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For decades, remote sensing technologies and the non-destructive testing (NDT) methods have been used for the assessment of transport infrastructure, highways, railways and airfields. The existence of provisions of multi-source, multi-scale and multi-temporal based information on infrastructure conditions on one hand and the developments of hardware and software technologies in the other, have provided opportunities for the growth of the applications of NDT techniques. The outcome lends itself to be incorporated into existing infrastructure management models. This paper presents an overview of the latest developments in ground-based (Ground Penetrating Radar (GPR) and interferometric radar systems) and satellite (space-borne Synthetic Aperture Radar (SAR) interferometry) remote sensing that applied to transport infrastructures. The applications of GPR to pavements, e.g. multi-layered pavement structure and asphalt concrete (AC) density, and rail-tracks, e.g. ballast assessment are discussed. In addition, the applicability of ground-based radar interferometry and SAR for the bridge structural health monitoring and horizontal transport infrastructure is presented. A novel integrated approach is introduced to form the base of a novel intelligent transport infrastructure management system. The approach is aimed utilizing the structure condition assessment-based information collected using SAR and NDT techniques to prioritize maintenance/rehabilitation activities of transportation assets. For example, analyses of multi-temporal SAR data are used to identify areas of concern at the network level (e.g. differential settlements at bridge approaches or rail track-beds, and excessive deformation rate of pavement surface). The identified locations would be further assessed using ground-based techniques to collect more accurate data. This approach would provide an effective, efficient, and sustainable state of good repair over the life cycle of the transportation infrastructure system.

In recent years, successful applications of the Synthetic Aperture Radar Interferometry (InSAR) have been reported for the monitoring of subsidence and deformation in transport infrastructures. Compared to other non-destructive surveying methodologies, this technique can perform network-level analyses more rapidly and it can provide time-series of ground displacements by multi-temporal data acquisition. However, processing of satellite images by high-resolution sensors (i.e., X-band radars) is demanding in terms of computational resources and specialist skills. This aspect has contributed to partially hinder this technique to become a strategic infrastructure asset management tool. Parallel to this, it is important to emphasise that the use of middle-range frequency SAR sensors (i.e., C-band) allows for the acquisition of lighter datasets and, hence, more computationally affordable analyses. However, due to a lower system resolution and the challenges in identifying features of scattering objects with size below the resolution cell, the C-band imagery is usually not employed for infrastructure monitoring. This limitation could be compensated in rural environment areas, where transport infrastructures are usually the most stable scatterers.\ud This study aims to demonstrate the viability of the medium-range resolution SAR imagery in transport asset monitoring for the preliminary identification of sections affected by subsidence in rural areas. InSAR analyses of high (COSMO-SkyMed) and medium-resolution (Sentinel-1A) datasets are performed on a dual-carriageway rural motorway. A comparison between the Persistent Scatterers Interferometry (PSI) outcomes from data processed with the two resolutions demonstrates the viability of using Sentinel-1A images for multi-temporal subsidence monitoring in highway infrastructure.