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Cellular automata and fractal urban form: a cellular modelling approach to the evolution of urban land-use patterns

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  • R White
  • G Engelen
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    Abstract

    Cellular automata belong to a family of discrete, connectionist techniques being used to investigate fundamental principles of dynamics, evolution, and self-organization. In this paper, a cellular automaton is developed to model the spatial structure of urban land use over time. For realistic parameter values, the model produces fractal or bifractal land-use structures for the urbanized area and for each individual land-use type. Data for a set of US cities show that they have very similar fractal dimensions. The cellular approach makes it possible to achieve a high level of spatial detail and realism and to link the results directly to general theories of structural evolution.

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    Bibliographic Info

    Article provided by Pion Ltd, London in its journal Environment and Planning A.

    Volume (Year): 25 (1993)
    Issue (Month): 8 (August)
    Pages: 1175-1199

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    Handle: RePEc:pio:envira:v:25:y:1993:i:8:p:1175-1199

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    Web page: http://www.pion.co.uk

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    Cited by:
    1. Geoffrey Caruso & Dominique Peeters & Jean Cavailhes & Mark Rounsevell, 2007. "Spatial configuration in a periurban city. A cellular automata-based microeconomic model," Working Papers 25364, Institut National de la Recherche Agronomique, France.
    2. Maria Plotnikova & Chokri Dridi, 2010. "A Cellular Automata Simulation of the 1990s Russian Housing Privatization Decision," Economics & Management Discussion Papers, Henley Business School, Reading University em-dp2010-05, Henley Business School, Reading University.
    3. Jose I. Barredo & Carlo Lavalle & Valentina Sagris & Guy Engelen, 2005. "Representing future urban and regional scenarios for flood hazard mitigation," ERSA conference papers ersa05p147, European Regional Science Association.
    4. Andreas Rienow & Dirk Stenger, 2014. "Geosimulation of urban growth and demographic decline in the Ruhr: a case study for 2025 using the artificial intelligence of cells and agents," Journal of Geographical Systems, Springer, Springer, vol. 16(3), pages 311-342, July.
    5. THOMAS, Isabelle & FRANKHAUSER, Pierre & BADARUITTI, Dominique, . "Comparing the fractality of European urban neighbourhoods: do national contexts matter?," CORE Discussion Papers RP -2402, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Caroline Bayr & Miriam Steurer & Rose-Gerd Koboltschnig, 2013. "Scenario Planning for Cities using Cellular Automata Models: A Case Study," Graz Economics Papers 2013-06, University of Graz, Department of Economics.
    7. Yan Liu & Yongjiu Feng & Robert Gilmore Pontius, 2014. "Spatially-Explicit Simulation of Urban Growth through Self-Adaptive Genetic Algorithm and Cellular Automata Modelling," Land, MDPI, Open Access Journal, vol. 3(3), pages 719-738, July.
    8. Nicolas Dendoncker & Mark Rounsevell & Patrick Bogaert, 2005. "Empirically Derived Suitability Maps to Downscale Aggregated Land Use Data," ERSA conference papers ersa05p59, European Regional Science Association.
    9. Alejandro Diaz Bautista & Mauro Diaz Dominguez, 2004. "Capital Humano y Crecimiento Económico en México (1970-2000). Human Capital and Economic Growth in Mexico," Urban/Regional, EconWPA 0405008, EconWPA.

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