Integrated approach to improve Road Infrastructure Resilience through complementary Non-Destructive Techniques

Abstract

Transportation infrastructure serves as the backbone of societal functionality. As aging road networks present increasing challenges, effective monitoring and maintenance become imperative. In this context, this article explores the integration of non-destructive techniques for monitoring and assessing damaged road sections. The work emphasizes the importance of leveraging the complementarity between non-destructive techniques to gain a holistic understanding of damaged road sections' structural integrity. Through the combination of these techniques, structural issues and underlying causes can be identified, as well as to develop maintenance and rehabilitation strategies.A case study of a critical section of the national road N-541 in Pontevedra, Spain, illustrates the application of this integration. First, Interferometry Synthetic Aperture Radar (InSAR) technology revealed points of interest. Four different cases, with two different methods: Scatterer Interferometry (PSI) and Quasi-PS (QPS) were used, to minimize uncertainty. Then, Global Positioning System (GPS) data, together with Laser Imaging Detection and Ranging (LiDAR), were used to create Digital Elevation Models (DEM). Finally, Ground Penetrating Radar (GPR) was useful to create a data cloud of possible subsurface damages. Machine learning technique (clustering) was applied to the GPR data to assist in defect depth analysis, further improving understanding and knowledge. The integration of complementary non-destructive methods offers a comprehensive framework for advancements in road infrastructure analysis and maintenance strategies, thus contributing to decision-makers to enhance transportation infrastructures' resilience and longevity.