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The Axial Analysis for Defining Neighborhoods’ Crime Vulnerability. A Methodological Proposal

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Computational Science and Its Applications – ICCSA 2021 (ICCSA 2021)

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Abstract

One major requirement for well-functioning cities, and for their sustainability, is that they have secure streets and public spaces, as also confirmed by the SDG 11. The work presented here deepens an ongoing research that addresses the issue of urban security in terms of risk. The study is carried out at the neighborhood scale aimed at examining the urban space accessibility and its role in the creation of security conditions. The model uses the Space Syntax Analysis, the TOPSIS method and zonal statistic, for the construction of a ranking and comparison between neighborhoods. The composite security index constructed (Isa) allows the identification of the critical conditions in the area examined, identifying neighborhoods that, with respect to optimal accessibility conditions, understood in terms of urban security, are configured as better or worse. The application of the model to the Milan case study has highlighted how within the same territorial context individual neighborhoods can have different responses to the urban crime problem by virtue of their accessibility conditions, delineating possible further research developments.

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Notes

  1. 1.

    For further information please consult the PGT-Milano 2030, available at the link: https://www.pgt.comune.milano.it/ (accessed 21/04/2021).

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Authors and Affiliations

  1. DICIV– Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084, Fisciano, SA, Italy

    Francesca Coppola & Isidoro Fasolino

Authors
  1. Francesca Coppola
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  2. Isidoro Fasolino
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Corresponding author

Correspondence to Francesca Coppola .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Monash University, Clayton, VIC, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

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Coppola, F., Fasolino, I. (2021). The Axial Analysis for Defining Neighborhoods’ Crime Vulnerability. A Methodological Proposal. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12958. Springer, Cham. https://doi.org/10.1007/978-3-030-87016-4_34

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  • DOI: https://doi.org/10.1007/978-3-030-87016-4_34

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