Modelling land-use effects of future urbanization using cellular automata: An Eastern Danish case

Authors:
Morten Fuglsang;Bernd Münier;Henning Sten Hansen
Affiliations:
Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark and Aalborg University Copenhagen, A.C. Meyers Vænge 15, 2450 Copenhagen, Denmark;Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark;Aalborg University Copenhagen, A.C. Meyers Vænge 15, 2450 Copenhagen, Denmark
Venue:
Environmental Modelling & Software
Year:
2013

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Abstract

The modelling of land use change is a way to analyse future scenarios by modelling different pathways. Application of spatial data of different scales coupled with socio-economic data makes it possible to explore and test the understanding of land use change relations. In the EU-FP7 research project PASHMINA (Paradigm Shift modelling and innovative approaches), three storylines of future transportation paradigm shifts towards 2040 are created. These storylines are translated into spatial planning strategies and modelled using the cellular automata model LUCIA. For the modelling, an Eastern Danish case area was selected, comprising of the Copenhagen metropolitan area and its hinterland. The different scenarios are described using a range of different descriptive GIS datasets. These include mapping of accessibility based on public and private transportation, urban density and structure, and distribution of jobs and population. These indicators are then incorporated in the model calculations as factors determining urban development, related to the scenario outlines. The results calculated from the scenarios reveals the great difference in urban distribution that different spatial planning strategies can produce, changing the shape of the urban landscape. The scenarios visualized showed to outline different planning strategies that could be implemented, creating a more homogenous urban structure targeted at a reduction of transportation work and thus energy consumption. This will lead to less impact on climate from transportation based on a more optimal localization and transport infrastructure strategy.