| dc.description.abstract | Small unmanned/uninhabited aerial vehicles (UAVs) are quickly becoming a cost-effective alternative for mapping and volumetrics, particularly for small- to medium-sized earthwork projects. However, the accuracy of photogrammetrically derived digital terrain models (DTMs) from UAV imagery is not extensively tested. This gap is addressed through a case study of stockpile volume estimation. A gravel stockpile was surveyed with a vertical take-off and landing UAV before and after a portion of it was excavated. Softcopy photogrammetry was applied to the UAV images to produce before and after DTMs, each with a resolution of 3.5 cm. The vertical accuracy of the UAV DTMs was estimated with global positioning system (GPS) test points, yielding RMS errors of 0.106 (before) and 0.097 m (after). These errors are similar to, if not lower, than those produced by airborne light detection and ranging (LIDAR), in general, but are higher than for terrestrial laser scanning. The before and after volume of the stockpile estimated from the UAV DTMs was 2.6 and 3.9% lower than the volume estimated from GPS-interpolated DTMs. By differencing the two UAV DTMs, the volume of gravel extracted from the stockpile was estimated and compared with a haul ticket. According to the latter, the extracted volume was | |
