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Space – time patterns of urban sprawl, a 1D cellular automata and microeconomic approach

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Listed:
  • Geoffrey Caruso
  • Dominique Peeters
  • Jean Cavailhès
  • Mark Rounsevell

Abstract

We present a theoretical model of residential growth that emphasises the path-dependent nature of urban sprawl patterns. The model is founded on the monocentric urban economic model and uses a cellular automata (CA) approach to introduce endogenous neighbourhood effects. Households are assumed both to like and to dislike the density of their neighbourhood, and are assumed to trade-off this density with housing space consumption and commuting costs. Discontinuous spatial patterns emerge from that trade-off, with the size of suburban clusters varying with time and distance to the centre. We use space – time diagrams inspired from 1D elementary CA to visualise changes in spatial patterns through time and space, and undertake sensitivity analyses to show how the pattern and timing of sprawl are affected by neighbourhood preferences, income level, commuting costs, or by imposing a green belt.

Suggested Citation

  • Geoffrey Caruso & Dominique Peeters & Jean Cavailhès & Mark Rounsevell, 2009. "Space – time patterns of urban sprawl, a 1D cellular automata and microeconomic approach," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 36(6), pages 968-988, November.
  • Handle: RePEc:pio:envirb:v:36:y:2009:i:6:p:968-988
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    Cited by:

    1. Akamatsu, Takashi & Fujishima, Shota & Takayama, Yuki, 2014. "On Stable Equilibria in Discrete-Space Social Interaction Models," MPRA Paper 55938, University Library of Munich, Germany.
    2. Akamatsu, Takashi & Fujishima, Shota & Takayama, Yuki, 2017. "Discrete-space agglomeration model with social interactions: Multiplicity, stability, and continuous limit of equilibria," Journal of Mathematical Economics, Elsevier, vol. 69(C), pages 22-37.

    More about this item

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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