Bayesian Data Fusion for Enhanced Monitoring of Bridge Displacements Using Satellite InSAR and Topographic Techniques

This paper introduces a Bayesian data fusion methodology for monitoring bridge displacements, using a synergistic combination of satellite Interferometric Synthetic Aperture Radar (InSAR) and topographic measurements. Focused on the Belprato 2 Viaduct affected by a slow-moving landslide, this research highlights the advantages of integrating multiple data sources to surpass the limitations of individual monitoring techniques. The results demonstrate substantial improvements in the accuracy and temporal resolution of displacement measurements, highlighting the utility of data fusion in structural health monitoring of aging infrastructures.