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Modelling Land Cover Changes in Peri-Urban Areas: A Case Study of George Town Conurbation, Malaysia

Author

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  • Narimah Samat

    (Geography Section, School of Humanities, Universiti Sains Malaysia, 11800 Penang, Malaysia)

  • Mohd Amirul Mahamud

    (Geography Section, School of Humanities, Universiti Sains Malaysia, 11800 Penang, Malaysia)

  • Mou Leong Tan

    (Geography Section, School of Humanities, Universiti Sains Malaysia, 11800 Penang, Malaysia)

  • Mohammad Javad Maghsoodi Tilaki

    (Geography Section, School of Humanities, Universiti Sains Malaysia, 11800 Penang, Malaysia)

  • Yi Lin Tew

    (Geography Section, School of Humanities, Universiti Sains Malaysia, 11800 Penang, Malaysia)

Abstract

Drastic growth of urban populations has caused expansion of peri-urban areas—the transitional zone between a city and its hinterland. Although urbanisation may bring economic opportunities and improve infrastructure in an area, uncontrolled urban expansion towards peri-urban areas will negatively impact the environment and the community living within the area. Malaysia, for example, has become one of the most urbanised countries in East Asia. However, cities in Malaysia are relatively small and less densely populated compared with other cities in East Asia. This indicates that urban expansion has been sprawling towards peri-urban areas, and not being controlled and properly managed. To ensure urban expansions occur sustainably, urban growth boundary (UGB) can potentially be used as a mechanism to contain and limit urban expansion, and allow urban growth to be planned to achieve sustainable development. A scientific approach is essential to determine an UGB that allows future growth to be predicted and taken into consideration. Potentially, urban spatial models have been widely used to plan and predict future urban expansions. George Town Conurbation, the second largest urban conurbation in Malaysia, has been chosen as the study area in this study. This study aims to demonstrate the application of a GIS-Cellular Automata model, known as FutureSim, which was developed to simulate land cover changes and generate a designated UGB for this area. The model was developed based on the transition rule derived from land cover changes, from 2010 to 2018, and then used to predict future land cover changes under two different planning scenarios—compact growth and urban sprawl scenarios. With the accuracy of the model exceeding 74%, FutureSim was used to predict land cover change until 2030. The model can potentially be used to assist planners and policymakers to make decisions on the allocation of sustainable land use and planning for rapidly developing regions.

Suggested Citation

  • Narimah Samat & Mohd Amirul Mahamud & Mou Leong Tan & Mohammad Javad Maghsoodi Tilaki & Yi Lin Tew, 2020. "Modelling Land Cover Changes in Peri-Urban Areas: A Case Study of George Town Conurbation, Malaysia," Land, MDPI, vol. 9(10), pages 1-16, October.
  • Handle: RePEc:gam:jlands:v:9:y:2020:i:10:p:373-:d:423959
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    References listed on IDEAS

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    1. Beynon, Malcolm, 2002. "DS/AHP method: A mathematical analysis, including an understanding of uncertainty," European Journal of Operational Research, Elsevier, vol. 140(1), pages 148-164, July.
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    Cited by:

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    2. Zhiyin Wang & Jiansheng Cao, 2021. "Assessing and Predicting the Impact of Multi-Scenario Land Use Changes on the Ecosystem Service Value: A Case Study in the Upstream of Xiong’an New Area, China," Sustainability, MDPI, vol. 13(2), pages 1-20, January.
    3. Paweł Dziekański & Piotr Prus & Mansoor Maitah & Magdalena Wrońska, 2021. "Assessment of Spatial Diversity of the Potential of the Natural Environment in the Context of Sustainable Development of Poviats in Poland," Energies, MDPI, vol. 14(19), pages 1-27, September.
    4. Jiaojiao Luo & Wei Wang & Yuzhe Wu & Yi Peng & Linlin Zhang, 2021. "Analysis of an Urban Development Boundary Policy in China Based on the IAD Framework," Land, MDPI, vol. 10(8), pages 1-17, August.
    5. Alysha van Duynhoven & Suzana Dragićević, 2021. "Exploring the Sensitivity of Recurrent Neural Network Models for Forecasting Land Cover Change," Land, MDPI, vol. 10(3), pages 1-29, March.
    6. Mashitoh Yaacob & Winnie Wing-Mui So & Noriko Iizuka, 2022. "Exploring Community Perceptions of Climate Change Issues in Peninsular Malaysia," Sustainability, MDPI, vol. 14(13), pages 1-23, June.
    7. Dong-jin Lee & Seong Woo Jeon, 2020. "Estimating Changes in Habitat Quality through Land-Use Predictions: Case Study of Roe Deer ( Capreolus pygargus tianschanicus ) in Jeju Island," Sustainability, MDPI, vol. 12(23), pages 1-18, December.
    8. Xiufeng Cao & Zhaoshun Liu & Shujie Li & Zhenjun Gao, 2022. "Integrating the Ecological Security Pattern and the PLUS Model to Assess the Effects of Regional Ecological Restoration: A Case Study of Hefei City, Anhui Province," IJERPH, MDPI, vol. 19(11), pages 1-19, May.

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