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Urban Street Networks, a Comparative Analysis of Ten European Cities

Author

Listed:
  • Emanuele Strano

    (Laboratory of Geographic Information Systems, School of Architecture, Civil and Environmental Engineering, Ecole Polytechique Fédérale de Lausanne (EPFL), and Urban Design Studies Unit, Department of Architecture, University of Strathclyde, Glasgow, Scotland)

  • Matheus Viana
  • Luciano da Fontoura Costa
  • Alessio Cardillo

    (Departamento de Física de Materia Condensada, Universidad de Zaragoza, E-50009 Zaragoza, Spain, and Institute for Biocomputation and Physics of Complex Systems, Universidad de Zaragoza, E-50018 Zaragoza, Spain, and Dipartimento di Fisica e Astronomia, Università de Catania and INFN, Via S Sofia, 64, 95123 Catania, Italy)

  • Sergio Porta

    (Urban Design Studies Unit, Department of Architecture, University of Strathclyde, Glasgow, Scotland)

  • Vito Latora

    (School of Mathematical Sciences, Queen Mary, University of London, London, England, and Dipartimento di Fisica e Astronomia, Università di Catania and INFN, Via S Sofia, 64, 95123 Catania, Italy, and Laboratorio sui Sistemi Complessi, Scuola Superiore de Catania, Via San Nullo 5/I, 95123 Catania, Italy)

Abstract

We compare the structural properties of the street networks of ten different European cities using their primal representation. We investigate the properties of the geometry of the networks and a set of centrality measures highlighting differences and similarities between cases. In particular, we found that cities share structural similarities due to their quasiplanarity but that there are also several distinctive geometrical properties. A principal component analysis is performed on the distributions of centralities and their respective moments, which is used to find distinctive characteristics by which we can classify cities into families. We believe that, beyond the improvement of the empirical knowledge on streets' network properties, our findings can open new perspectives into the scientific relationship between city planning and complex networks, stimulating the debate on the effectiveness of the set of knowledge that statistical physics can contribute for city planning and urban-morphology studies.

Suggested Citation

  • Emanuele Strano & Matheus Viana & Luciano da Fontoura Costa & Alessio Cardillo & Sergio Porta & Vito Latora, 2013. "Urban Street Networks, a Comparative Analysis of Ten European Cities," Environment and Planning B, , vol. 40(6), pages 1071-1086, December.
    • Handle: RePEc:sae:envirb:v:40:y:2013:i:6:p:1071-1086
    DOI: 10.1068/b38216
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    References listed on IDEAS

    as
    1. Jiang, Bin, 2007. "A topological pattern of urban street networks: Universality and peculiarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 647-655.
    2. Carlo Ratti & Stanislav Sobolevsky & Francesco Calabrese & Clio Andris & Jonathan Reades & Mauro Martino & Rob Claxton & Steven H Strogatz, 2010. "Redrawing the Map of Great Britain from a Network of Human Interactions," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-6, December.
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    Cited by:

    1. Geoff Boeing, 2020. "Planarity and street network representation in urban form analysis," Environment and Planning B, , vol. 47(5), pages 855-869, June.
    2. Boeing, Geoff, 2019. "Street Network Models and Measures for Every U.S. City, County, Urbanized Area, Census Tract, and Zillow-Defined Neighborhood," SocArXiv 7fxjz, Center for Open Science.
    3. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    4. Shiguang Wang & Dexin Yu & Mei-Po Kwan & Huxing Zhou & Yongxing Li & Hongzhi Miao, 2019. "The Evolution and Growth Patterns of the Road Network in a Medium-Sized Developing City: A Historical Investigation of Changchun, China, from 1912 to 2017," Sustainability, MDPI, vol. 11(19), pages 1-25, September.
    5. Baorui Han & Dazhi Sun & Xiaomei Yu & Wanlu Song & Lisha Ding, 2020. "Classification of Urban Street Networks Based on Tree-Like Network Features," Sustainability, MDPI, vol. 12(2), pages 1-13, January.

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