Ciampoli, L. Bianchini, Gagliardi, V., Benedetto, A., Alani, A. M. and Tosti, F. (2022) InSAR analysis of C-band data for transport infrastructure monitoring. In: 11th International Conference on the Bearing Capacity of Roads, Railways and Airfields (BCRRA 2022); 28 - 30 Jun 2022, Trondheim, Norway.

Abstract

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. 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.

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