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

Damage characterisation using stand-off observations to enable recovery: the case of infrastructure affected by targeted attacks
Auteur(s): , , , ,
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Présenté pendant IABSE Congress: Beyond Structural Engineering in a Changing World, San José, Cost Rica, 25-27 Seotember 2024, publié dans , pp. 785-791
DOI: 10.2749/sanjose.2024.0785
Prix: € 25,00 incl. TVA pour document PDF  
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During conflicts, bridges are prime targets due to their strategic importance in transportation and economic growth. Their destruction hampers resilience efforts, delaying economic recovery. Limite...
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Détails bibliographiques

Auteur(s): (University of Birmingham, UK)
(University of Birmingham, UK)
(University of Birmingham, UK)
(Centre for Research and Technology Hellas (CERTH), Athens, Greece)
(Centre for Research and Technology Hellas (CERTH), Athens, Greece)
(Centre for Research and Technology Hellas (CERTH), Athens, Greece)
(Brunel University London, UK)
(Brunel University London, UK)
Médium: papier de conférence
Langue(s): anglais
Conférence: IABSE Congress: Beyond Structural Engineering in a Changing World, San José, Cost Rica, 25-27 Seotember 2024
Publié dans:
Page(s): 785-791 Nombre total de pages (du PDF): 7
Page(s): 785-791
Nombre total de pages (du PDF): 7
DOI: 10.2749/sanjose.2024.0785
Abstrait:

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.