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Modelling sustainable urban growth in a rapidly urbanising region using a fuzzy-constrained cellular automata approach
Authors:Yan Liu
Institution:1. Centre for Spatial Environmental Research and School of Geography, Planning and Environmental Management, The University of Queensland , Australia yan.liu@uq.edu.au
Abstract:This article presents an application of a fuzzy-constrained cellular automata model to simulate the spatio-temporal processes of urban growth in the rapidly growing Gold Coast City in Southeast Queensland, Australia. Urban growth has been captured in the model as a continuous process in space and over time, which has been affected by a set of primary and secondary transition rules. The primary transition rules deal with the propensity of a local area for development and the impact of its neighbouring cells on such development, while the secondary transition rules reflect the influences of environmental and institutional factors on urban growth. Application of the model demonstrates its re-applicability to different regions and the effectiveness of the cellular automata technique in studying urban dynamics. It also provides tools to explore sustainable urban growth options under different socio-environmental and planning control factors. A sustainable urban future of the region is achievable if development is managed to maintain a balance amongst ecological conservation, economic growth and the contemporary Australian lifestyle.
Keywords:sustainable urban growth  cellular automata  fuzzy set  fuzzy logic-constrained rule  Gold Coast City
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