Automated satellite monitoring of roadways and bridges over a regional scale

Abstract

Worldwide, countries are facing the challenge of ageing transport infrastructure, as thousands of assets have already reached the end of their life service. Structural monitoring is crucial to identify damage precursors and prevent structural failure, but the health evaluation of so many assets is challenging. Space-borne Interferometric Synthetic Aperture Radar (InSAR) can remotely provide high-resolution and high-density monitoring data over large areas, allowing to reconstruct the displacement field of structures with millimetre-scale accuracy. InSAR displacement measurements have been widely used within the civil engineering field, demonstrating that this technology can detect building and infrastructure deformations. However, to use satellite datasets for structural-monitoring purpose, (i) InSAR displacement measurements need to be related to large infrastructure inventories and (ii) performance indicators for the identification of structural anomalies on a large scale need to be defined. We present a novel methodology based on the automated integration of InSAR-derived displacements with infrastructure databases for the identification of early warnings over large networks. The proposed methodology is applied to the Italian motorway network and bridges. The proposed methodology leads to the creation of risk maps highlighting the assets which exhibit the most rapid variation in monitored deformations and anomalous differential movements within the infrastructure