Digital bathymetric model fusion of offshore waters around China’s coastline based on global bathymetry data

Ruan Xiaoguang; Zhan Zhaojie; Yan Zhaojin; Tan Qiuying; Guo Meijing; Yang Yang

doi:10.12284/hyxb2024062

Volume 46 Issue 7

Jul. 2024

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Ruan Xiaoguang，Zhan Zhaojie，Yan Zhaojin, et al. Digital bathymetric model fusion of offshore waters around China’s coastline based on global bathymetry data[J]. Haiyang Xuebao，2024, 46(7)：16–28 doi: 10.12284/hyxb2024062

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Digital bathymetric model fusion of offshore waters around China’s coastline based on global bathymetry data

doi: 10.12284/hyxb2024062

1.
College of Geomatics, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
2.
Nanxun Innovation Institute, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
3.
School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China
4.
Zhejiang Highway Technicians College, Hangzhou 311300, China
5.
The Academy of Digital China, Fuzhou University, Fuzhou 350108, China

Received Date: 2023-07-14
Accepted Date: 2024-08-12
Rev Recd Date: 2024-01-24

Available Online: 2024-08-15

Publish Date: 2024-07-01

Abstract

Abstract

Digital bathymetric models (DBMs) are important basic geographic information data in the fields of offshore engineering construction, resource development, environmental protection and so on. The existing global public DBMs products such as GEBCO (The General Bathymetric Chart of the Oceans), SRTM (The Shuttle Radar Topography Mission) and ETOPO (Earth Topography) have different data types, data sources and product accuracy in different sea areas. In order to reconstruct China’s offshore bathymetric model using global bathymetric data and DBMs products, this paper proposed a weighted fusion reconstruction framework based on bathymetric partition. Firstly, the reliability and applicability of six commonly used DBMs products (GEBCO_2022, SRTM30_PLUS, SRTM15_V2.5.5, TOPO_25.1, DTU10, ETOPO_2022) were compared and analyzed in five dimensions (overall accuracy, different water depths, route profiles, geographical partitions, local details). Then, considering the bathymetric and topographic characteristics, the study area was segmented and partitioned, and the optimal DBMs products in the partition were selected, and the optimal weighted fusion was carried out with the minimum error as the constraint. Finally, the fusion results were processed by measured value recovery, smooth filtering and other post-processing to form a high-precision seamless bathymetric model with 15" resolution in offshore waters around China’s coastline. The results showed that the RMSE of the fusion results was reduced by 27%, 14%, 14% and 13% compared with SRTM30_PLUS, GEBCO_2022, SRTM15_V2.5.5 and ETOPO_2022, and the details of the topograhy were also retained. The feasibility of the fusion framework was proved, which could provide a reference for the fusion reconstruction and timely updating of large-scale seabed topography from multiple datasets.
- digital bathymetric model,
- multi-source data fusion,
- bathymetry,
- seabed topography,
- China’s coastline

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References

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