Damage characterisation using stand-off observations to enable recovery: the case of infrastructure affected by targeted attacks
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Bibliographic Details
| Author(s): |
Stergios-Aristoteles Mitoulis
(University of Birmingham, UK)
Nadiia Kopiika (University of Birmingham, UK) Jelena Ninić (University of Birmingham, UK) Andreas Karavias (Centre for Research and Technology Hellas (CERTH), Athens, Greece) Pavlos Krassakis (Centre for Research and Technology Hellas (CERTH), Athens, Greece) Nikolaos Koukouzas (Centre for Research and Technology Hellas (CERTH), Athens, Greece) Nataliya Shakhovska (Brunel University London, UK) Sotirios Argyroudis (Brunel University London, UK) |
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| Medium: | conference paper | ||||
| Language(s): | English | ||||
| Conference: | IABSE Congress: Beyond Structural Engineering in a Changing World, San José, Cost Rica, 25-27 Seotember 2024 | ||||
| Published in: | IABSE Congress San José 2024 | ||||
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| Page(s): | 785-791 | ||||
| Total no. of pages: | 7 | ||||
| DOI: | 10.2749/sanjose.2024.0785 | ||||
| Abstract: |
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. |
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| Keywords: |
critical infrastructure remote sensing damage characterisation multi-scale human-induced hazards
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