How to create seismic risk scenarios in historic built environment using rapid data collection and managing

The Historic Built Environment (HBE) is constantly prone to natural disasters because of its complexity. Resilience-increasing strategies in such a context should both preserve the cultural heritage and make the hosted communities safe. Earthquakes represent critical disasters because of the interactions between HBE elements (i.e.: buildings, open spaces, urban paths) and its inhabitants. Thus, the practical development of emergency plans and related risk reduction strategies should consider the induced effects of the earthquake on the HBE and the spatiotemporal variation in the number of exposed people. This goal needs propaedeutic methods to define relevant scenarios in view of the possible characterization of risk-related factors at the HBE scale. To this aim, this contribution tries to arrange a first sustainable, holistic, easy-to-use, and replicable framework. The paper innovatively provides planners with a unique scheme to reach available data from reliable sources concerning seismic hazard, vulnerability and damage, and exposure (i.e. related to human lives quantification). Results on a case-study application (a typical Italian HBE) demonstrate the framework capabilities, by including the critical HBE damage-related conditions and crowding phenomena (in a multi-hazard perspective, based on the probable number and typologies of exposed individuals). Then, specific solutions can be advanced. The proposed holistic framework can be easily replicable and adaptable due to the possibility to update the employed tools as well as to replace them with other existing and validated ones, giving the same inquired parameters as results. The methodological framework could constitute an effective support for risk scenarios creation at the HBE scale to be used in risk-assessment and emergency plans actions (e.g. basing on typological analyses on buildings/urban tissue, and simulation-based studies including individuals' behaviours in emergency and evacuation) by guaranteeing rapid data collection activities.