Modelling urban change with cellular automata: Contemporary issues and future research directions
Article
Article Title | Modelling urban change with cellular automata: Contemporary issues and future research directions |
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ERA Journal ID | 5974 |
Article Category | Article |
Authors | Liu, Yan, Batty, Michael, Wang, Siqin and Corcoran, Jonathan |
Journal Title | Progress in Human Geography: an international review of geographical work in the social sciences and humanities |
Journal Citation | 45 (1), pp. 3-24 |
Number of Pages | 22 |
Year | 2021 |
Place of Publication | United Kingdom |
ISSN | 0309-1325 |
1477-0288 | |
Digital Object Identifier (DOI) | https://doi.org/10.1177/0309132519895305 |
Web Address (URL) | https://journals.sagepub.com/doi/full/10.1177/0309132519895305 |
Abstract | The study of land use change in urban and regional systems has been dramatically transformed in the last four decades by the emergence and application of cellular automata (CA) models. CA models simulate urban land use changes which evolve from the bottom-up. Despite notable achievements in this field, there remain significant gaps between urban processes simulated in CA models and the actual dynamics of evolving urban systems. This article identifies contemporary issues faced in developing urban CA models and draws on this evidence to map out four interrelated thematic areas that require concerted attention by the wider CA urban modelling community. These are: (1) to build models that comprehensively capture the multi-dimensional processes of urban change, including urban regeneration, densification and gentrification, in-fill development, as well as urban shrinkage and vertical urban growth; (2) to establish models that incorporate individual human decision behaviours into the CA analytic framework; (3) to draw on emergent sources of ‘big data’ to calibrate and validate urban CA models and to capture the role of human actors and their impact on urban change dynamics; and (4) to strengthen theory-based CA models that comprehensively explain urban change mechanisms and dynamics. We conclude by advocating cellular automata that embed agent-based models and big data input as the most promising analytical framework through which we can enhance our understanding and planning of the contemporary urban change dynamics. |
Keywords | agent-based modelling (ABM); big data; cellular automata (CA); future research directions; human behaviours; multi-dimensional urban change processes |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of Queensland |
University College London, United Kingdom | |
Library Services |
https://research.usq.edu.au/item/w8z31/modelling-urban-change-with-cellular-automata-contemporary-issues-and-future-research-directions
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