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联合重力异常和重力垂直梯度异常数据反演皇帝山海域海底地形

阳凡林 沈瑞杰 梅赛 屠泽杰 辛明真

阳凡林,沈瑞杰,梅赛,等. 联合重力异常和重力垂直梯度异常数据反演皇帝山海域海底地形[J]. 海洋学报,2022,44(12):126–135 doi: 10.12284/hyxb2022145
引用本文: 阳凡林,沈瑞杰,梅赛,等. 联合重力异常和重力垂直梯度异常数据反演皇帝山海域海底地形[J]. 海洋学报,2022,44(12):126–135 doi: 10.12284/hyxb2022145
Yang Fanlin,Shen Ruijie,Mei Sai, et al. Inversion of seafloor topography in Emperor Seamount sea area by combined gravity anomalies and vertical gravity gradient anomalies data[J]. Haiyang Xuebao,2022, 44(12):126–135 doi: 10.12284/hyxb2022145
Citation: Yang Fanlin,Shen Ruijie,Mei Sai, et al. Inversion of seafloor topography in Emperor Seamount sea area by combined gravity anomalies and vertical gravity gradient anomalies data[J]. Haiyang Xuebao,2022, 44(12):126–135 doi: 10.12284/hyxb2022145

联合重力异常和重力垂直梯度异常数据反演皇帝山海域海底地形

doi: 10.12284/hyxb2022145
基金项目: 国家自然科学基金重点项目(41930535);高端外国专家引进计划(G2021025006L);山东省研究生教育创新计划建设项目(SDYJG19083)
详细信息
    作者简介:

    阳凡林(1974-),男,湖北省荆州市人,教授,主要从事海底地形测量和海洋定位导航方面的研究工作。E-mail:flyang@sdust.edu.cn

    通讯作者:

    梅赛(1985-),男,副研究员,从事海洋地质调查与研究工作。E-mail:meisai2000@163.com

  • 中图分类号: P229.1;P714.7

Inversion of seafloor topography in Emperor Seamount sea area by combined gravity anomalies and vertical gravity gradient anomalies data

  • 摘要: 海底地形对开展海洋科学调查和研究十分重要。以多波束为主的回声测深技术测量成本高且效率低,几十年来仅实现了全球约20%的海床测绘。对于空白区(特别是深海区域),可以借助重力异常和重力垂直梯度异常进行回归分析反演得到,但该方法得到的比例因子鲁棒性不强。为了解决这一问题,同时考虑到两种重力数据在表征海底地形长短波长的不同优势,本文结合滑动窗口赋权和稳健回归分析来反演海底地形。在太平洋皇帝山海域(35°~45°N,165°~175°E)的实验结果表明:在船测检核点处,本文构建模型的标准差为61.02 m,相比于单一重力数据反演模型,精度分别提高了14.92%(重力异常)和2.08%(重力垂直梯度异常),能较好地反映皇帝海山链的地形走势。
  • 图  1  研究区域与船载测深轨迹分布

    Fig.  1  Study area and shipborne bathymetry trace distribution map

    图  2  重力模型示意图

    Fig.  2  Gravimetric model diagram

    图  3  重力数据与海底地形的相干性

    Fig.  3  Coherence between gravimetric data and seafloor topography

    图  4  反演波段重力数据与残余海深线性拟合结果

    Fig.  4  Results of linear fitting between gravity data of inversion band and residual sea depth

    图  5  重力垂直梯度异常模型权值xi分配示意图,相应的,重力异常模型的权值分配为1−xi

    Fig.  5  The schematic diagram of weight distribution xi of vertical gravity gradient anomalies model. Accordingly, the weight distribution of gravity anomalies model is 1−xi

    图  6  海底地形反演流程

    Fig.  6  Flowchart of seafloor topography inversion

    图  7  MGM海底地形模型

    Fig.  7  The seafloor topography model of multiple gravity model

    图  8  MGM差值分布图

    Fig.  8  Difference distribution diagram of multiple gravity model

    图  9  检核点处差值结果统计直方图

    Fig.  9  Statistical histogram of the difference results at the check point

    图  10  异常点空间位置分布图(黑色圆点代表异常点位)

    Fig.  10  Spatial distribution map of outliers (black dots represent outliers)

    图  11  皇帝海山链地形剖面图

    Fig.  11  The topographic profile of the Emperor Seamount Chain

    表  1  海底地形模型与多波束数据差值统计结果

    Tab.  1  Difference statistics of seafloor topographic model with multibeam data

    模型平均值/m标准差/m相关系数
    SGA166.54462.980.948 3
    SVG128.76402.270.956 1
    MGM_LS159.01421.550.949 7
    MGM139.09393.890.961 1
    下载: 导出CSV

    表  2  海底地形模型在检核点处差值统计结果

    Tab.  2  Difference statistics of seafloor topographic model at check point

    模型最大值/m最小值/m平均值/m标准差/m相关系数
    MGM942.65–895.090.6461.020.998 0
    DTU181 560.311 110.947.7495.410.996 6
    V23.11 697.412 148.3310.4695.520.996 6
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-04-19
  • 修回日期:  2022-06-07
  • 网络出版日期:  2022-08-26
  • 刊出日期:  2023-01-17

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