UAV, computer vision, structure from motion, landslide, terrestrial laser scanning
Structure from motion (SfM) computer vision is a remote sensing method that is gaining popularity due to its simplicity and ability to accurately characterize site geometry in three dimensions (3D). While many researchers have demonstrated the potential for SfM to be used with unmanned aerial vehicles (UAVs) to model in three dimensions various geologic features such as landslides, little is understood how the selection of the UAV platform can affect the resolution and accuracy of the model. This study evaluates the resolution and accuracy of 3D point cloud models of a large landslide that occurred in 2013 near Page, Arizona that were developed from various small UAV platform and camera conﬁgurations. Terrestrial laser scans (TLS) were performed at the landslide and were used to establish a comparative baseline model. Results from the study indicate that point cloud resolution improved by more than 16% when using multi-rotor UAVs instead of ﬁxed-wing UAVs. However, accuracy of the points in the point cloud model appear to be independent of the UAV platform, but depend principally on the selected camera and the image resolution. Additional practical guidance on ﬂying various UAV platforms in challenging ﬁeld conditions is provided for geologists and engineers.
Original Publication Citation
BYU ScholarsArchive Citation
Ruggles, Samantha; Clark, Joseph; Franke, Kevin W.; Wolfe, Derek; Reimschiissel, Brandon; Martin, Ronald Abraham; Okeson, Trent; and Hedengren, John, "Comparison of SfM Computer Vision Point Clouds of a Landslide Derived from Multiple Small UAV Platforms and Sensors to a TLS based Model" (2016). All Faculty Publications. 1685.
NRC Research Press
Ira A. Fulton College of Engineering and Technology
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