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Cellular Automata in Urban Spatial Modelling

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Agent-Based Models of Geographical Systems

Abstract

Cities and urban dynamics are today understood as self-organized complex systems. While the understanding of cities has changed, also the paradigm in modeling their dynamics has changed from a top-down to a bottom-up approach. Cellular automata models provide an excellent framework for urban spatial modeling of complex dynamics and the accumulation of local actions. The first part of this chapter describes the basic concepts of cellular automata. The second part discusses the definition of complexity and the complex features of cellular automata. The history and principles of urban cellular automata models are introduced in the third part.

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Authors and Affiliations

  1. School of Architecture, Tampere University of Technology, Tampere, Finland

    Sanna Iltanen

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  1. Sanna Iltanen
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Correspondence to Sanna Iltanen .

Editor information

Editors and Affiliations

  1. School of Geography, University of Leeds, Woodhouse Lane, Leeds, LS2 9JT, United Kingdom

    Alison J. Heppenstall

  2. , Department of Computational Social Scien, George Mason University, University Drive 4400, Fairfax, 22030, Virginia, USA

    Andrew T. Crooks

  3. International Institute of Applied Syste, Schlossplatz 1, Laxenburg, 2361, Austria

    Linda M. See

  4. Ctr. Advanced Spatial Analysis, University College London, Torrington Place 1-19, London, WC1E 6BT, United Kingdom

    Michael Batty

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Iltanen, S. (2012). Cellular Automata in Urban Spatial Modelling. In: Heppenstall, A., Crooks, A., See, L., Batty, M. (eds) Agent-Based Models of Geographical Systems. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8927-4_4

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