Scenario Planning for Cities using Cellular Automata Models: A Case Study
AbstractWe show how small to medium sized cities can make use of the cellular automata (CA) approach to integrate land use data and other GIS based data with inter-active scenario evaluation. In our model development we put particular focus on the interdependency between transport infrastructure supply and population density. Due to their close connection with the field of Geography most CA models concentrate on land use changes only. How the CA model can be used in practice by city planners is generally not discussed. Also, population changes in cells and the associated pressures on infrastructure networks are generally not included. In this paper we first build and use a CA model to illustrate land use change. We then apply OLS regression as well as linear optimization techniques to allocate population growth into cells in a way that observes the stylized facts established by the standard Urban Economics literature (population growth in a particular cell is dependent on its distance to the city centre as well as its quality with respect to public transport ease). Third we show applications that illustrate how a CA model can be used for scenario planning in cities. Our CA model can be used to generate maps of future land use patterns for different potential future scenarios. It provides a fast and very economical way to compare alternative strategic plans and development rules for a small to medium sized city. For our sample town, Austria’s second largest city Graz, we develop five different long-term scenarios. The model output for each scenario can then be used as input for infrastructure planning procedures. We illustrate some examples: ex-ante transport infrastructure evaluation, graphic representation of the spatially differentiated structure of the population, evaluation of existing zoning rules, evaluation of infrastructure capacities (e.g. sewage system).
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Bibliographic InfoPaper provided by University of Graz, Department of Economics in its series Graz Economics Papers with number 2013-06.
Date of creation: Jun 2013
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