A screening and prioritization framework for regional-scale bridge health assessment based on spaceborne radar measurements

This work presents a screening and prioritization framework for regional-scale bridge assessment using spaceborne radar measurements enriched with environmental and geospatial data. Each bridge is represented through a compact set of distribution-based features derived from differential interferometric synthetic aperture radar (DInSAR) displacement measurements. This representation reduces sensitivity to measurement noise and geolocation uncertainty of DInSAR measures, enabling consistent bridge-level analysis even with medium-resolution data. A bridge-level anomaly detection strategy is introduced, where deviations from expected behavior are evaluated relative to a virtual baseline that accounts for ongoing long-term displacement trends and previously experienced environmental conditions. The resulting anomaly index is combined with persistence criteria to support both long-term anomaly mapping and date-specific inspection. These functionalities are integrated into an interactive dashboard for infrastructure assessment and prioritization. The framework is demonstrated over a 22,510 km2 area in Emilia–Romagna, Italy, with results from Sentinel-1 data supported by consistent patterns observed in high-resolution COSMO-SkyMed measurements.