Regional-scale bridge condition monitoring using InSAR displacements and environmental data

Abstract

This article introduces a novel methodology for detecting and classifying anomalies in multiple bridges within a geographical region using satellite-based interferometric synthetic aperture radar displacements and environmental measures. The approach uses subspace alignment to harmonize bridge features, enabling the detection of anomalies based on deviations in one bridge compared to the rest of the population. Simulated and real case studies involving steel railway bridges spanning the Po River in Italy demonstrate the effectiveness of the proposed approach, showcasing its potential for large-scale applications. Moreover, the study explores the transferability of knowledge from simulated data to real-world monitoring scenarios, yielding promising results in classifying real instances using synthetic labels. The proposed approach presents practical benefits for bridge monitoring agencies by providing a cost-effective method for enhancing the resilience and safety of transportation infrastructure.