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Topological analysis of urban street networks

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  • Bin Jiang
  • Christophe Claramunt
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    Abstract

    The authors propose a topological analysis of large urban street networks based on a computational and functional graph representation. This representation gives a functional view in which vertices represent named streets and edges represent street intersections. A range of graph measures, including street connectivity, average path length, and clustering coefficient, are computed for structural analysis. In order to characterise different clustering degrees of streets in a street network they generalise the clustering coefficient to a k -clustering coefficient that takes into account k neighbours. Based on validations applied to three cities, the authors show that large urban street networks form small-world networks but exhibit no scale-free property.

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    Bibliographic Info

    Article provided by Pion Ltd, London in its journal Environment and Planning B: Planning and Design.

    Volume (Year): 31 (2004)
    Issue (Month): 1 (January)
    Pages: 151-162

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    Handle: RePEc:pio:envirb:v:31:y:2004:i:1:p:151-162

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    Web page: http://www.pion.co.uk

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    Cited by:
    1. Marc Barthélemy & Alessandro Flammini, 2009. "Co-evolution of Density and Topology in a Simple Model of City Formation," Networks and Spatial Economics, Springer, vol. 9(3), pages 401-425, September.
    2. Alexander Erath & Michael Löchl & Kay Axhausen, 2009. "Graph-Theoretical Analysis of the Swiss Road and Railway Networks Over Time," Networks and Spatial Economics, Springer, vol. 9(3), pages 379-400, September.
    3. David Levinson, 2011. "Network Structure and City Size," Working Papers 000094, University of Minnesota: Nexus Research Group.
    4. Zengwang Xu & Daniel Sui, 2007. "Small-world characteristics on transportation networks: a perspective from network autocorrelation," Journal of Geographical Systems, Springer, vol. 9(2), pages 189-205, June.
    5. Wu, Jian-Jun & Gao, Zi-You & Sun, Hui-jun, 2008. "Optimal traffic networks topology: A complex networks perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 1025-1032.
    6. Tsekeris, Theodore & Souliotou, Anastasia-Zoi, 2014. "Graph-theoretic evaluation support tool for fixed-route transport development in metropolitan areas," Transport Policy, Elsevier, vol. 32(C), pages 88-95.
    7. Marc Barthélémy & Michele Campagna & Alessandro Chessa & Andrea De Montis & Alessandro Vespignani, 2005. "Emergent topological and dynamical properties of a real inter-municipal commuting network - perspectives for policy-making and planning," ERSA conference papers ersa05p607, European Regional Science Association.
    8. Pavithra Parthasarathi & Hartwig Hochmair & David Levinson, 2009. "The Influence of Network Structure on Travel Distance," Working Papers 000069, University of Minnesota: Nexus Research Group.
    9. Jiang, Bin, 2008. "Flow dimension and capacity for structuring urban street networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(16), pages 4440-4452.
    10. Pavithra Parthasarathi & David Levinson & Hartwig Hochmair, 2012. "Network Structure and Travel Time Perception," Working Papers 000102, University of Minnesota: Nexus Research Group.

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