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Geosimulation of urban growth and demographic decline in the Ruhr: a case study for 2025 using the artificial intelligence of cells and agents

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  • Andreas Rienow
  • Dirk Stenger

Abstract

The Ruhr is an “old acquaintance” in the discourse of urban decline in old industrialized cities. The agglomeration has to struggle with archetypical problems of former monofunctional manufacturing cities. Surprisingly, the image of a shrinking city has to be refuted if you shift the focus from socioeconomic wealth to its morphological extension. Thus, it is the objective of this study to meet the challenge of modeling urban sprawl and demographic decline by combining two artificial intelligent solutions: The popular urban cellular automaton SLEUTH simulates urban growth using four simple but effective growth rules. In order to improve its performance, SLEUTH has been modified among others by combining it with a robust probability map based on support vector machines. Additionally, a complex multi-agent system is developed to simulate residential mobility in a shrinking city agglomeration: residential mobility and the housing market of shrinking city systems focuses on the dynamic of interregional housing markets implying the development of potential dwelling areas. The multi-agent system comprises the simulation of population patterns, housing prices, and housing demand in shrinking city agglomerations. Both models are calibrated and validated regarding their localization and quantification performance. Subsequently, the urban landscape configuration and composition of the Ruhr 2025 are simulated. A simple spatial join is used to combine the results serving as valuable inputs for future regional planning in the context of multifarious demographic change and preceding urban growth. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • 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, vol. 16(3), pages 311-342, July.
    • Handle: RePEc:kap:jgeosy:v:16:y:2014:i:3:p:311-342
    DOI: 10.1007/s10109-014-0196-9
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    References listed on IDEAS

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    1. R White & G Engelen, 1993. "Cellular Automata and Fractal Urban Form: A Cellular Modelling Approach to the Evolution of Urban Land-Use Patterns," Environment and Planning A, , vol. 25(8), pages 1175-1199, August.
    2. Helen Briassoulis, 2000. "Analysis of Land Use Change: Theoretical and Modeling Approaches," Wholbk, Regional Research Institute, West Virginia University, number 17, Fall.
    3. Heimpold, Gerhard & Ebert, M., 2012. "5. Konferenz „Analysen und Politik für Ostdeutschland – aus der Forschung des IWH“ – ein Bericht," Wirtschaft im Wandel, Halle Institute for Economic Research (IWH), vol. 18(2), pages 60-67.
    4. Oliver Arentz & Johann Eekhoff & Christine Arentz, 2010. "Zur Finanzmarktkrise: Die Rolle der Immobilienbewertung," IWP Discussion Paper Series 01/2010, Institute for Economic Policy, Cologne, Germany.
    5. repec:rri:bkchap:17 is not listed on IDEAS
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    Cited by:

    1. Luca Salvati & Giuseppe Venanzoni & Pere Serra & Margherita Carlucci, 2016. "Scattered or polycentric? Untangling urban growth in three southern European metropolitan regions through exploratory spatial data analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(1), pages 1-29, July.

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    More about this item

    Keywords

    Urban growth; Demographic shrinkage; SLEUTH; ReHoSh; Residential mobility; Housing market; C60; R14; R21; R23; R31;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • 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
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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