Use of small unmanned aircraft systems in airfield pavement inspection: implementation and potential

Routine maintenance can make an airfield pavement last for an extended period and regular pavement inspections help to identify the need for such maintenance. There is scope for comprehensively evaluating small Unmanned/Uncrewed Aircraft Systems (sUAS), also known as drone, data use in airfield pavement inspection. This research team collected sUAS data from six airports, which were processed into red-green-blue (RGB) orthophotos, Digital Elevation Models (DEMs), hillshades from DEMs, and thermal orthophotos. The RGB optical data were useful in detecting 13 out of 14 available Portland cement concrete (PCC) pavement distresses and 5 out of 9 available asphalt concrete (AC) pavement distresses. DEMs were also useful in confirming the location of distresses with elevation changes. RGB data of 1.5 mm/pixel and DEM data of 6 mm/pixel or better were recommended for pavement distress detection and rating. Pavement Condition Index (PCI) values were calculated using sUAS data and compared with foot-on-ground (FOG) inspection PCI values. The mean differences between FOG PCI and sUAS PCI ranged from 1.3 to 9.1 for six airports. The Pearson correlation coefficient R-value varied from 0.79 to 0.90, showing a strong correlation and demonstrating the potential for future integration of sUAS-based PCI inspection to complement FOG inspection.