Abstract
This paper advocates a performance-based approach to the planning of temporary housing sites after sudden urban disasters. A “functionally graded” configurational analysis method is used to assess, quantitatively and qualitatively, the socio-spatial impact of government-led housing assistance provision across the regional, urban and neighbourhood scales. To highlight the different outcomes achieved in different urban contexts by apparently similar housing recovery plans, a diachronic comparative study of four epicentral historic towns hit by the 2016–2017 Central Italy earthquakes is performed. The research analyses the configurational properties of these settlements at four critical points in time: before the disaster; right after it (emergency phase); during disaster recovery; after the reconstruction is completed. This paper builds on previous research on rapid urban modelling and economic spatial analysis workflows to respond to potential implementation challenges, which include time constraints and geo-data availability issues after disasters. By using a real case scenario, this study seeks to demonstrate the potential benefits of adopting the proposed multidimensional spatial analysis method to foster the delivery of integrated housing recovery solutions, which contribute to sustainable urban development These encompass informing, timely updating, and coordinating strategic, management, and operational decisions related to the design and planning of temporary housing sites.
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Pezzica, C., Chioni, C., Cutini, V., Bleil de Souza, C. (2020). Assessing the Impact of Temporary Housing Sites on Urban Socio-spatial Performance: The Case of the Central Italy Earthquake. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12251. Springer, Cham. https://doi.org/10.1007/978-3-030-58808-3_24
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