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Spatially-explicit prediction of low-density peri-urban development: comparison between urban and rural scenarios in the Moreton Bay Region in South East Queensland, Australia

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  • Siqin Wang
  • Yan Liu
  • Yongjiu Feng
  • Zhenkun Lei

Abstract

Mainstream urban modelling literature focuses on urban expansion featured by a relatively fast urbanisation process, but relatively less research is available to understand and model the slow-paced urban and rural land development in the low-density peri-urban context. This study aims to address this knowledge gap by simulating the urban and rural land development in the Moreton Bay Region in South East Queensland (SEQ), Australia using two cellular automata (CA) models that are coupled with a generalised simulated annealing (GSA) algorithm. With the total land available for development estimated using a Markov Chain model, the GSA-CA urban and rural models were developed, respectively, to simulate urban and rural land development from 1991 to 2011, and then to predict their future development to 2041 following vigorous model calibrations. The modelling results illustrate three snapshots of the predicted spatial patterns of urban and rural development in 2021, 2031 and 2041, with moderate growth in both the urban and rural areas over time, but with urban development occurring in a more compact form than rural development. The GSA-CA modelling approach is capable of optimising the CA transition rules and has the potential to be applied to other geographical contexts to support regional planning, decision-making and scenario designation for future land development in cities that have entered the saturation phase of urbanisation.

Suggested Citation

  • Siqin Wang & Yan Liu & Yongjiu Feng & Zhenkun Lei, 2022. "Spatially-explicit prediction of low-density peri-urban development: comparison between urban and rural scenarios in the Moreton Bay Region in South East Queensland, Australia," Environment and Planning B, , vol. 49(7), pages 1820-1837, September.
    • Handle: RePEc:sae:envirb:v:49:y:2022:i:7:p:1820-1837
    DOI: 10.1177/23998083211069382
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