A complex network approach to urban growth
AbstractThe economic geography can be viewed as a large and growing network of interacting activities. This fundamental network structure and the large size of such systems makes complex networks an attractive model for its analysis. In this paper we propose the use of complex networks for geographical modeling and demonstrate how such an application can be combined with a cellular model to produce output that is consistent with large scale regularities such as power laws and fractality. Complex networks can provide a stringent framework for growth dynamic modeling where concepts from e.g. spatial interaction models and multiplicative growth models can be combined with the flexible representation of land and behavior found in cellular automata and agent-based models. In addition, there exists a large body of theory for the analysis of complex networks that have direct applications for urban geographic problems. The intended use of such models is twofold: i) to address the problem of how the empirically observed hierarchical structure of settlements can be explained as a stationary property of a stochastic evolutionary process rather than as equilibrium points in a dynamics, and, ii) to improve the prediction quality of applied urban modeling.
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Bibliographic InfoPaper provided by Utrecht University, Section of Economic Geography in its series Papers in Evolutionary Economic Geography (PEEG) with number 0505.
Length: 26 pages
Date of creation: Feb 2005
Date of revision: Feb 2005
evolutionary economics; complex networks; urban growth;
Other versions of this item:
- NEP-ALL-2006-01-01 (All new papers)
- NEP-GEO-2006-01-01 (Economic Geography)
- NEP-KNM-2006-01-01 (Knowledge Management & Knowledge Economy)
- NEP-NET-2006-01-01 (Network Economics)
- NEP-SOC-2006-01-01 (Social Norms & Social Capital)
- NEP-URE-2006-01-01 (Urban & Real Estate Economics)
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