district |
| spellingShingle | Md. Anik Hossain Md. Rahedul Islam Tamanna Yesmin Rabeya Sultana Md. Kamrul Hossain Rafiquel Islam Spatiotemporal assessment of environmental change in Kushtia, Bangladesh (1998–2023) using remote sensing-based environmental indices Environmental Challenges Remote sensing Environmental change Spatiotemporal analysis Environmental indices Principal component analysis (PCA) Kushtia district |
| title | Spatiotemporal assessment of environmental change in Kushtia, Bangladesh (1998–2023) using remote sensing-based environmental indices |
| title_full | Spatiotemporal assessment of environmental change in Kushtia, Bangladesh (1998–2023) using remote sensing-based environmental indices |
| title_fullStr | Spatiotemporal assessment of environmental change in Kushtia, Bangladesh (1998–2023) using remote sensing-based environmental indices |
| title_full_unstemmed | Spatiotemporal assessment of environmental change in Kushtia, Bangladesh (1998–2023) using remote sensing-based environmental indices |
| title_short | Spatiotemporal assessment of environmental change in Kushtia, Bangladesh (1998–2023) using remote sensing-based environmental indices |
| title_sort | spatiotemporal assessment of environmental change in kushtia bangladesh 1998 2023 using remote sensing based environmental indices |
| topic | Remote sensing Environmental change Spatiotemporal analysis Environmental indices Principal component analysis (PCA) Kushtia district |
| url | http://www.sciencedirect.com/science/article/pii/S2667010025000861 |
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