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Sediment Transport of Coastal Region Using Time-Series Unmanned Aerial Vehicle Spatial Data.
- Source :
- Journal of Marine Science & Engineering; Jul2023, Vol. 11 Issue 7, p1313, 15p
- Publication Year :
- 2023
-
Abstract
- Continuous monitoring of the varying topographical characteristics of shorelines is important for effective coastal management. Closed-circuit television (CCTV) cameras are installed to accumulate photographic data on coastal topographical changes. The overall change in the coastal waters can be intuitively understood from the images. However, the amount of three-dimensional (3D) changes that can be grasped is limited. To address this, studies have employed aerial photogrammetry, which is the use of unmanned aerial vehicles (UAVs) to capture aerial pictures, construct 3D models of target areas, and perform analysis through scale-invariant feature transform and structure from motion technologies. Although highly efficient, this technique requires several ground-control points (GCPs), which could corrupt the overall imagery. This study designs real-time kinematics—global navigation satellite system (RTK–GNSS) UAV, which requires few GCPs. To evaluate the positional accuracy of the captured UAV orthographic images and digital surface models (DSMs) used for precise coastal terrain measurements, a virtual reference service survey was performed to determine the vertical errors. The R-squared was 0.985, which is close to 1.0. Short-term and one-year topographic changes before and after a storm were investigated using time-series UAV image data after a coastal maintenance project. Analysis of the coefficient of variation in the beach volume for one year revealed that submerged breakwater reduced erosion during high wave resistance. The submerged breakwater located in the center exhibited variability similar to the opening. Hence, this method is more suitable for periodically monitoring coastal areas. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20771312
- Volume :
- 11
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- Journal of Marine Science & Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 169330221
- Full Text :
- https://doi.org/10.3390/jmse11071313