NETWORK-SCALE PAVEMENT ROUGHNESS MAPPING USING SPACEBORNE HIGH RESOLUTION X-BAND SAR DATA

This paper studies the applicability of radar remote sensing data, specifically, high-resolution Synthetic Aperture Radar (SAR) data acquired at X-band frequencies, to the network wide mapping of pavement roughness of roads in the United States. Based on a comparison of high -resolutionX -band images from the Cosmo-SkyMed satellites with road roughness data in the form of International Roughness Index (IRI) measurements, we found that X -band radar brightness generally increases when pavement roughness worsens. We developed a signal model that relates radar brightness to IRI, and successfully inverted this model to distinguish well maintained road segments from segments in need of repair. Over test sites in Augusta County, VA, we found that our classification scheme reached an overall accuracy of 92%. This study demonstrates the capacity of X -band SAR for pavement roughness mapping and suggests that an incorporation of X -band SAR data into DOT operations could provide benefits that may result in costs savings.