Abstract
Shallow marine sand waves are formed on the seabed and are widely distributed within tidal environments. However, the use of multibeam echo sounding (MBES) is costly to obtain the bathymetric mapping of large complex sand waves. Therefore, we propose a new method that employs a combination of multiangle sun glint images and sparse MBES data to achieve comprehensive bathymetric mapping of large and complex sand waves. This method involves estimating sea surface roughness, automatically extracting sand-wave crests, conducting adaptive subregion partitioning, estimating the water depth at auxiliary points, and generating digital bathymetric models. The method was employed in a case study of sand waves on the Taiwan Bank. Bathymetric mapping was implemented for large complex sand waves over an area spanning approximately 350 km2 using multiangle sun glint images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer and MBES data. The results show that mapped and measured water depths were well-matched; the root-mean-square error of water depths was 1.77 m, and the relative error was 5.03%. These findings show that bathymetric mapping of large complex sand waves can be effectively conducted using the new method, and as such, the workload of MBES is reduced and efficiency is improved.
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Data Availability Statement
The datasets generated and / or analyzed during the current study are not publicly available due to state policy restrictions, but are available from the corresponding author on reasonable request.
Abbreviations
- MBES:
-
multibeam echo sounding
- ASTER:
-
advanced spaceborne thermal emission and reflection radiometer
- SSR:
-
sea surface roughness
- SAR:
-
synthetic aperture radar
- DBMs:
-
digital bathymetric models
- FFT:
-
fast Fourier transform
- IDSW:
-
distance square weighting method
- UTC:
-
coordinated universal time
- NVI:
-
nadir-looking-view image
- VNIR:
-
visible and near-infrared
- BVI:
-
backward-looking-view image
- NASA:
-
National Aeronautics and Space Administration’s
- SWIR:
-
shortwave infrared
- TIR:
-
thermal infrared
- RMSE:
-
root-mean-square error
- BAS:
-
bathymetry assessment system
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Acknowledgment
The authors wish to acknowledge the cooperative efforts between NASA and Japan’s Ministry of Economy Trade and Industry (METI) during development of the ASTER sensor. The bathymetry datasets used in this study were obtained from the Public Science and Technology Research Fund Project of Ocean (No. 201105001). The authors would like to thank Professor Yan LI from Xiamen University for his comments on this paper.
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Supported by the National Natural Science Foundation of China (Nos. 41876208, 41830540, 41576174)
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Zhang, H., Wang, J., Li, D. et al. Reconstruction of large complex sand-wave bathymetry with adaptive partitioning combining satellite imagery and sparse multi-beam data. J. Ocean. Limnol. 40, 1924–1936 (2022). https://doi.org/10.1007/s00343-021-1216-5
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DOI: https://doi.org/10.1007/s00343-021-1216-5