Italian historic centres have been facing a process of decline and deterioration whose impact has been irreversibly accelerated by a great number of hazardous events. Among others, earthquakes have destroyed and damaged many settlements highlighting the necessity to improve their seismic risk management strategy by means of an integrated approach. These areas present high vulnerability and exposure associated to the characteristics of the built environment, the demographic distribution, the community and social life, the lack of risk awareness, and finally the poor regulatory framework for their management and maintenance. This research explores the theoretical, methodological and practical issues of developing seismic risk analyses and management plans in Italian historic centres. It develops and tests a multi-level model integrating different approaches and disciplines. The model is tackled on two levels of investigation: at territorial level, to measure and compare the overall vulnerability, shape and redundancy of a sample set of historic centres in the Central Italy, characterized by different size, location and territorial significance; and at local level, to assess the seismic performance of a specific historical settlement, its emergency operability and the necessary interventions. The novelty of the proposal is in the adoption of an interdisciplinary model that links the data collection and analysis to the decision-making process. This task is achieved by applying a set of instruments for the development of a fit-for-purpose platform. In particular, Geographic Information Systems (GIS), Vulnerability Index Methods (VIM) and Space Syntax analysis are employed to inform and support the development of effective disaster mitigation strategies. As a result, this approach develops large-scale data-driven intervention priorities and site-specific measures aimed at mitigating the impact of future earthquakes as well as assisting early recovery and reconstruction activities.
Seismic risk management in historic centres. Integrated large-scale modelling for a scenario-based methodology
2020
Abstract
Italian historic centres have been facing a process of decline and deterioration whose impact has been irreversibly accelerated by a great number of hazardous events. Among others, earthquakes have destroyed and damaged many settlements highlighting the necessity to improve their seismic risk management strategy by means of an integrated approach. These areas present high vulnerability and exposure associated to the characteristics of the built environment, the demographic distribution, the community and social life, the lack of risk awareness, and finally the poor regulatory framework for their management and maintenance. This research explores the theoretical, methodological and practical issues of developing seismic risk analyses and management plans in Italian historic centres. It develops and tests a multi-level model integrating different approaches and disciplines. The model is tackled on two levels of investigation: at territorial level, to measure and compare the overall vulnerability, shape and redundancy of a sample set of historic centres in the Central Italy, characterized by different size, location and territorial significance; and at local level, to assess the seismic performance of a specific historical settlement, its emergency operability and the necessary interventions. The novelty of the proposal is in the adoption of an interdisciplinary model that links the data collection and analysis to the decision-making process. This task is achieved by applying a set of instruments for the development of a fit-for-purpose platform. In particular, Geographic Information Systems (GIS), Vulnerability Index Methods (VIM) and Space Syntax analysis are employed to inform and support the development of effective disaster mitigation strategies. As a result, this approach develops large-scale data-driven intervention priorities and site-specific measures aimed at mitigating the impact of future earthquakes as well as assisting early recovery and reconstruction activities.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/137538
URN:NBN:IT:UNIPI-137538