Built Environment Typologies Prone to Risk: A Cluster Analysis of Open Spaces in Italian Cities

Alessandro D’Amico, Martina Russo, Marco Angelosanti, Gabriele Bernardini, Donatella Vicari, Enrico Quagliarini and Edoardo Currà
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Alessandro D’Amico: Department of Civil, Building and Environmental Engineering, Sapienza Università di Roma, 00184 Rome, Italy
Martina Russo: Department of Civil, Building and Environmental Engineering, Sapienza Università di Roma, 00184 Rome, Italy
Marco Angelosanti: Department of Civil, Building and Environmental Engineering, Sapienza Università di Roma, 00184 Rome, Italy
Gabriele Bernardini: Department of Construction, Civil Engineering and Architecture (DICEA), Università Politecnica delle Marche, 60121 Ancona, Italy
Donatella Vicari: Department of Statistical Sciences, Sapienza University of Rome, 00185 Rome, Italy
Enrico Quagliarini: Department of Construction, Civil Engineering and Architecture (DICEA), Università Politecnica delle Marche, 60121 Ancona, Italy
Edoardo Currà: Department of Civil, Building and Environmental Engineering, Sapienza Università di Roma, 00184 Rome, Italy

Sustainability, 2021, vol. 13, issue 16, 1-32

Abstract: Planning for preparedness, in terms of multi-hazard disasters, involves testing the relevant abilities to mitigate damage and build resilience, through the assessment of deterministic disaster scenarios. Among risk-prone assets, open spaces (OSs) play a significant role in the characterization of the built environment (BE) and represent the relevant urban portion on which to develop multi-risk scenarios. The aim of this paper is to elaborate ideal scenarios—namely, Built Environment Typologies (BETs)—for simulation-based risk assessment actions, considering the safety and resilience of BEs in emergency conditions. The investigation is conducted through the GIS data collection of the common characteristics of OSs (i.e., squares), identified through five parameters considered significant in the scientific literature. These data were processed through a non-hierarchical cluster analysis. The results of the cluster analysis identified five groups of OSs, characterized by specific morphological, functional, and physical characteristics. Combining the outcomes of the cluster analysis with a critical analysis, nine final BETs were identified. The resulting BETs were linked to characteristic risk combinations, according to the analysed parameters. Thus, the multi-risk scenarios identified through the statistical analysis lay the basis for future risk assessments of BEs, based on the peculiar characteristics of Italian towns.

Keywords: built environment; multi-risk; GIS; cluster analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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