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Robustness and closeness centrality for self-organized and planned cities

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  • A. Paolo Masucci

    (Centre for Advanced Spatial Analysis, University College of London)

  • Carlos Molinero

    (Centre for Advanced Spatial Analysis, University College of London)

Abstract

Street networks are important infrastructural transportation systems that cover a great part of the planet. It is now widely accepted that transportation properties of street networks are better understood in the interplay between the street network itself and the so-called information or dual network, which embeds the topology of the street network’s navigation system. In this work, we present a novel robustness analysis, based on the interaction between the primal and the dual transportation layer for two large metropolises, London and Chicago, thus considering the structural differences to intentional attacks for self-organized and planned cities. We elaborate the results through an accurate closeness centrality analysis in the Euclidean space and in the relationship between primal and dual space. Interestingly enough, we find that even if the considered planar graphs display very distinct properties, the information space induce them to converge toward systems which are similar in terms of transportation properties.

Suggested Citation

  • A. Paolo Masucci & Carlos Molinero, 2016. "Robustness and closeness centrality for self-organized and planned cities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(2), pages 1-8, February.
  • Handle: RePEc:spr:eurphb:v:89:y:2016:i:2:d:10.1140_epjb_e2016-60431-2
    DOI: 10.1140/epjb/e2016-60431-2
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    References listed on IDEAS

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    1. Dorogovtsev, S. N. & Mendes, J.F.F., 2013. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780199686711.
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    Cited by:

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    2. Aybike Ulusan & Ozlem Ergun, 2018. "Restoration of services in disrupted infrastructure systems: A network science approach," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-28, February.
    3. Le Zhang & Xiaoxiao Xu & Yanlong Guo, 2022. "Comprehensive Evaluation of the Implementation Effect of Commercial Street Quality Improvement Based on AHP-Entropy Weight Method—Taking Hefei Shuanggang Old Street as an Example," Land, MDPI, vol. 11(11), pages 1-19, November.
    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. Perlada, Camille D. & Orden, Alfiero K. & Cirunay, Michelle T. & Batac, Rene C., 2021. "Quantifying the organization of urban elements through the statistical distributions of their spatial spreading metrics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 568(C).
    6. Brinkley, Catherine & Raj, Subhashni, 2022. "Perfusion and urban thickness: The shape of cities," Land Use Policy, Elsevier, vol. 115(C).

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