Cellular Automata approach in dynamic modelling of land cover changes using RapidEye images in Dhaka, Bangladesh
Satellite images have been used extensively to identify the land use/land cover (LULC) changes in Bangladesh. However, no study has been conducted to classify LULC changes in the Dhaka Metropolitan Development Plan (DMDP) area using high-resolution commercial satellite images. The study aimed to sim...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-08-01
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| Series: | Environmental Challenges |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667010021000639 |
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| author | Abdulla - Al Kafy Md. Nazmul Huda Naim Gangaraju Subramanyam Abdullah-Al- Faisal Nessar Uddin Ahmed Abdullah Al Rakib Marium Akter Kona Golam Sabbir Sattar |
| author_facet | Abdulla - Al Kafy Md. Nazmul Huda Naim Gangaraju Subramanyam Abdullah-Al- Faisal Nessar Uddin Ahmed Abdullah Al Rakib Marium Akter Kona Golam Sabbir Sattar |
| author_sort | Abdulla - Al Kafy |
| collection | DOAJ |
| description | Satellite images have been used extensively to identify the land use/land cover (LULC) changes in Bangladesh. However, no study has been conducted to classify LULC changes in the Dhaka Metropolitan Development Plan (DMDP) area using high-resolution commercial satellite images. The study aimed to simulate future LULC scenarios using RapidEye commercial images in the fastest-growing DMDP area. Support Vector Machine algorithm was applied to estimate the LULC scenarios for years 2012, 2015, and 2018. Cellular Automata machine learning algorithm was used to simulate the future LULC scenarios for 2025. The study result revealed that a significant net increase in the urban areas (UAs) by 15.52%, a remarkable decrease in sparse vegetation (SV) by 12.48%, and a transformation of 17.83% green cover (SV and dense vegetation) areas by 14.95% (8.9%/year) UAs were found from 2012 to 2018. Prediction results demonstrated that UAs would likely to be expanded by 53% and SV will be reduced by 13% (28% was in 2012) in 2025. The outcomes of this study will help the city authorities of DMDP in preparing a comprehensive micro-level urban development plan, where planned infrastructural development and supervision, land use planning, natural resource conservation, and environmental sustainability will be ensured. |
| first_indexed | 2024-12-16T15:22:02Z |
| format | Article |
| id | doaj.art-4d5eb6f73efe430b82e285e39b8e1d84 |
| institution | Directory Open Access Journal |
| issn | 2667-0100 |
| language | English |
| last_indexed | 2024-12-16T15:22:02Z |
| publishDate | 2021-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Environmental Challenges |
| spelling | doaj.art-4d5eb6f73efe430b82e285e39b8e1d842022-12-21T22:26:36ZengElsevierEnvironmental Challenges2667-01002021-08-014100084Cellular Automata approach in dynamic modelling of land cover changes using RapidEye images in Dhaka, BangladeshAbdulla - Al Kafy0Md. Nazmul Huda Naim1Gangaraju Subramanyam2Abdullah-Al- Faisal3Nessar Uddin Ahmed4Abdullah Al Rakib5Marium Akter Kona6Golam Sabbir Sattar7Department of Urban & Regional Planning, Rajshahi University of Engineering & Technology (RUET), Rajshahi 6204, Bangladesh; ICLEI South Asia, Rajshahi City Corporation, Rajshahi 6203, Bangladesh; Corresponding author: Urban Planner & City Project Officer, ICLEI South Asia, Rajshahi City Corporation, Rajshahi, 6203, Bangladesh.Department of Urban & Regional Planning, Chittagong University of Engineering & Technology (CUET), Chattogram 4349, Bangladesh; NGO Forum for Public Health, Cox’s Bazar, Bangladesh.Regional Agricultural Research Station, Tirupati, IndiaDepartment of Urban & Regional Planning, Rajshahi University of Engineering & Technology (RUET), Rajshahi 6204, Bangladesh; GIS Unit, Operational Centre Amsterdam (OCA), Médecins Sans Frontières (MSF), Cox's Bazar 4750, BangladeshDepartment of Urban & Regional Planning, Bangladesh University of Engineering & Technology (BUET), Dhaka 1000, Bangladesh; Development Design Consultants Limited, Dhaka 1212, BangladeshDepartment of Urban & Regional Planning, Rajshahi University of Engineering & Technology (RUET), Rajshahi 6204, BangladeshDepartment of Civil Engineering, Bangladesh Army University of Engineering and Technology, Natore, BangladeshInstitute of Environmental Science, University of Rajshahi, Rajshahi 6205, BangladeshSatellite images have been used extensively to identify the land use/land cover (LULC) changes in Bangladesh. However, no study has been conducted to classify LULC changes in the Dhaka Metropolitan Development Plan (DMDP) area using high-resolution commercial satellite images. The study aimed to simulate future LULC scenarios using RapidEye commercial images in the fastest-growing DMDP area. Support Vector Machine algorithm was applied to estimate the LULC scenarios for years 2012, 2015, and 2018. Cellular Automata machine learning algorithm was used to simulate the future LULC scenarios for 2025. The study result revealed that a significant net increase in the urban areas (UAs) by 15.52%, a remarkable decrease in sparse vegetation (SV) by 12.48%, and a transformation of 17.83% green cover (SV and dense vegetation) areas by 14.95% (8.9%/year) UAs were found from 2012 to 2018. Prediction results demonstrated that UAs would likely to be expanded by 53% and SV will be reduced by 13% (28% was in 2012) in 2025. The outcomes of this study will help the city authorities of DMDP in preparing a comprehensive micro-level urban development plan, where planned infrastructural development and supervision, land use planning, natural resource conservation, and environmental sustainability will be ensured.http://www.sciencedirect.com/science/article/pii/S2667010021000639Land cover dynamicsRapidEye imagesSupport Vector MachineCellular Automata |
| spellingShingle | Abdulla - Al Kafy Md. Nazmul Huda Naim Gangaraju Subramanyam Abdullah-Al- Faisal Nessar Uddin Ahmed Abdullah Al Rakib Marium Akter Kona Golam Sabbir Sattar Cellular Automata approach in dynamic modelling of land cover changes using RapidEye images in Dhaka, Bangladesh Environmental Challenges Land cover dynamics RapidEye images Support Vector Machine Cellular Automata |
| title | Cellular Automata approach in dynamic modelling of land cover changes using RapidEye images in Dhaka, Bangladesh |
| title_full | Cellular Automata approach in dynamic modelling of land cover changes using RapidEye images in Dhaka, Bangladesh |
| title_fullStr | Cellular Automata approach in dynamic modelling of land cover changes using RapidEye images in Dhaka, Bangladesh |
| title_full_unstemmed | Cellular Automata approach in dynamic modelling of land cover changes using RapidEye images in Dhaka, Bangladesh |
| title_short | Cellular Automata approach in dynamic modelling of land cover changes using RapidEye images in Dhaka, Bangladesh |
| title_sort | cellular automata approach in dynamic modelling of land cover changes using rapideye images in dhaka bangladesh |
| topic | Land cover dynamics RapidEye images Support Vector Machine Cellular Automata |
| url | http://www.sciencedirect.com/science/article/pii/S2667010021000639 |
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