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
Article
Wang, Siqin, Liu, Yan, Feng, Yongjiu and Lei, Zhenkun. 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: Urban Analytics and City Science. 49 (7), pp. 1820-1837. https://doi.org/10.1177/23998083211069382
| Article Title | 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 |
|---|---|
| ERA Journal ID | 20859 |
| Article Category | Article |
| Authors | Wang, Siqin, Liu, Yan, Feng, Yongjiu and Lei, Zhenkun |
| Journal Title | Environment and Planning B: Urban Analytics and City Science |
| Journal Citation | 49 (7), pp. 1820-1837 |
| Number of Pages | 18 |
| Year | Sep 2022 |
| Publisher | SAGE Publications Ltd |
| Place of Publication | United Kingdom |
| ISSN | 2399-8083 |
| 2399-8091 | |
| Digital Object Identifier (DOI) | https://doi.org/10.1177/23998083211069382 |
| Web Address (URL) | https://journals.sagepub.com/doi/10.1177/23998083211069382 |
| 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. |
| Keywords | Low-density land development; cellular automata; generalised simulated annealing algorithm; scenario prediction; peri-urban areas; Australia |
| Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
| Byline Affiliations | University of Queensland |
| Shanghai Ocean University, China | |
| Library Services |
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Liu, Yan and Phinn, Stuart. 2005. "Modelling the driving forces of Sydney's urban development (1971-96) in a cellular environment." Applied Geographic Information Systems (GIS). 1 (3). https://doi.org/10.2104/ag050027This item comprises data from the following sources: Web of Science