Spatiotemporal Dynamics of Land Use Change in Narayanganj Sadar (2002-2023) and Forecasting for 2035 Using CA-Markov Modeling

Rapid urbanization and industrial growth reshaped the landscape, making the environment and human life increasingly vulnerable. This study undergoes future land use prediction, which is necessary for future development and decision-making. Narayanganj had rapid industrial growth, and population pressure led to extensive urban expansion in the region. Using multi-temporal Landsat satellite imagery of 2002, 2014, and 2023, this research uses Cellular Automation Markov modeling to analyze Land Use Land Cover (LULC) transition dynamics for two decades and to project future trends up to 2035. The methodology for preprocessing satellite images in QGIS and ArcGIS to classify land use categories comprises built-up areas, water bodies, agricultural land, and homestead vegetation. Change detection techniques were used to track transitions in three individual periods (2002-2014, 2014-2023) and demonstrate an extreme rise of urban development from 17.64% up to 47.38% of urbanized areas, while the agricultural areas declined by 38.66% and water bodies by 4.78%. Results of the CA-Markov model, forecasting the LULC changes for 2035 through Idrisi Selva, indicate further urban growth at the expense of agricultural land and water resources. Some factors, like its proximity to the Capital City, rapid industrial development, and population pressure, led to extensive urban expansion in the region. The results suggest the need for urban planners to adopt green infrastructure, water conservation, and agricultural land protection as part of sustainable urban planning strategies to minimize the negative ecological impacts of urbanization for long-term environmental sustainability.

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Publication Details

Journal
Journal of Geographic Information System
Published
2025-01-01
DOI
https://doi.org/10.4236/jgis.2025.173008
Primary Topic
Land Use and Ecosystem Services
Type
article
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article

Spatiotemporal Dynamics of Land Use Change in Narayanganj Sadar (2002-2023) and Forecasting for 2035 Using CA-Markov Modeling

Zulfahmi Ali Rahman, Imran Ahmad, Al Rabby Siemens, Muhammad Shahidul Islam et al.
Journal of Geographic Information System
Land Use and Ecosystem Services
article

Spatiotemporal Dynamics of Land Use Change in Narayanganj Sadar (2002-2023) and Forecasting for 2035 Using CA-Markov Modeling

Zulfahmi Ali Rahman, Imran Ahmad, Al Rabby Siemens, Muhammad Shahidul Islam, Fardina Jahid Tahia, Eyanur Hossain
article en

Abstract

Rapid urbanization and industrial growth reshaped the landscape, making the environment and human life increasingly vulnerable. This study undergoes future land use prediction, which is necessary for future development and decision-making. Narayanganj had rapid industrial growth, and population pressure led to extensive urban expansion in the region. Using multi-temporal Landsat satellite imagery of 2002, 2014, and 2023, this research uses Cellular Automation Markov modeling to analyze Land Use Land Cover (LULC) transition dynamics for two decades and to project future trends up to 2035. The methodology for preprocessing satellite images in QGIS and ArcGIS to classify land use categories comprises built-up areas, water bodies, agricultural land, and homestead vegetation. Change detection techniques were used to track transitions in three individual periods (2002-2014, 2014-2023) and demonstrate an extreme rise of urban development from 17.64% up to 47.38% of urbanized areas, while the agricultural areas declined by 38.66% and water bodies by 4.78%. Results of the CA-Markov model, forecasting the LULC changes for 2035 through Idrisi Selva, indicate further urban growth at the expense of agricultural land and water resources. Some factors, like its proximity to the Capital City, rapid industrial development, and population pressure, led to extensive urban expansion in the region. The results suggest the need for urban planners to adopt green infrastructure, water conservation, and agricultural land protection as part of sustainable urban planning strategies to minimize the negative ecological impacts of urbanization for long-term environmental sustainability.

Journal of Geographic Information SystemVol. 17(03)
Climate action
Openalex Percentile: Top 85%
Land Use and Ecosystem Services
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