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

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.

A survey form for the characterization of the historical built environment prone to multi-risks

“…It defines the potential levels of crowding over time, vehicular and pedestrian accessibility, and the type of user [16]. The fifth section focused on the characteristics of the considered OSs' context [12]. These factors are related to the peculiarity of the site, reporting the SLODs hazard level (e.g., climate and environmental factors), and the evaluation of probable SUODs and multi-hazard potential.…”

“…Although the development of analysis tools for BE and its risks is generally divided to date, previous studies have shown how a multi-risk approach allowed for the development of a set of mitigation strategies. These particularly concern the criticalities determined by the coexistence and mutual interaction of risks, conditions that could otherwise compromise the effectiveness of the adopted measures [12].…”

“…Finally, section 5 highlighted the types and levels of danger associated with each space; the median in the number of identifiable dangers was 6, with a minimum for al context to the BEs characteristics. This specific step was already achieved within the BE S 2 ECURE project and published in D'Amico et al [12]. Moreover, the data collection methods could be implemented with further specialist analyses to better represent the BE and their specific risks, as well as to support the risk communication to users of the BE (technical and not technical) through disruptive technologies [25].…”

“…The specific morpho-typological characteristics and the urban layout, both players in the genesis and evolution of urban fabrics, substantially influence the system's ability to ensure the desired level of safety through strategic functions and services during all the phases of the catastrophic event. In this sense, OSs, defined as linear spaces (LS; e.g., streets) and areal spaces (AS; e.g., squares), play a fundamental role in the emergency management phase [12]: the roads allow the connection between the various elements of the BE, guaranteeing the evacuation process and the rescue operations, while the squares act as "safe" outdoor waiting areas for users affected by the sudden event. The value of these elements largely depends on the specific risk, the critical issues related to the functions they contain, and the use of such spaces made by users (e.g., becoming catalysts of attendance) [3].…”

“…An average planimetric extension of 3.731 m 2 was observed, with a minimum for San Gemini (1.240 m 2 ) and a maximum for Trani (12.000 m 2 ).Section 2 showed a median value for the structural aggregates present in the squares analyzed equal to 6, with a maximum for Ostuni (9) and a minimum for San Gemini (3). The accesses were analyzed considering the different transport modes permitted (pedestrian, vehicular, and controlled access), and their global count resulted in a median of 7 accesses per square, with a minimum for San Gemini (4) and a maximum for Matera(12). Regarding special buildings, a median of 3 is observed,…”