Supporting “Build Back Better” in historical towns: a novel methodology to include users’ exposure and vulnerability in strategic function relocation assessment

This work aims to develop a methodological framework to evaluate the multi-scale impact of function relocation in Historical Urban Built Environments (HUBEs) assessing users' vulnerability and exposure at the: (1) macroscale, to evaluate if relocation can benefit the whole HUBE safety; (2) mesoscale (open space-related), to identify critical “hot-spots” in the HUBE. The framework is showcased on a significant earthquake-prone Italian HUBE. Applying ‘Build Back Better’ (BBB) principles to Historical Urban Built Environments (HUBEs) means balancing sustainable structural and non-structural strategies with revitalization and preservation tasks, by addressing multiple risk factors. Among them, user exposure (“how many people?”) and vulnerability (“of which typology?”) can describe how the HUBE and its composing parts can be attractive depending on their functions, also impacting potential damage and losses. Relocating strategic functions can directly impact these factors, being strictly linked with urban policies.

Existing approaches try to quantify user factors over space and time, but operational implications for decision-makers seem to be still limited. In particular, validated methodologies exploiting geospatial tools are used to generate typical use scenarios (i.e. daytime, night-time, holidays), aggregating micro-scale inputs on indoor and outdoor functions at meso/macroscales. User factors metrics are derived to compare current and relocation scenarios on selected buildings. Results demonstrate the framework capabilities in quantifying relocation impacts at the considered scales, thus providing valuable support to urban planning practices. Its implementation in decision-support systems would enable dynamic monitoring of urban development policies, prioritizing risk-reduction over space, and focusing interventions on physical vulnerability where user factors impact increases.