Damage characterisation using stand-off observations to enable recovery: the case of infrastructure affected by targeted attacks

During conflicts, bridges are prime targets due to their strategic importance in transportation and economic growth. Their destruction hampers resilience efforts, delaying economic recovery. Limited research exists on characterising bridge damage via stand-off observations. This paper integrates diverse data sources and emerging technologies for comprehensive bridge damage assessment based on stand-off observations using remote sensing techniques. A case study in Ukraine employs Sentinel-1 SAR images, crowd-sourced data, and deep learning techniques to assess damage at various scales, from regional, to asset and component scale. This approach facilitates swift decision-making for infrastructure development and restoration planning. By providing crucial intelligence to decision-makers and funders, it aids in prioritising recovery investments and expediting post-disaster resilience planning for critical infrastructure.