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Assessment of Land Use Land Cover Changes and Future Predictions Using CA-ANN Simulation for Gazipur City Corporation, Bangladesh

Author

Listed:
  • Md Shihab Uddin

    (Department of Water Resources Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh)

  • Badal Mahalder

    (Department of Water Resources Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh)

  • Debabrata Mahalder

    (Center for Natural Resource Studies, Dhaka 1213, Bangladesh)

Abstract

Anthropogenic activities have a significant influence on land use and land cover (LULC) changes, especially in rapidly growing areas. Among several models, the combination of a cellular automata–artificial neural network (CA-ANN) model is being widely used for assessing future LULC changes using satellite images. This study aimed to investigate LULC changes in Gazipur City Corporation (GCC), Bangladesh, and the changes in LULC patterns over the last two decades (2002 to 2022). In this study, the maximum likelihood supervised classification technique was used for processing the available satellite images. The results show that the urban area and vegetation coverage increased by 150% and 22.78%, whereas the bare land and waterbody decreased by 7.02% and 78.9%, respectively, from 2002 to 2022 inside the GCC area. For future LULC predictions, the CA-ANN model was developed, the accuracy percentage of which was 86.49%, and the kappa value was 0.83. The future LULC prediction model results show that the urban area will increase by 47.61%, whereas the bare land and waterbody are supposed to decrease by 24.17% and 67.23%, respectively, by 2042. The findings of this study could be useful for future sustainable urban planning and management, as well as enabling decision making by authorities for improvements in environmental and ecological conditions in the study area.

Suggested Citation

  • Md Shihab Uddin & Badal Mahalder & Debabrata Mahalder, 2023. "Assessment of Land Use Land Cover Changes and Future Predictions Using CA-ANN Simulation for Gazipur City Corporation, Bangladesh," Sustainability, MDPI, vol. 15(16), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:16:p:12329-:d:1216368
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    References listed on IDEAS

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    1. Rizwan Muhammad & Wenyin Zhang & Zaheer Abbas & Feng Guo & Luc Gwiazdzinski, 2022. "Spatiotemporal Change Analysis and Prediction of Future Land Use and Land Cover Changes Using QGIS MOLUSCE Plugin and Remote Sensing Big Data: A Case Study of Linyi, China," Land, MDPI, vol. 11(3), pages 1-24, March.
    2. Taher Osman & Prasanna Divigalpitiya & Takafumi Arima, 2016. "Using the SLEUTH urban growth model to simulate the impacts of future policy scenarios on land use in the Giza Governorate, Greater Cairo Metropolitan region," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 20(3), pages 407-426, September.
    3. Griselda Vázquez-Quintero & Raúl Solís-Moreno & Marín Pompa-García & Federico Villarreal-Guerrero & Carmelo Pinedo-Alvarez & Alfredo Pinedo-Alvarez, 2016. "Detection and Projection of Forest Changes by Using the Markov Chain Model and Cellular Automata," Sustainability, MDPI, vol. 8(3), pages 1-13, March.
    4. Muhammad Hadi Saputra & Han Soo Lee, 2019. "Prediction of Land Use and Land Cover Changes for North Sumatra, Indonesia, Using an Artificial-Neural-Network-Based Cellular Automaton," Sustainability, MDPI, vol. 11(11), pages 1-16, May.
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