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Achieving a Sustainable Urban Form through Land Use Optimisation: Insights from Bekasi City’s Land-Use Plan (2010–2030)

Author

Listed:
  • Rahmadya Trias Handayanto

    (Information Management, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand)

  • Nitin Kumar Tripathi

    (Remote Sensing and GIS, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand)

  • Sohee Minsun Kim

    (Urban Environmental Management, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand)

  • Sumanta Guha

    (Computer Science, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand)

Abstract

Cities worldwide have been trying to achieve a sustainable urban form to handle their rapid urban growth. Many sustainable urban forms have been studied and two of them, the compact city and the eco city, were chosen in this study as urban form foundations. Based on these forms, four sustainable city criteria (compactness, compatibility, dependency, and suitability) were considered as necessary functions for land use optimisation. This study presents a land use optimisation as a method for achieving a sustainable urban form. Three optimisation methods (particle swarm optimisation, genetic algorithms, and a local search method) were combined into a single hybrid optimisation method for land use in Bekasi city, Indonesia. It was also used for examining Bekasi city’s land-use-plan (2010–2030) after optimising current (2015) and future land use (2030). After current land use optimisation, the score of sustainable city criteria increased significantly. Three important centres of land use (commercial, industrial, and residential) were also created through clustering the results. These centres were slightly different from centres of the city plan zones. Additional land uses in 2030 were predicted using a nonlinear autoregressive neural network with external input. Three scenarios were used for allocating these additional land uses including sustainable development, government policy, and business-as-usual. Future land use allocation in 2030 found that the sustainable development scenario showed better performance compared to government policy and business-as-usual scenarios.

Suggested Citation

  • Rahmadya Trias Handayanto & Nitin Kumar Tripathi & Sohee Minsun Kim & Sumanta Guha, 2017. "Achieving a Sustainable Urban Form through Land Use Optimisation: Insights from Bekasi City’s Land-Use Plan (2010–2030)," Sustainability, MDPI, vol. 9(2), pages 1-18, February.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:2:p:221-:d:89482
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    References listed on IDEAS

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    1. Sharafi, Masoud & ELMekkawy, Tarek Y., 2014. "Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach," Renewable Energy, Elsevier, vol. 68(C), pages 67-79.
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