The unprecedented increase in the severity and frequency of natural disasters, often as consequences of multi-hazard events, led to worldwide special attention to disasters risks reduction. Meanwhile, awareness about the vulnerability of transportation and infrastructure systems situation during a natural disaster emergency plays a significant role in the disaster management process and urban and regional planning. This study focuses on assessing the vulnerability of the transportation network in the Province of Pavia, Italy, with a particular emphasis on flood risk. The analysis follows a five-step methodology using the Analytic Hierarchy Process—AHP, supported by expert evaluation through the Delphi method, to assign weights to selected indicators, combined with Geographic Information System—GIS tools for spatial analysis. By overlaying vulnerability layers with existing flood hazard maps, the study identifies the most at-risk municipalities. The results provide valuable insights for policy makers, planners, and emergency response managers, enabling data-driven decisions for improving infrastructure resilience in flood-prone territories.

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Assessing Spatial Vulnerability Throughout AHP: Flood Risk of Transportation Network in Pavia Province, Italy

  • Nastaran Esmaeilpour Zanjani,
  • Roberto De Lotto,
  • Caterina Pietra,
  • Elisabetta Venco

摘要

The unprecedented increase in the severity and frequency of natural disasters, often as consequences of multi-hazard events, led to worldwide special attention to disasters risks reduction. Meanwhile, awareness about the vulnerability of transportation and infrastructure systems situation during a natural disaster emergency plays a significant role in the disaster management process and urban and regional planning. This study focuses on assessing the vulnerability of the transportation network in the Province of Pavia, Italy, with a particular emphasis on flood risk. The analysis follows a five-step methodology using the Analytic Hierarchy Process—AHP, supported by expert evaluation through the Delphi method, to assign weights to selected indicators, combined with Geographic Information System—GIS tools for spatial analysis. By overlaying vulnerability layers with existing flood hazard maps, the study identifies the most at-risk municipalities. The results provide valuable insights for policy makers, planners, and emergency response managers, enabling data-driven decisions for improving infrastructure resilience in flood-prone territories.