Change analyses and prediction of land use and land cover changes in Bernam River Basin, Malaysia

Land use and land cover (LULC) change is a dynamic process which is significantly influenced by anthropogenic activities. Analysing historical LULC trends and predicting future dynamics is critical to provide insights for decision-makers and planners aiming for sustainable land management and develo...

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Main Authors: Kondum, F.A., Rowshon, Md.K., Luqman, C.A., Hasfalina, C.M., Zakari, M.D.
Format: Article
Language:English
Published: Elsevier B.V. 2024
Online Access:http://psasir.upm.edu.my/id/eprint/115131/1/115131.pdf
http://psasir.upm.edu.my/id/eprint/115131/
https://linkinghub.elsevier.com/retrieve/pii/S2352938524001459
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spelling my.upm.eprints.1151312025-02-21T07:24:46Z http://psasir.upm.edu.my/id/eprint/115131/ Change analyses and prediction of land use and land cover changes in Bernam River Basin, Malaysia Kondum, F.A. Rowshon, Md.K. Luqman, C.A. Hasfalina, C.M. Zakari, M.D. Land use and land cover (LULC) change is a dynamic process which is significantly influenced by anthropogenic activities. Analysing historical LULC trends and predicting future dynamics is critical to provide insights for decision-makers and planners aiming for sustainable land management and development. This study focuses on the Bernam River Basin (BRB). It employs an integrated approach that combines the Multi-Layer Perceptron (MLP), the Cellular Automata (CA)-Markov algorithm, remote sensing, and Geographical Information System (GIS) techniques. Using multi-temporal 10m resolution Sentinel-2 Landsat imagery from 2010, 2020, and 2022, the study classified LULC into seven categories: water, forest, wetlands, agriculture, urban, barren, and rangeland areas. Change analysis from 2010 to 2020 was conducted, with 2022 validating predicted LULC transitions. The MLP model, trained on land change driver variables, facilitated the generation of transition potentials for simulating future LULC changes. A spatially explicit CA-Markov model implemented LULC change projections for 2022, 2025, 2050, and 2075, based on the transition potentials. The analysis reveals an annual increase of 0.24% in water, 0.61% in forest, and 2.11% in urban areas, while wetlands (2.69%), agriculture (2.47%), barren (3.51%), and rangeland (4.58%) experienced declines. The CA-Markov approach accurately predicted LULC transitions for 2022, validated through an error matrix with an overall accuracy of 91.56% based on 450 sampling points. Predictions for 2025–2075 indicate rising trends in water (1.76%), wetlands (29.18%), agriculture (60.08%), urban (96.53%), barren (0.59%), and rangeland areas (3.57%). Forests are expected to decrease by 12% (261.52 km2). The study identified agriculture and urban expansion as the primary drivers of LULC changes in the river basin. These findings provide critical information for regional authorities to formulate evidence-based policies and management strategies, ensuring the environmental sustainability of BRB. Furthermore, these predicted LULC patterns can be integrated into complementary models, such as the Soil and Water Assessment Tool, to assess the impacts of LULC changes on water resources. Elsevier B.V. 2024 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/115131/1/115131.pdf Kondum, F.A. and Rowshon, Md.K. and Luqman, C.A. and Hasfalina, C.M. and Zakari, M.D. (2024) Change analyses and prediction of land use and land cover changes in Bernam River Basin, Malaysia. Remote Sensing Applications: Society and Environment, 36. art. no. 101281. pp. 1-14. ISSN 2352-9385; eISSN: 2352-9385 https://linkinghub.elsevier.com/retrieve/pii/S2352938524001459 10.1016/j.rsase.2024.101281
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Land use and land cover (LULC) change is a dynamic process which is significantly influenced by anthropogenic activities. Analysing historical LULC trends and predicting future dynamics is critical to provide insights for decision-makers and planners aiming for sustainable land management and development. This study focuses on the Bernam River Basin (BRB). It employs an integrated approach that combines the Multi-Layer Perceptron (MLP), the Cellular Automata (CA)-Markov algorithm, remote sensing, and Geographical Information System (GIS) techniques. Using multi-temporal 10m resolution Sentinel-2 Landsat imagery from 2010, 2020, and 2022, the study classified LULC into seven categories: water, forest, wetlands, agriculture, urban, barren, and rangeland areas. Change analysis from 2010 to 2020 was conducted, with 2022 validating predicted LULC transitions. The MLP model, trained on land change driver variables, facilitated the generation of transition potentials for simulating future LULC changes. A spatially explicit CA-Markov model implemented LULC change projections for 2022, 2025, 2050, and 2075, based on the transition potentials. The analysis reveals an annual increase of 0.24% in water, 0.61% in forest, and 2.11% in urban areas, while wetlands (2.69%), agriculture (2.47%), barren (3.51%), and rangeland (4.58%) experienced declines. The CA-Markov approach accurately predicted LULC transitions for 2022, validated through an error matrix with an overall accuracy of 91.56% based on 450 sampling points. Predictions for 2025–2075 indicate rising trends in water (1.76%), wetlands (29.18%), agriculture (60.08%), urban (96.53%), barren (0.59%), and rangeland areas (3.57%). Forests are expected to decrease by 12% (261.52 km2). The study identified agriculture and urban expansion as the primary drivers of LULC changes in the river basin. These findings provide critical information for regional authorities to formulate evidence-based policies and management strategies, ensuring the environmental sustainability of BRB. Furthermore, these predicted LULC patterns can be integrated into complementary models, such as the Soil and Water Assessment Tool, to assess the impacts of LULC changes on water resources.
format Article
author Kondum, F.A.
Rowshon, Md.K.
Luqman, C.A.
Hasfalina, C.M.
Zakari, M.D.
spellingShingle Kondum, F.A.
Rowshon, Md.K.
Luqman, C.A.
Hasfalina, C.M.
Zakari, M.D.
Change analyses and prediction of land use and land cover changes in Bernam River Basin, Malaysia
author_facet Kondum, F.A.
Rowshon, Md.K.
Luqman, C.A.
Hasfalina, C.M.
Zakari, M.D.
author_sort Kondum, F.A.
title Change analyses and prediction of land use and land cover changes in Bernam River Basin, Malaysia
title_short Change analyses and prediction of land use and land cover changes in Bernam River Basin, Malaysia
title_full Change analyses and prediction of land use and land cover changes in Bernam River Basin, Malaysia
title_fullStr Change analyses and prediction of land use and land cover changes in Bernam River Basin, Malaysia
title_full_unstemmed Change analyses and prediction of land use and land cover changes in Bernam River Basin, Malaysia
title_sort change analyses and prediction of land use and land cover changes in bernam river basin, malaysia
publisher Elsevier B.V.
publishDate 2024
url http://psasir.upm.edu.my/id/eprint/115131/1/115131.pdf
http://psasir.upm.edu.my/id/eprint/115131/
https://linkinghub.elsevier.com/retrieve/pii/S2352938524001459
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score 13.244413