Fusion method for water depth data from multiple sources based on image recognition

Huiyu HAN; Feng ZHOU

doi:10.1007/s00343-024-4009-9

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Fusion method for water depth data from multiple sources based on image recognition

Physics | Updated：2025-08-07

- Fusion method for water depth data from multiple sources based on image recognition
- Journal of Oceanology and Limnology Vol. 43, Issue 4, Pages: 1093-1105(2025)
- Affiliations：
  
  1.School of Oceanography, Shanghai Jiao Tong University, Shanghai 200240, China
  2.State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
- Author bio：
  
  zhoufeng@sio.org.cn
- Funds：
- DOI：10.1007/s00343-024-4009-9
  CLC：
- Received：05 January 2024，
  
  Published：01 July 2025
- Accepted：
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HAN Huiyu,ZHOU Feng.Fusion method for water depth data from multiple sources based on image recognition[J].Journal of Oceanology and Limnology,2025,43(04):1093-1105.
DOI：

HAN Huiyu,ZHOU Feng.Fusion method for water depth data from multiple sources based on image recognition[J].Journal of Oceanology and Limnology,2025,43(04):1093-1105. DOI： 10.1007/s00343-024-4009-9.

摘要

Abstract

Considering the difficulty of integrating the depth points of nautical charts of the East China Sea into a global high-precision Grid Digital Elevation Model (Grid-DEM)

we proposed a “Fusion based on Image Recognition (FIR)” method for multi-sourced depth data fusion

and used it to merge the electronic nautical chart dataset (referred to as Chart2014 in this paper) with the global digital elevation dataset (referred to as Globalbath2002 in this paper). Compared to the traditional fusion of two datasets by direct combination and interpolation

the new Grid-DEM formed by FIR can better represent the data characteristics of Chart2014

reduce the calculation difficul

and be more intuitive

and

the choice of different interpolation methods in FIR and the influence of the “exclusion radius

” parameter were discussed. FIR avoids complex calculations of spatial distances among points from different sources

and instead uses spatial exclusion map to perform one-step screening based on the exclusion radius

which greatly improved the fusion status of a reliable dataset. The fusion results of different experiments were analyzed statistically with root mean square error and mean relative error

showing that the interpolation methods based on Delaunay triangulation are more suitable for the fusion of nautical chart depth of China

and factors such as the point density distribution of multiple source data

accuracy

interpolation method

and various terrain conditions should be fully considered when selecting the exclusion radius

关键词

Keywords

references

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