Scholarlink

In this paper, the high-resolution topographic dataset in a typical area of Arctic ocean is formed by fusion calculation of multi-source datasets including publicly available seabed terrain data, single/multi-beam bathymetric data and electronic chart bathymetric data. We solve the problem of large computational volume of data fusion of massive measurement points by expanding the solution scale through the method of partitioned parallel computing. The seabed terrain data fusion with different sources and resolutions are completed based on the “remove-restore” method. On this basis, the Split-Sample method is used to evaluate the fusion accuracy. The results show that the average absolute error of the gridded fusion data with 10 m spatial resolution is 23.0 m, and the depth discrepancy ratio is only 1.2%.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Study on the Multi-source Variable Resolution Data Fusion of Seabed Terrain in Typical Area of Arctic Ocean

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Xun Gong,
  • Qingzhe Wang,
  • Chong Zhang,
  • Houyu Zhou,
  • Wei An

摘要

In this paper, the high-resolution topographic dataset in a typical area of Arctic ocean is formed by fusion calculation of multi-source datasets including publicly available seabed terrain data, single/multi-beam bathymetric data and electronic chart bathymetric data. We solve the problem of large computational volume of data fusion of massive measurement points by expanding the solution scale through the method of partitioned parallel computing. The seabed terrain data fusion with different sources and resolutions are completed based on the “remove-restore” method. On this basis, the Split-Sample method is used to evaluate the fusion accuracy. The results show that the average absolute error of the gridded fusion data with 10 m spatial resolution is 23.0 m, and the depth discrepancy ratio is only 1.2%.