Abstract
Complex landscapes with high topographic relief and intricate geometry present challenges for complete and accurate mapping of both lateral (x, y) and vertical (z) detail without deformation. Although small uninhabited/unmanned aerial vehicles (UAVs) paired with structure-from-motion (SfM) image processing has recently emerged as a popular solution for a range of mapping applications, common image acquisition and processing strategies can result in surface deformation along steep slopes within complex terrain. Incorporation of oblique (off-nadir) images into the UAV–SfM workflow has been shown to reduce systematic errors within resulting models, but there has been no consensus or documentation substantiating use of particular imaging angles. To address these limitations, we examined UAV–SfM models produced from image sets collected with various imaging angles (0–35°) within a high-relief ‘badland’ landscape and compared resulting surfaces with a reference dataset from a terrestrial laser scanner (TLS). More than 150 UAV–SfM scenarios were quantitatively evaluated to assess the effects of camera tilt angle, overlap, and imaging configuration on the precision and accuracy of the reconstructed terrain. Results indicate that imaging angle has a profound impact on accuracy and precision for data acquisition with a single camera angle in topographically complex scenes. Results also confirm previous findings that supplementing nadir image blocks with oblique images in the UAV–SfM workflow consistently improves spatial accuracy and precision and reduces data gaps and systematic errors in the final point cloud. Subtle differences among various oblique camera angles and imaging patterns suggest that higher overlap and higher oblique camera angles (20–35°) increased precision and accuracy by nearly 50% relative to nadir-only image blocks. We conclude by presenting four recommendations for incorporating oblique images and adapting flight parameters to enhance 3D mapping applications with UAV–SfM in high-relief terrain.
Highlights
Uninhabited/unmanned aerial vehicles (UAVs) paired with structure-from-motion and multiview stereopsis (SfM–MVS) photogrammetric workflows ( UAV–SfM) have become widely accepted tools for mapping and modeling in the geosciences [1,2,3,4,5,6,7,8,9,10]
Differences between the terrestrial laser scanner (TLS) reference dataset and UAV–SfM datasets could be attributed to inconsistencies/deformation of reconstructed surface shape, georeferencing errors, or a combination of both
Image sets collected with a single camera angle are unlikely to produce complete datasets and are prone to higher levels of deformation along steep slopes
Summary
Uninhabited/unmanned aerial vehicles (UAVs) paired with structure-from-motion and multiview stereopsis (SfM–MVS) photogrammetric workflows ( UAV–SfM) have become widely accepted tools for mapping and modeling in the geosciences [1,2,3,4,5,6,7,8,9,10]. UAV data acquisition strategies are commonly modeled after conventional airborne photogrammetry (i.e., [19,20]), in which an ‘image block’ is formed from parallel flight lines, flown in a ‘lawnmower’ or ‘snaking’ pattern at a stable altitude, with consistent overlap (frontlap and sidelap), and a nadir (or straight down)-facing camera angle [21,22]. This classic gridded flight plan is straightforward and can be generated automatically by specifying a few basic flight parameters in modern flight planning software (e.g., Pix4Dcapture, DroneDeploy). They are not ideal for recording features exposed along vertical façades (e.g., stratigraphic surfaces along a vertical cliff face) as these features are prone to greater deformation and/or chance of omission from nadir-view sensors [23,24,25]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
