Influence of Different Illumination Conditions on 3D Reconstruction Accuracy of Erosion Gully
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S252.9

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    Abstract:

    In order to further explore the differences in accuracy of UAV-derived 3D models under different lighting conditions, four phases of digital surface models were constructed by UAV photography technology under sunny and cloudy conditions, and elevation points measured by RTK (real-time kinematic) and digital elevation model obtained by 3D laser scanner were taken as benchmark, respectively. At the typical section and the entire erosion gully scale, the difference in elevation accuracy of 3D reconstruction of erosion gully under different lighting conditions was analyzed. The results showed that: (1) At the typical section scale, the elevation accuracy of the model constructed on cloudy days was the highest, and the elevation accuracy of the model constructed at noon on sunny days was higher than that in the morning and afternoon, while the elevation error of the shaded area was 0.138~0.217 m higher than that in the non-shaded area. (2) At the entire erosion gully scale, the root mean square error of the aerial survey elevation model on cloudy days was only 0.155 m, which was the minimum. For different periods of sunny days, the elevation error of DSM obtained by UAV survey at noon was the lowest, but it was still 0.411 m higher than that of DSM on cloudy days. Based on the three elevation models of sunny days, the elevation error in the shaded area was 0.250~0.346 m higher than that in the non-shaded area. (3) From different slope aspects, the elevation error of sunny slope was the lowest, while the increasing of shadow area led to the further increase of other slope aspects errors. The results showed that the shadow caused by illumination significantly reduced the accuracy of the elevation model, which could provide a reference for the research of aerial mapping of erosion gully based on UAV.

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History
  • Received:June 14,2022
  • Revised:
  • Adopted:
  • Online: February 10,2023
  • Published: February 28,2023
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