Shallow water bathymetry using remote sensing based on spectral stratification

Chu Sensen; Cheng Liang; Cheng Jian; Zhang Xuedong; Liu Jinming

doi:10.12284/hyxb2023024

Volume 45 Issue 1

Jan. 2023

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Chu Sensen，Cheng Liang，Cheng Jian, et al. Shallow water bathymetry using remote sensing based on spectral stratification[J]. Haiyang Xuebao，2023, 45(1)：125–137 doi: 10.12284/hyxb2023024

Citation:

Chu Sensen，Cheng Liang，Cheng Jian, et al. Shallow water bathymetry using remote sensing based on spectral stratification[J]. Haiyang Xuebao，2023, 45(1)：125–137 doi: 10.12284/hyxb2023024

Citation:

Chu Sensen，Cheng Liang，Cheng Jian, et al. Shallow water bathymetry using remote sensing based on spectral stratification[J]. Haiyang Xuebao，2023, 45(1)：125–137 doi: 10.12284/hyxb2023024

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Shallow water bathymetry using remote sensing based on spectral stratification

doi: 10.12284/hyxb2023024

Chu Sensen^{1, 2, 3
,},
Cheng Liang^{1, 2, 3, 4
,
,},
Cheng Jian¹,
Zhang Xuedong¹,
Liu Jinming^{5
,
,}

1.
School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
2.
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210023, China
3.
Collaborative Innovation Center for the South Sea Studies, Nanjing 210023, China
4.
Key Laboratory for Land Satellite Remote Sensing Applications, Ministry of Natural Resources, Nanjing 210023, China
5.
Defense Engineering Institute Academy of Military Sciences, Beijing 100036, China

Received Date: 2022-05-04
Rev Recd Date: 2022-09-07

Available Online: 2022-09-22

Publish Date: 2023-01-09

Abstract

Abstract

Shallow water bathymetry using remote sensing is an important technology in marine geodesy. The Stumpf ratio and Lyzenga polynomial methods, as classic representative algorithms, are widely used and many improved algorithms have been developed. However, these methods do not take into account the bathymetry ability of different spectra. In this study, we propose a bathymetry method based on spectral stratification. Firstly, according to the difference in the penetration ability of red, green and blue spectra to the waterbody, an image-based nonparametric spectral layering strategy is proposed to extract the red, green and blue layers. Then, based on the band bathymetric performance of different spectral layers, we constructed a bathymetric inversion optimization model by spectral layers and further obtained the shallow water bathymetry. The Changxian Reef in the Nansha sea area and Buck Island Reef in U.S. Virgin Islands are selected as test cases to validate the proposed method. Compared with the classical Stumpf ratio and Lyzenga polynomial methods, the root-mean-square error (RMSE), mean absolute error (MAE) and mean relative error (MRE) of the proposed method have decreased by 0.41−0.89 m, 0.35−0.65 m, and 4%−19% respectively. Particularly, the accuracy of the red light layer (i.e., the shallow water depth) is significantly improved, and the MRE is reduced by 58%−149%. Our findings suggest that the proposed bathymetry method based on spectral stratification is feasible and effective in improving the accuracy of the shallow water depth estimation and has good potential for future applications.
- multispectral,
- shallow water,
- water depth retrieval,
- Sentinel-2,
- Stumpf method,
- Lyzenga method,
- multispectral bathymetry

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References(43)

References

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