In this paper, the bottom sediment classification method by using high precision multibeam bathymetric data is discussed.
探讨了基于高精度多波束水深数据的底质分类方法。
Hydrographic and bathymetric data have been applied to review the dynamic regime and morphological evolution in recent years in the sandbar area of the Modaomen estuary.
应用近几年的水文和地形实测资料，研究了磨刀门拦门沙区域近期的动力和地貌演变特点。
The proposed method organized bathymetric data utilizing grid block structure, interpolated depth at grid node adopting three mathematical models and thinned data with multi-scale grid.
利用格网分块结构高效组织海量多波束水深数据，分别采用三种数学模型内插网格节点水深值，实现了不同网格尺度下的数据抽稀。
Bathymetric (or sea floor terrain) data is often collected from boats using sonar to take measurements of the sea floor. The lines reflect the path of the boat as it gathers the data.
水深(或海底地形)的数据往往是在船只上使用声纳测量海底采集的。
Automatic interpolation of charted depth annotated point, automatic selection of Marine topography feature point and automatic build of bathymetric contour come true by using history data.
利用历史资料实现了海域水深注记点的自动内插、海底地形特征点的自动选取和等深线的自动生成。
In order to obtain the data of depth precisely and accurately, it is important to improve the performance and accuracy of the multi-beam bathymetric algorithms.
为了得到精细而准确的海底深度数据，提高多波束测深算法的精度和性能就显得十分关键。
In order to obtain the data of depth precisely and accurately, it is important to improve the performance and accuracy of the multi-beam bathymetric algorithms.
为了得到精细而准确的海底深度数据，提高多波束测深算法的精度和性能就显得十分关键。
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