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VisualUVAM: A Decision Support System Addressing the Curse of Dimensionality for the Multi-Scale Assessment of Urban Vulnerability in Spain

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  • Jorge Salas

    (School of Civil Engineering, Universitat Politècnica de València, 46022 Valencia, Spain)

  • Víctor Yepes

    (ICITECH, Universitat Politècnica de València, 46022 Valencia, Spain)

Abstract

Many-objective optimization methods have proven successful in the integration of research attributes demanded for urban vulnerability assessment models. However, these techniques suffer from the curse of the dimensionality problem, producing an excessive burden in the decision-making process by compelling decision-makers to select alternatives among a large number of candidates. In other fields, this problem has been alleviated through cluster analysis, but there is still a lack in the application of such methods for urban vulnerability assessment purposes. This work addresses this gap by a novel combination of visual analytics and cluster analysis, enabling the decision-maker to select the set of indicators best representing urban vulnerability accordingly to three criteria: expert’s preferences, goodness of fit, and robustness. Based on an assessment framework previously developed, VisualUVAM affords an evaluation of urban vulnerability in Spain at regional, provincial, and municipal scales, whose results demonstrate the effect of the governmental structure of a territory over the vulnerability of the assessed entities.

Suggested Citation

  • Jorge Salas & Víctor Yepes, 2019. "VisualUVAM: A Decision Support System Addressing the Curse of Dimensionality for the Multi-Scale Assessment of Urban Vulnerability in Spain," Sustainability, MDPI, vol. 11(8), pages 1-17, April.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:8:p:2191-:d:222134
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    References listed on IDEAS

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    Cited by:

    1. Jorge Salas & Víctor Yepes, 2020. "Enhancing Sustainability and Resilience through Multi-Level Infrastructure Planning," IJERPH, MDPI, vol. 17(3), pages 1-22, February.
    2. Bismark Adu-Gyamfi & Rajib Shaw, 2021. "Utilizing Population Distribution Patterns for Disaster Vulnerability Assessment: Case of Foreign Residents in the Tokyo Metropolitan Area of Japan," IJERPH, MDPI, vol. 18(8), pages 1-17, April.
    3. Yuming Lin & Zhenjiang Shen, 2022. "An Innovative Index for Evaluating Urban Vulnerability on Pandemic Using LambdaMART Algorithm," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    4. Jeisson Prieto & Rafael Malagón & Jonatan Gomez & Elizabeth León, 2021. "Urban Vulnerability Assessment for Pandemic Surveillance—The COVID-19 Case in Bogotá, Colombia," Sustainability, MDPI, vol. 13(6), pages 1-13, March.
    5. Vicent Penadés-Plà & David Martínez-Muñoz & Tatiana García-Segura & Ignacio J. Navarro & Víctor Yepes, 2020. "Environmental and Social Impact Assessment of Optimized Post-Tensioned Concrete Road Bridges," Sustainability, MDPI, vol. 12(10), pages 1-18, May.

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