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Sustainability 2017, 9(2), 221; doi:10.3390/su9020221

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

1
Information Management, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
2
Remote Sensing and GIS, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
3
Urban Environmental Management, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
4
Computer Science, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
*
Author to whom correspondence should be addressed.
Academic Editors: Karsten Grunewald and Olaf Bastian
Received: 2 December 2016 / Revised: 1 February 2017 / Accepted: 3 February 2017 / Published: 6 February 2017
(This article belongs to the Special Issue Maintaining Ecosystem Services to Support Urban Needs)
View Full-Text   |   Download PDF [3369 KB, uploaded 6 February 2017]   |  

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. View Full-Text
Keywords: compact city; eco city; land use zoning; land use optimisation; hybrid optimisation; multi-criteria analysis; evolutionary algorithm compact city; eco city; land use zoning; land use optimisation; hybrid optimisation; multi-criteria analysis; evolutionary algorithm
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Handayanto, R.T.; Tripathi, N.K.; Kim, S.M.; Guha, S. Achieving a Sustainable Urban Form through Land Use Optimisation: Insights from Bekasi City’s Land-Use Plan (2010–2030). Sustainability 2017, 9, 221.

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