Road Crack Detection and Orientation Estimation in Airborne Radar Data

Abstract

Cracks on road surfaces compromise vehicle safety and ride comfort, and if left unaddressed, they can develop into larger potholes. Synthetic aperture radar (SAR) data acquired by high-resolution airborne SAR systems are sensitive to changes on the road surface and can be utilized for periodic road condition monitoring. In this study, the airborne X-band SAR data acquired by DLR's F-SAR system with 25 cm spatial resolution are used for detecting road surface cracks together with their severity and orientation information. A novel method combining an adaptive thresholding algorithm with the Radon transform is proposed, where the adaptive thresholding algorithm detects cracks and the Radon transform qualitatively quantifies their severity by analyzing the maximum Radon magnitude values from the sinogram. Additionally, the Radon transform determines the orientation of cracks, expressed as bearing angles relative to the true north. Validation against Google Earth images confirms the close agreement between the detected cracks and their actual locations and orientations. This research highlights the potential of airborne SAR data for predictive road maintenance, enabling early intervention to prevent further surface degradation.