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From Macro to Micro—How Much Micro is too Much?

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  • Michael Wegener

Abstract

This paper discusses the usefulness of the trend towards microsimulation in urban transport and land‐use modelling for the planning practice. It starts with a history of urban transport and land‐use models and observes a trend towards increasing conceptual, spatial and temporal resolution stimulated by improved data availability, higher computer speed and better theories about mobility and location of individual behaviour. While recognizing these advances, the paper calls attention to the problems of disaggregate models in terms of data requirements, computing time and stochastic variation and shows that in the light of new challenges cities are facing environmental problems, such as energy scarcity and climate change, not further refinement but more focus on basic needs and constraints is needed to make the models useful for the planning practice. As a possible solution to the macro–micro debate, it calls for a theory of multi‐level models according to which for each planning task there is an appropriate level of conceptual, spatial and temporal resolution. The paper closes with an example of a multi‐level land use, transport and environment model ranging from the European to the grid cell level.

Suggested Citation

  • Michael Wegener, 2011. "From Macro to Micro—How Much Micro is too Much?," Transport Reviews, Taylor & Francis Journals, vol. 31(2), pages 161-177.
    • Handle: RePEc:taf:transr:v:31:y:2011:i:2:p:161-177
    DOI: 10.1080/01441647.2010.532883
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    Cited by:

    1. Frederik Priem & Philip Stessens & Frank Canters, 2020. "Microsimulation of Residential Activity for Alternative Urban Development Scenarios: A Case Study on Brussels and Flemish Brabant," Sustainability, MDPI, vol. 12(6), pages 1-28, March.
    2. McLeod, Sam & Schapper, Jake H.M. & Curtis, Carey & Graham, Giles, 2019. "Conceptualizing freight generation for transport and land use planning: A review and synthesis of the literature," Transport Policy, Elsevier, vol. 74(C), pages 24-34.
    3. Jiri Horak & Jan Tesla & David Fojtik & Vit Vozenilek, 2019. "Modelling Public Transport Accessibility with Monte Carlo Stochastic Simulations: A Case Study of Ostrava," Sustainability, MDPI, vol. 11(24), pages 1-25, December.
    4. Marko Kryvobokov, 2015. "A two-level regional approach to residential location choice model," Letters in Spatial and Resource Sciences, Springer, vol. 8(2), pages 181-196, July.
    5. Vanoutrive, Thomas & Van De Vijver, Elien & Van Malderen, Laurent & Jourquin, Bart & Thomas, Isabelle & Verhetsel, Ann & Witlox, Frank, 2012. "What determines carpooling to workplaces in Belgium: location, organisation, or promotion?," Journal of Transport Geography, Elsevier, vol. 22(C), pages 77-86.
    6. Zimu Jia & Long Chen & Jingjia Chen & Guowei Lyu & Ding Zhou & Ying Long, 2020. "Urban modeling for streets using vector cellular automata: Framework and its application in Beijing," Environment and Planning B, , vol. 47(8), pages 1418-1439, October.
    7. Scarinci, Riccardo & Zanarini, Alessandro & Bierlaire, Michel, 2019. "Electrification of urban mobility: The case of catenary-free buses," Transport Policy, Elsevier, vol. 80(C), pages 39-48.
    8. Wegener, Michael, 2013. "The future of mobility in cities: Challenges for urban modelling," Transport Policy, Elsevier, vol. 29(C), pages 275-282.

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