Remote sensing for detecting and tracking damage on municipal infrastructure systems: A review of recent trends

Abstract

Ensuring safety, serviceability and resilience of infrastructure components and systems are key considerations for asset owners and engineers. However, realisation of these performance objectives is often hindered by ageing infrastructure and exposure to both natural and anthropogenic hazards. Furthermore, much of a nation’s infrastructure may be located in extreme or remote environments where access for inspection and maintenance is costly, dangerous or even impossible. Remote sensing is increasingly being used by civil engineers to inspect and monitor infrastructure assets and systems. Remote sensing systems can capture data across large geographical regions using e.g. satellite flyovers or surveys using camera and/or laser technology carried by drones. Remote sensing systems can also provide off-site access to real-time data using wireless transmissions from fixed sensors and/or sensor arrays. Remote sensing is also an important approach for inspections in post-disaster zones due to, for example, access limitations, safety concerns and the need for rapid data collection post-event to guide relief efforts. Monitoring infrastructure performance and tracking damage progress on fixed infrastructure assets can also be attempted using remote sensing systems. The increasing use of many types of SHM systems has in part been driven by the desire to supplant or at least enhance visual inspection regimes. This paper presents a concise review of recent literature on the use of remote sensing approaches in municipal engineering applications focussing on both assessment of individual infrastructure assets and distributed infrastructure systems. The synthesis of the results of the review aims to illustrate to what extent remote sensing approaches are actually replacing or supplementing visual inspection efforts across a range of scenarios e.g. pre- and post-disaster and during normal operation. The paper also discusses possible uses of artificial intelligence and machine learning to process the large quantities of data generated by some remote sensing systems. The paper concludes with recommendations for asset owners and operators considering increasing their use of remote sensing systems for infrastructure assessments.