

FOLLOWUS
1.State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
2.Key Laboratory of Submarine Geosciences, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
3.School of Oceanography, Shanghai Jiao Tong University, Shanghai 200240, China
Huaguo ZHANG,zhanghg@sio.org.cn
Ziyin WU,zywu@vip.163.com
收稿:2021-07-05,
录用:2021-8-31,
网络首发:2021-10-28,
纸质出版:2022-09
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Reconstruction of large complex sand-wave bathymetry with adaptive partitioning combining satellite imagery and sparse multi-beam data[J]. 海洋湖沼学报(英文), 2022,40(5):1924-1936.
Huaguo ZHANG, Juan WANG, Dongling LI, et al. Reconstruction of large complex sand-wave bathymetry with adaptive partitioning combining satellite imagery and sparse multi-beam data[J]. Journal of Oceanology and Limnology, 2022, 40(5): 1924-1936.
Reconstruction of large complex sand-wave bathymetry with adaptive partitioning combining satellite imagery and sparse multi-beam data[J]. 海洋湖沼学报(英文), 2022,40(5):1924-1936. DOI: 10.1007/s00343-021-1216-5.
Huaguo ZHANG, Juan WANG, Dongling LI, et al. Reconstruction of large complex sand-wave bathymetry with adaptive partitioning combining satellite imagery and sparse multi-beam data[J]. Journal of Oceanology and Limnology, 2022, 40(5): 1924-1936. DOI: 10.1007/s00343-021-1216-5.
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 km
2
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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