Abstract

The objective of this paper is to present the development of quantitative, spatially explicit, and alternative scenarios of future urban land use in Europe. The scenario-construction methodology is based on three steps: (1) an interpretation of four global-scale storylines describing in qualitative terms alternative urban-development pathways, (2) the development and application of a simple statistical model to estimate the future demand for urban land, and (3) the development of rules to allocate this urban demand geographically through the consideration of land-use planning goals. The qualitative part of the analysis is based on an interpretation of the four storylines of the Special Report on Emission Scenarios by the Intergovernmental Panel on Climate Change. This interpretation describes the principal driving forces that are specific to the European region and to the urban sector on the basis of the theoretical principles of urban economy. The urban-demand model includes two driving forces: (a) the population, representing demographic trends and the demand for housing; and (b) the gross domestic product, reflecting the economic level and dynamism. A further three variables are used as drivers of spatial patterns: (c) accessibility to the transport network; (d) the degree of restriction arising from land-use planning policy, and (e) the relative attractiveness (in terms of residential-location choice) of small, medium, and large cities. Thus, the urban-land-use change model is based on a multilevel analysis, which integrates theory and empirical evidence. The results are original urban-land-use maps of Europe for each of the four scenarios on the basis of a 10′ (latitude and longitude) geographic grid. The comparison of these alternative views of the future and the transparency of the development of these views provide a rich and consistent method for understanding the relationships between driving forces, their intensity, and their consequence for geographic space. Scenario analysis is a useful tool to test incentives, measures, or planning regulations according to different policy objectives.

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