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A Model to Mitigate the Peripheralization Risk at Urban Scale

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Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

Abstract

The uncontrolled expansion of built-up areas and of multiple forms of poverty, on a global level, determines a new geography of degradation, extended both to suburbs and to central zones, thus exposing cities, in their entirety, at risk of peripheralization. In this framework, counteracting actions at the urban scale, such as regeneration programmes, need to be targeted primarily at areas of significant risk, occurring with a combination of vulnerability factors, in three dimensions: social, building and urban. Furthermore, in order to be effective, such programmes must be geared to maximizing risk mitigation. This is possible when the planning of interventions takes into account the evaluation results of the better design alternative in order to reduce pre-existing vulnerability. Such an approach constitutes the novelty of the study. So, the aim of the work is to provide an innovative model for the mitigation of peripheralization risk at urban scale. For this purpose, the contribution defines a set of mitigation indicators and a protocol for evaluating the most effective design alternative based on the Analytic Hierarchy Process (AHP).

G. Roberto and N. Antonio designed the research. All authors contributed to the definition of the methodology. M. Alessandra prepared a draft manuscript. G. Roberto and N. Antonio enriched and revised the manuscript.

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Notes

  1. 1.

    In chronological order (with date of first appearance): Urban Pilot Projects (1989–1993); Community Initiatives POVERTY III (1989–1993); URBAN I (1994–1999); URBAN II (2000–2006); URBACT II (2007–2013); URBACT III (2014–2020).

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Roberto, G., Antonio, N., Alessandra, M., Maria, C. (2020). A Model to Mitigate the Peripheralization Risk at Urban Scale. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12250. Springer, Cham. https://doi.org/10.1007/978-3-030-58802-1_66

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  • DOI: https://doi.org/10.1007/978-3-030-58802-1_66

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