期刊
JOURNAL OF MARINE SCIENCE AND TECHNOLOGY-TAIWAN
卷 29, 期 1, 页码 1-17出版社
NATL TAIWAN OCEAN UNIV
DOI: 10.51400/2709-6998.1000
关键词
Unmanned aerial vehicles; Photogrammetry; Beach topography
This study developed a method for beach topography surveillance using unmanned aerial vehicles (UAVs) equipped with cameras and positioning systems. Comparisons between image-matching point clouds and direct measurements showed that UAVs at an operational altitude of 70 m had a ground sample distance of 3.26 cm and measurement errors within acceptable criteria.
The mechanisms of in situ topography changes must be identified for spatial planning in coastal areas. In this study, the authors used in situ direct measurement methods and indirect remote-sensing technologies to develop a method for beach topography surveillance. Unmanned aerial vehicles (UAVs) have advantages of high portability and mobility and low operating altitude. Therefore, a UAV was equipped with a lightweight camera and a positioning system that comprised a global positioning system and an inertial measurement unit. Aerial photogrammetry and aerial triangulation methods were adopted for matching image feature points to obtain the corresponding topographic points in the sand. A virtual base station with real-time kinematic positioning functionality was used to measure the coordinates of the ground control points for correcting the actual coordinates to obtain actual topographic points of the beach sand. The results obtained using image-matching point clouds and direct measurements were compared. The ground sample distance of a UAV at the operational altitude of 70 m was 3.26 cm. Moreover, the average elevation error was 3.20 cm, and the root mean square error was 0.169 m. The measurement error was +/- 25 cm, which was within the acceptance criteria of +/- 50 cm set by Water Resources Agency, Ministry of Economic Affairs, Taiwan. UAV imaging technology can increase the efficiency of conventional manual sampling and reduce the cost of indirect observations, thus minimizing the measurement errors and field measurement costs.
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