Use of Digital Elevation Model for Detecting Airfield Pavement Distress

Abstract

A digital elevation model (DEM) is a topographic representation of a bare surface, usually referring to the Earth’s surface. DEMs have been used for flood assessment, landside hazard detection, soil properties’ quantification, road and highway planning, etc. Recently, DEMs generated using small unmanned aircraft systems (sUAS) have shown potential in transportation infrastructure inspection. In this study, we evaluated the performance of sUAS-collected DEM data to detect airfield pavement distresses. Natural-color red-green-blue (RGB) data were collected from both Portland cement concrete (PCC) and asphalt concrete (AC) pavements at three airports with UAS. The data were processed to generate an RGB optical orthophoto using close-range photogrammetry, and one product of that process was a DEM representing the airfield pavement in three-dimensional space. The resolution of the generated DEMs varied from 2.8 mm/pix to 84 mm/pix based on sUAS sensors, flying altitude, and parameters selected for RGB data processing. The DEMs were studied for their usefulness in visually identifying 14 PCC pavement distresses and nine AC pavement distresses. Analysis showed that DEM with 6 mm/pix resolution or better can be useful for detecting one or more severity levels of 13 PCC pavement distresses and 6 AC pavement distresses. High-resolution DEMs were also useful in identifying distresses related to elevation differences, such as shoving, depression, and faulting. This study illustrates the potential of DEM data in airfield pavement distress detection.