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Optimization of UAVs‐SfM data collection in aeolian landform morphodynamics: a case study from the Gonghe Basin, China

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Optimization of UAVs‐SfM data collection in aeolian landform morphodynamics: a case study from the Gonghe Basin, China

Wanyin Luo,* Mei Shao, Xuehua Che, Patrick A. Hesp, Robert G. Bryant, Changzhen Yan and Zanpin Xing

Earth Surf. Process. Landforms (2020),DOI: 10.1002/esp.4965

ABSTRACT: UAVs-SfM (Unmanned Aerial Vehicles- Structure from Motion) systems can generate high-resolution 3D topographic models of aeolian landforms. To explore the optimisation of UAVs-SfM for use in aeolian landform morphodynamics, this study tested flight parameters for two contrasting aeolian landform areas (free dune and blowout) to assess the 3D reconstruction accuracy of the UAVs survey compared with field point measurements using differential RTK-GPS (Real-time Kinematic-Global Positioning System). The results reveal the optimum UAVs-SfM flight set-up at the free-dune site was: flying height = 74 m, camera tilt angle = -90°, photo overlap ratio = 85%/70% (heading/sideways). The horizontal/vertical location error was around 0.028~0.055 m and 0.053-0.069 m respectively, and a point cloud density of 463/m3 was found to generate a clear texture using these flying parameters. For the <20m deep blowout the optimum set-up with highest accuracy and the lowest cliff texture distortion was: flying height = 74 m combined camera tilt angle = -90° and -60°, photo overlap ratio = 85%/70% (heading/sideways), and an evenly distributed GCPs (Ground Control Points) density of 42/km2 using these flying parameters. When the depth of the blowouts exceeded 40 m, the optimum flight/survey parameters changed slightly to account for more challenging cliff texture generation: flying height = 80 m (with -90° and -60°combined camera tilt angle), GCPs density = 63/km2 to generate horizontal and vertical location error of 0.024 m and 0.050 m respectively, and point cloud density of 2597.11/m3. The main external factors that affect the successful 3D reconstruction of aeolian landforms using UAVs-SfM are the weather conditions, manipulation errors, and instrument system errors. The UAVs-SfM topographic monitoring results demonstrate that UAVs provide a viable and robust means for aeolian landform morphodynamics monitoring. Importantly, the rapid and high precision 3D reconstruction processes were significantly advanced using the optimal flight parameters reported here.

文章链接:https://doi.org/10.1002/esp.4965

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