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The Network Analysis of Urban Streets: A Primal Approach

Author

Listed:
  • Sergio Porta

    (Dipartimento di Progettazione dell'Architettura, Politecnico di Milano, Via Golgi 39, Milano 20133, Italy)

  • Paolo Crucitti

    (Scuola Superiore di Catania, Catania, Italy)

  • Vito Latora

    (Dipartimento di Fisica e Astronomia, Università di Catania and INFN Sezione di Catania, Italy)

Abstract
The network metaphor in the analysis of urban and territorial cases has a long tradition, especially in transportation or land-use planning and economic geography. More recently, urban design has brought its contribution by means of the ‘space syntax’ methodology. All these approaches-though under different terms like ‘accessibility’, ‘proximity’, ‘integration’ ‘connectivity’, ‘cost’, or ‘effort’-focus on the idea that some places (or streets) are more important than others because they are more central . The study of centrality in complex systems, however, originated in other scientific areas, namely in structural sociology, well before its use in urban studies; moreover, as a structural property of the system, centrality has never been extensively investigated metrically in geographic networks as it has been topologically in a wide range of other relational networks such as social, biological, or technological ones. After a previous work on some structural properties of the primal graph representation of urban street networks, in this paper we provide an in-depth investigation of centrality in the primal approach as compared with the dual one. We introduce multiple centrality assessment (MCA), a methodology for geographic network analysis, which is defined and implemented on four 1-square-mile urban street systems. MCA provides a different perspective from space syntax in that: (1) it is based on primal, rather than dual, street graphs; (2) it works within a metric, rather than topological, framework; (3) it investigates a plurality of peer centrality indices rather than a single index. We show that, in the MCA primal approach, much more than in the dual approach, some centrality indices nicely capture the ‘skeleton’ of the urban structure that impacts so much on spatial cognition and collective behaviours. Moreover, the distributions of centrality in self-organized cities are different from those in planned cities.

Suggested Citation

  • Sergio Porta & Paolo Crucitti & Vito Latora, 2006. "The Network Analysis of Urban Streets: A Primal Approach," Environment and Planning B, , vol. 33(5), pages 705-725, October.
    • Handle: RePEc:sae:envirb:v:33:y:2006:i:5:p:705-725
    DOI: 10.1068/b32045
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    References listed on IDEAS

    as
    1. Latora, Vito & Marchiori, Massimo, 2002. "Is the Boston subway a small-world network?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 109-113.
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    Cited by:

    1. 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.
    2. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    3. Boeing, Geoff, 2017. "The Relative Circuity of Walkable and Drivable Urban Street Networks," SocArXiv 4rzqa, 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.
    6. Feng, Huifang & Bai, Fengshan & Xu, Youji, 2019. "Identification of critical roads in urban transportation network based on GPS trajectory data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    7. Han Yue & Xinyan Zhu, 2019. "Exploring the Relationship between Urban Vitality and Street Centrality Based on Social Network Review Data in Wuhan, China," Sustainability, MDPI, vol. 11(16), pages 1-19, August.
    8. Boeing, Geoff, 2019. "The Morphology and Circuity of Walkable and Drivable Street Networks," SocArXiv edj2s, Center for Open Science.
    9. Valerio Cutini & Valerio Di Pinto & Antonio Maria Rinaldi & Francesco Rossini, 2020. "Proximal Cities: Does Walkability Drive Informal Settlements?," Sustainability, MDPI, vol. 12(3), pages 1-20, January.

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