The current climate emergency underscores the necessity of well-designed “climate adaptation strategies” to reduce risks level and enhance resilience, particularly in complex urban contexts like European cities. These strategies face significant challenges in highly vulnerable regions such as the Mediterranean, a recognised "hotspot" for extreme weather events. Within this framework, historical centres represent critical areas requiring strategic approaches to improve “preparedness” with tailored solutions for Cultural Heritage. These strategies address the physical and material degradation of urban and architectural elements while accommodating for the unique features of the "heritage system." This study, part of an ongoing PhD research, aims to develop a Decision Support System (DSS) to guide public administrations in defining localised climate adaptation strategies. The methodology provides a structured framework for analysing and addressing climate risks. It starts with data collection from urban clusters to identify climate indicators and build site-specific datasets. These data are then critically analysed to identify vulnerabilities and critical hotspots. To manage data heterogeneity, the experimental methodology defines a normalisation process using benchmarking tools (Outdoor Damage Index), offering a standardised scale to assess risk levels. This process allows the creation of tailored adaptation strategies and supports decision-making for historical centres. This paper delves into the initial phases of the research, emphasising data acquisition and systematisation as foundational steps for creating a robust framework to guide climate adaptation in the Mediterranean’s historical urban environments.
Decision Support Strategies for Urban Resilience: Mediterranean Historical Centres as Living Laboratories for Climate Adaptation / Armocida, Francesco; Giglio, Francesca; Sarlo, Antonella Blandina. - III:(2025), pp. 923-930. ( HERITAGE 2025 | International Conference on Earthen and Vernacular Heritage: Conservation, Adaptive Reuse and Urban Regeneration Valencia 10-12 settembre) [10.4995/Heritage2025.2025.21179].
Decision Support Strategies for Urban Resilience: Mediterranean Historical Centres as Living Laboratories for Climate Adaptation
Armocida Francesco;Giglio FrancescaConceptualization
;Sarlo Antonella
2025-01-01
Abstract
The current climate emergency underscores the necessity of well-designed “climate adaptation strategies” to reduce risks level and enhance resilience, particularly in complex urban contexts like European cities. These strategies face significant challenges in highly vulnerable regions such as the Mediterranean, a recognised "hotspot" for extreme weather events. Within this framework, historical centres represent critical areas requiring strategic approaches to improve “preparedness” with tailored solutions for Cultural Heritage. These strategies address the physical and material degradation of urban and architectural elements while accommodating for the unique features of the "heritage system." This study, part of an ongoing PhD research, aims to develop a Decision Support System (DSS) to guide public administrations in defining localised climate adaptation strategies. The methodology provides a structured framework for analysing and addressing climate risks. It starts with data collection from urban clusters to identify climate indicators and build site-specific datasets. These data are then critically analysed to identify vulnerabilities and critical hotspots. To manage data heterogeneity, the experimental methodology defines a normalisation process using benchmarking tools (Outdoor Damage Index), offering a standardised scale to assess risk levels. This process allows the creation of tailored adaptation strategies and supports decision-making for historical centres. This paper delves into the initial phases of the research, emphasising data acquisition and systematisation as foundational steps for creating a robust framework to guide climate adaptation in the Mediterranean’s historical urban environments.| File | Dimensione | Formato | |
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