Spatial accuracy assessment of unmanned aerial vehicle-based structures from motion multi-view stereo photogrammetry for geomorphic observations in initiation zones of debris flows, Ohya landslide, Japan
Haruka Tsunetaka, Norifumi Hotta, Yuichi S. Hayakawa, Fumitoshi Imaizumi
Abstract
Abstract Fluctuations in sediment storage arising from sediment discharge and recharge in headwater channels are an important factor influencing changes in landforms in mountainous areas, but the frequency of surveys is limited because of access difficulties and complex topography. Although unmanned aerial vehicle-based structure-from-motion photogrammetry (UAV-SfM) may be effective for topographic measurement, its utilization in headwater channels has not been fully examined. We assessed the accuracy and reproducibility of a digital elevation model acquired via UAV-SfM (DEM SfM ) in a headwater channel within the Ohya landslide area, Japan, using a DEM acquired via terrestrial laser scanning (DEM TLS ). The results indicate that differences in the measured elevation between DEM SfM and DEM TLS in the vicinity of the channel bed ranged from about 0.4 to −0.4 m, with a median of 0.06 m. Hence, the profiles acquired via DEM SfM coincide well with those acquired via DEM TLS , and the spatial distributions and histograms of the measured surface slope were nearly the same for UAV-SfM and TLS. However, part of the DEM SfM indicates low elevation compared with DEM TLS , probably because of topical distortion arising from technical problems in UAV-SfM. The positive and negative differences in volume between DEM SfM and DEM TLS were approximately 200 and −30 m 3 , respectively. To remedy this bias, an alignment of the UAV-SfM point cloud using the TLS point cloud in the hillslope sections was conducted, based on an iterative closest point (ICP) algorithm. Consequently, the median of the elevation differences decreased to −0.002 m, resulting in the positive and negative differences becoming approximately 100 m 3 . This demonstrates that ICP-based alignment can lead to a reduction of the deviation of differences in the estimated volume. In terms of eliminating biases due to topical distortion in elevation, this approach would be valid for the estimation of volumetric changes using UAV-SfM.