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Modeling Cities and Regions as Complex Systems: From Theory to Planning Applications

© VITO. Milestones in scientific modeling of urban dynamics in book by Canadian and VITO experts

Long before cities got overcrowded and landscapes were threatened to disappear, scientists looked for the best way to understand the development of changes in land use, integrating all connected parameters. Accurate predictor models are essential as decision support systems for policy makers. Hence, twenty years ago, Roger White (Honorary Research Professor at the Department of Geography, Memorial University of Newfoundland Canada), Guy Engelen and Inge Uljee (researchers at VITO’s Environmental Modeling Unit) established the field of cellular automata (CA) modeling of urban dynamics. White, Engelen and Uljee recently have published their work in a ground-breaking book on urban and regional modeling: “Modeling Cities and Regions as Complex Systems: From Theory to Planning Applications”, MIT Press, Cambridge, MA 02142, USA, 332p.

In this book they demonstrate their deep understanding of the recent developments of land use change and integrated models, as well as spatial decision support systems. The book introduces in a stepwise manner one of the most advanced land use models, discusses the dynamics of populations and economic activities, describes the integration with models in other domains such as economics, demography and transportation, and presents their use in practical planning and policy applications, many of which have been developed at VITO. The result is an abundant and realistic representation of the spatial dynamics of a variety of urban phenomena. The book is unique in its coverage of both the general issues associated with complex self-organizing systems and the specifics of designing and implementing models of such systems.

Essential reading for urbanists as well as planners and policy makers alike who are tackling the problems of urban growth and scenario analysis.

More info on the book

This book describes the theory and practice of modeling the spatial dynamics of urban growth and transformation. As cities are complex, adaptive, self-organizing systems, the most appropriate modeling framework is one based on the theory of self-organizing systems — an approach already used in such fields as physics and ecology. The book presents a series of models, most of them developed using cellular automata, which are inherently spatial and computationally efficient. Case studies illustrate the use of these models for real-life urban and regional planning problems. Finally, the book presents a new, dynamic theory of urban spatial structure that emerges from the models and their applications.