Terrestrial and unmanned aerial system imagery for deriving photogrammetric three-dimensional point clouds and volume models of mass wasting sites

Abstract

Three-dimensional (3-D) geodata of mass wasting sites are important to model surfaces, volumes, and their changes over time. With a photogrammetric approach commonly known as structure from motion, 3-D point clouds can be derived from image collections in a straightforward way. The quality of point clouds covering a quarry dump derived from terrestrial and aerial imagery is compared and assessed. A comprehensive set of quality indicators is calculated and compared to surveyed reference data and to a terrestrial LiDAR point cloud. The examined indicators are completeness of coverage, point density, vertical accuracy, multiscale point cloud distance, scaling accuracy, and dump volume. It is found that the photogrammetric datasets generally represent the examined dump well with, for example, an area coverage of up to 90% and 100% in case of terrestrial and aerial imagery, respectively, a maximum scaling difference of 0.62%, and volume estimations reaching up to 100% of the LiDAR reference. Combining the advantages of 3-D geodata derived from terrestrial (high detail, accurate volume calculation even with a small number of input images) and aerial images (high coverage) can be a promising method to further improve the quality of 3-D geodata derived with low-cost approaches.