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Disaggregate models with aggregate data: Two UrbanSim applications

Listed author(s):
  • Patterson, Zachary


    (Concordia University, Montréal, Canada)

  • Kryvobokov, Marko

    (Lab of Transport Economics (LET), CNRS, Lyon; France)

  • Marchal, Fabrice

    (Lab of Transport Economics (LET), CNRS, Lyon; France)

  • Bierlaire, Michel

    (Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne; Switzerland)

Registered author(s):

    UrbanSim has significant data requirements. In particular, it requires disaggregate data (traditionally at the 150 meter by 150 meter gridcell level) for employment, households, and buildings. While such data are not always easily available, most regions have readily available data in a more aggregate form, often at the level of traffic analysis zone (TAZ) or other municipal divisions. This paper describes two UrbanSim applications for the cities of Brussels, Belgium and Lyon, France that adopted different approaches of using aggregate data. In Brussels, aggregate zonal data were disaggregated to the gridcell level. In the Lyon application, the zone was used as the unit of analysis and as such, each zone corresponds to one gridcell. The objectives of this paper are: 1) establish whether an UrbanSim model can be developed using aggregate data; 2) describe two different approaches to using aggregate data with UrbanSim and evaluate; and 3) evaluate the advantages and disadvantages of using aggregate data, as well as the two different approaches described. In doing so, it advances knowledge in the field of transportation and land use modeling by helping modelers evaluate the use of an increasingly popular integrated transportation land use modeling option. Several conclusions flow from this work. First, aggregate data can be used to develop UrbanSim models. Second, only a limited amount of disaggregate information can be drawn from aggregate data. In the context of UrbanSim, this is manifested in models with relatively few variables and dubious simulation results—in other words, while it is possible to develop an UrbanSim application with aggregate data, it should not be used for applied analysis. Finally, the development of such models can be a relatively low-cost exercise to gain familiarity with UrbanSim’s functioning and data requirements. As a result, it can also be seen as an important first step to developing or evaluating UrbanSim for application in a new region.

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    Article provided by Center for Transportation Studies, University of Minnesota in its journal The Journal of Tranport and Land Use.

    Volume (Year): 3 (2010)
    Issue (Month): 2 ()
    Pages: 5-37

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    Handle: RePEc:ris:jtralu:0029
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    1. Paul Waddell, 2000. "A behavioral simulation model for metropolitan policy analysis and planning: residential location and housing market components of UrbanSim," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 27(2), pages 247-263, March.
    2. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    3. H Couclelis, 1985. "Cellular Worlds: A Framework for Modeling Micro—Macro Dynamics," Environment and Planning A, , vol. 17(5), pages 585-596, May.
    4. H Couclelis, 1985. "Cellular worlds: a framework for modeling micro - macro dynamics," Environment and Planning A, Pion Ltd, London, vol. 17(5), pages 585-596, May.
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