A new approach to enhancing inSAR-based subsidence detection in pavements: validation with complementary FWD and GPR data

This article explores the benefits of a novel, non-invasive, and multi-scale methodology for pavement condition monitoring by developing a Key Performance Indicator (KPI) derived from Interferometric Synthetic Aperture Radar (InSAR) results, obtained through the Persistent Scatter Interferometry (PSI) and Quasi-PS (QPS) methods. These methods were applied with SARPROZ software using Sentinel-1 images. InSAR enables network-level identification of subsidence and differential settlements, particularly in transition zones. For the first time, InSAR outputs are synthesized into an interpretable KPI and validated against complementary non-destructive tests—Falling Weight Deflectometer (FWD) and Ground Penetrating Radar (GPR), with the goal of providing a cost-effective and holistic joint assessment methodology, ensuring more, overcoming the interpretation limitations of stand-alone tests, and optimizing the required amount of in-situ measurements. FWD loading tests were performed to provide information on the structural condition of the pavement, while GPR measurements, using air-launched frequency antennas (1.0 GHz and 1.8 GHz), detected changes in pavement structure and possible internal defects. The results obtained demonstrate that implementing a KPI synthesizes InSAR outputs into a more interpretable and actionable metric, validated with more meaningful correlations with FWD and GPR analysis, enabling the detection of transition zones, specific elements, and potential damages. From KPI it was also determined the limit of detection for the case study in a national road in Portugal. The holistic approach offers a more efficient, safer, and cost-effective tool for evaluating pavement condition.