Nripojyoti Biswas

The long-term monitoring of transportation infrastructure assets at a lower cost and with short mobilization time is of significant interest to both state and federal transportation agencies in the U.S. Because of the significant improvement in spatial and temporal resolution of synthetic aperture radar (SAR) remote sensing systems and a notable reduction in the cost of data acquisition, SAR has now become a viable method to provide economic and rapid condition assessment of transportation assets. A research study was developed and performed to comprehensively perform the inspection and characterization of a pavement surface based on the amplitude of backscattering of an X-band radar. In situ characterization of the test site was first performed using traditional inertial profilers and aerial photogrammetry with unmanned aerial vehicle (UAV) surveys. The results from these in situ methods were compared with the corrected amplitude of the SAR data, which indicated that the distribution of surface roughness values computed from the inertial profiler, UAV, and SAR exhibited similar probability densities at various segmental lengths considered in this study. This suggested that the problematic areas that are evident during in situ characterization can be delineated and quantified based on the normalized radar cross section of the pavement surface. Overall, the outcome of this research exhibits the potential of SAR for future transportation asset management undertakings, and the systematic framework developed as a part of this research could be of significant interest to engineers and transportation practitioners.

Infrastructure in the U.S.A. was graded with a “C–” in the 2021 ASCE report card. Frequent monitoring of infrastructure assets is key to ensuring the serviceability of the assets and safety of public users. Advancements in aerial technologies, compact sensors, computer processing, and image analysis software have given rise to various engineering applications of sensor-mounted unmanned aerial vehicle (UAV) platforms. Several contactless sensors are being mounted on UAVs to conduct a comprehensive assessment of infrastructure conditions compared to a qualitative visual examination by an experienced inspector. Many transportation agencies in the U.S.A. have been using UAVs for applications ranging from the research stage to regular inspection activities. These applications are mainly focused on inspecting infrastructure assets such as pavements, bridges, substructures, railways, and other assets. The current research discussed the approaches followed to conduct aerial condition monitoring of transportation infrastructure assets using optical sensors mounted on UAVs. Qualitative and quantitative inspections of pavement, bridge, and substructure infrastructure case studies were performed. Pavement distress extents were measured in three dimensions and a 360° inspection of bridges was conducted by accessing hard-to-reach areas. Scaled views of the four sides of a bridge were developed and the challenges in data collection and processing were outlined. Further, a localized inspection was also demonstrated to show the feasibility of using photogrammetry for remote condition assessments post-disaster/emergency. Overall, the rich visualization, safety, flexibility, and ease of handling offered by these technologies are expected to transform the method of conducting infrastructure performance monitoring inspections in the future.