# Measuring the Seismic Resilience of Housing Systems in Italy
## 3 Application to Housing Systems in Southern Italy  
The proposed resilience measurement framework has been applied to the housing systems of all municipalities in Apulia, Basilicata, Calabria, Campania, and Sicily regions. To estimate their seismic robustness, a probabilistic risk analysis has been performed through the convolution of vulnerability, exposure, and hazard models. In recent works [28; 45], these models have been used to assess and define Urban Limit Conditions (ULCs) and resilient mitigation strategies of specific Territorial Contexts (TCs) defined according to the emergency planning exigencies of Italian Civil Protection. The vulnerability curves proposed by [PERSON] et al. [28; 35] have been considered as vulnerability models. Such curves were obtained from the macroseismic approach of [PERSON] and [PERSON] [46], referring to their probable vulnerability values (\(V-\) and \(V+\)) for masonry and RC building types, and using the I-PGA correlation law of [PERSON] [47] or [PERSON] and [PERSON] [48]. As shown in Figures 2 and 3, the considered vulnerability curves correlate the damage factor (i.e., the expected repair cost ratio as a percentage of the building replacement cost) with the hazard intensity measure expressed in terms of Peak Ground Acceleration (PGA), considering four masonry vulnerability classes (A, B, C1 and D1) and two RC vulnerability classes (C2, D2), together with two height classes (L= 1-2 stories and MH\(\geq\) 3 stories). To take into account the structural response uncertainties of the different building types associated with a specific vulnerability class, two different vulnerability models have been adopted. These vulnerability models were defined according to the repair cost ratios of buildings in L'Aquila [49] and work well with exposure models developed at large scales (e.g., regional or national scales), which are usually based on poor census data aggregated at the municipality level. The exposure model of the considered residential building stock and its occupants has been obtained from the national census data on buildings and population [50]. These data are disaggregated at the sub-municipal level according to census sections that cover the entire national territory. The main characteristics of buildings include structural material, construction age, and number of stories. Referringto the criteria used in the National Risk Assessment [51], vulnerability classes are derived from structural material and construction age. Consequently, the considered residential buildings have been grouped in twelve taxonomies (one for each vulnerability and height class), combining their structural material and construction age with their number of stories. In this way, the residential assets have been appropriately sampled and spatially linked to the corresponding vulnerability models taking into consideration their geographic coordinates together with their structural material, construction age, number of stories and occupants, built area, and structural and non-structural replacement cost. Such cost has been assumed constant among the twelve taxonomies and equal to 1200 EUR / m\({}^{2}\), which represents the mean reconstruction cost of buildings in L'Aquila [49]. It can be assigned to the entire portfolio because the repair cost ratios used in the vulnerability curves definition refer to buildings in L'Aquila. These repair cost ratios strictly depend on the seismic damage suffered by buildings rather than on the hazard intensity [49]. Figure 3: Vulnerability curves proposed by [PERSON] et al. [28; 35] for RC buildings with height classes: (**a**) Low (L = 1–2 stories); (**b**) Medium–High (MH \(\geq\) 3 stories). Figure 2: Vulnerability curves proposed by [PERSON] et al. [28; 35] for masonry buildings with height classes: (**a**) Low (L = 1–2 stories); (**b**) Medium–High (MH \(\geq\) 3 stories).