JIA Shuaidong, ZHANG Lihua, DONG Jian, PENG Rencan. A Method for Constructing DDM Serving for Navigation Using Pre-constructed Model Surface to Control and Adjust the Selection of DDM Nodes[J]. Geomatics and Information Science of Wuhan University, 2019, 44(11): 1715-1722. DOI: 10.13203/j.whugis20180087
Citation: JIA Shuaidong, ZHANG Lihua, DONG Jian, PENG Rencan. A Method for Constructing DDM Serving for Navigation Using Pre-constructed Model Surface to Control and Adjust the Selection of DDM Nodes[J]. Geomatics and Information Science of Wuhan University, 2019, 44(11): 1715-1722. DOI: 10.13203/j.whugis20180087

A Method for Constructing DDM Serving for Navigation Using Pre-constructed Model Surface to Control and Adjust the Selection of DDM Nodes

Funds: 

The National Natural Science Foundation of China 41901320

The National Natural Science Foundation of China 41871369

The National Natural Science Foundation of China 41601498

The National Natural Science Foundation of China 41774014

More Information
  • Author Bio:

    JIA Shuaidong, PhD, lecturer, specializes in process and application of hydrographic data. E-mail:sky_jsd@163.com

  • Corresponding author:

    ZHANG Lihua, PhD, professor. E-mail:zlhua@163.com

  • Received Date: July 19, 2018
  • Published Date: November 04, 2019
  • Aiming at the drawbacks of the traditional methods which cannot make the constructed depth models meet the requirement of navigational safety, a method for constructing digital depth model(DDM) serving for navigation using pre-constructed model surface to control and adjust the selection of DDM nodes is proposed. Firstly, the selected depths, the alternative depths, the candidate depth and the pre-constructed model surface are defined. Secondly, the probability and the representativeness of DDM are calculated quantitatively by using the alternative depths so that the model quality can be estimated dynamically in the process of the depth modeling. Finally, the operator for selecting depths is designed and utilized for controlling and adjusting the selection of the depths quantitatively, thus the models are constructed of which the probability of an adequate depth meets the requirement of the navigational safety. The experimental results demonstrate that:(1) compared with the traditional method, the proposed method can make the probability of the depth model meet the requirement of navigational safety; (2) for the depths of which the assuring rate meet the requirement of the navigational safety, the representativeness of the depth model constructed with the proposed method is higher than that of the traditional method.
  • [1]
    董箭, 彭认灿, 郑义东.利用局部动态最优Delaunay三角网改进逐点内插算法[J].武汉大学学报·信息科学版, 2013, 38(5): 613-617 http://ch.whu.edu.cn/CN/abstract/abstract2648.shtml

    Dong Jian, Peng Rencan, Zheng Yidong. An Inproved Algorithm of Point-by-Point Interpolation by Using Local Dynamic Optimal Delaunay Triangulation Network[J]. Geomatics and Information Science of Wuhan University, 2013, 38(5): 613-617 http://ch.whu.edu.cn/CN/abstract/abstract2648.shtml
    [2]
    Jakobsson M. International Bathymetric Chart of the Arctic Ocean (IBCAO)[EB/OL]. https://link.springer.(com/content/pdf/10.1007%2F978-94-007-6644-0_68-2.pdf), 2018
    [3]
    Weatherall P, Marks K M, Jakobsson M, et al. A New Digital Bathmetric Model of the World's Oceans[J]. Earth and Space Science, 2015, 2(8): 331-345 doi: 10.1002/2015EA000107
    [4]
    邹永刚, 翟京生, 刘雁春, 等.利用不确定度的海底数字高程模型构建[J].武汉大学学报·信息科学版, 2011, 36(8): 964-968 http://ch.whu.edu.cn/CN/abstract/abstract627.shtml

    Zou Yonggang, Zhai Jingsheng, Liu Yanchun, et al. Seabed DEM Construction Based on Uncertainty[J]. Geomatics and Information Science of Wuhan University, 2011, 36(8): 964-968 http://ch.whu.edu.cn/CN/abstract/abstract627.shtml
    [5]
    张立华, 贾帅东, 王涛, 等.深度保证率和表达度指标的定义及评估方法[J].武汉大学学报∙信息科学版, 2015, 40(5): 695-700 http://d.old.wanfangdata.com.cn/Periodical/whchkjdxxb201505023

    Zhang Lihua, Jia Shuaidong, Wang Tao, et al. Definitions and Estimating Methods of a Probability of an Adequate Depth and Representativeness [J]. Geomatics and Information Science of Wuhan University, 2015, 40(5): 695-700 http://d.old.wanfangdata.com.cn/Periodical/whchkjdxxb201505023
    [6]
    贾帅东, 张立华, 彭认灿, 等.确保水深模型航海安全性的深度保证率控制方法[J].交通运输工程学报, 2015, 15(5): 101-109 doi: 10.3969/j.issn.1671-1637.2015.05.013

    Jia Shuaidong, Zhang Lihua, Peng Rencan, et al. A Method to Control the Probability of Adequate Depth for Ensuring the Navigational Safety of Depth Model[J]. Journal of Traffic and Transportation Engineering, 2015, 15(5): 101-109 doi: 10.3969/j.issn.1671-1637.2015.05.013
    [7]
    Smith S. The Navigation Surface: A Multipurpose Bathymetric Database[D]. New Hampshire: University of New Hampshire, 2003
    [8]
    张立华, 李改肖, 郑义东, 等.海图制图综合[M].北京:国防工业出版社, 2017

    Zhang Lihua, Li Gaixiao, Zheng Yidong, et al. Chart Cartographic Generalization[M]. Beijing: National Defense Industry Press, 2017
    [9]
    海军出版社. GB12320-1998中国航海图编绘规范[S].北京: 中国标准出版社, 1999

    Navy Press. GB12320-1998. Specifications for Chinese Nautical Charts[S]. Beijing: Chinese Standards Press, 1999
    [10]
    王沫, 张立华, 于彩霞, 等.一种基于水深点坡向关系的特征浅点提取方法[J].武汉大学学报∙信息科学版, 2016, 41(2): 208-213 http://d.old.wanfangdata.com.cn/Periodical/whchkjdxxb201602011

    Wang Mo, Zhang Lihua, Yu Caixia, et al. Distilling Feature Shallow Points from Soundings Based on the Slope-Relationship[J]. Geomatics and Information Science of Wuhan University, 2016, 41(2): 208-213 http://d.old.wanfangdata.com.cn/Periodical/whchkjdxxb201602011
    [11]
    Amante C. Accuracy of Interpolated Bathymetric Digital Elevation Models[D]. Colorado: University of Colorado, 2012
    [12]
    de Wulf A, Constales D, Stal C, et al. Accuracy Ascpects of Processing and Filtering of Multibeam Data: Grid Modeling Versus TIN Based Modeling[C]. FIG Working Week, Rome, Italy, 2012
    [13]
    王鹤荀, 郭洪驹.船舶安全富余水深的确定[J].上海海事大学学报, 2004, 25(4): 19-21 doi: 10.3969/j.issn.1672-9498.2004.04.006

    Wang Hexun, Guo Hongju. Determination of Ship?s Safe UKC[J]. Journal of Shanghai Maritime University, 2004, 25(4): 19-21 doi: 10.3969/j.issn.1672-9498.2004.04.006
    [14]
    张立华, 贾帅东, 元建胜, 等.一种基于不确定度的水深控浅方法[J].测绘学报, 2012, 41(2): 184-190 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=chxb201202006

    Zhang Lihua, Jia Shuaidong, Yuan Jiansheng, et al. A Method for Controlling Shoal-Biased Based on Uncertainty[J]. Acta Geodaetica et Cartographica Sinica, 2012, 41(2): 184-190 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=chxb201202006
    [15]
    British Crown and Sea Zone Solutions Ltd. Comparison of Surveyed and Charted Bathymetry [R]. Seabed Data Center, Taunton, British, 2007
    [16]
    曹鸿博, 张立华, 陈跃, 等.海底DEM精度分析[C].全国第二十二届海洋测绘综合性学术研讨会, 太原, 中国, 2010

    Cao Hongbo, Zhang Lihua, Chen Yue, et al. A Precision Analysis of Seabed DEM[C]. Hydrographic Surveying and Charting Symposium of the 29th General Meeting, Taiyuan, China, 2010
    [17]
    张立华.基于电子海图的航线自动生成理论与方法[M].北京:科学出版社, 2011

    Zhang Lihua. The Theories and Methods for Automatically Generating Routes Based on Electronic Chart[M]. Beijing: Science Press, 2011
    [18]
    Ari I, Aksakalli V, Aydogdu V, et al. Optimal Ship Navigation with Safety Distance and Realistic Turn Constraints[J]. European Journal of Operational Research, 2013, 229(3): 707-717 doi: 10.1016/j.ejor.2013.03.022
    [19]
    International Hydrographic Orgnization. S-44 IHO Standards for Hydrographic Surveys[S].5th ed. Monaco: International Hydrographic Bureau, 2008
    [20]
    贾帅东.航海DDM的构建理论与方法[D].大连: 海军大连舰艇学院, 2015

    Jia Shuaidong. The Theories and Methods for Constructing DDM Serving for Navigation [D]. Dalian: Dalian Naval Academy, 2015
  • Related Articles

    [1]WU Jiaqi, JIANG Yonghua, SHEN Xin, LI Beibei, PAN Shenlin. Satellite Video Motion Detection Supported by Decision Tree Weak Classification[J]. Geomatics and Information Science of Wuhan University, 2019, 44(8): 1182-1190. DOI: 10.13203/j.whugis20180094
    [2]FU Zisheng, LI Qiuping, LIU Lin, ZHOU Suhong. Identification of Urban Network Congested Segments Using GPS Trajectories Double-Clustering Method[J]. Geomatics and Information Science of Wuhan University, 2017, 42(9): 1264-1270. DOI: 10.13203/j.whugis20150036
    [3]DENG Min, CHEN Ti, YANG Wentao. A New Method of Modeling Spatio-temporal Sequence by Considering Spatial Scale Characteristics[J]. Geomatics and Information Science of Wuhan University, 2015, 40(12): 1625-1632. DOI: 10.13203/j.whugis20130842
    [4]FU Zhongliang, LIU Siyuan. MR-tree with Voronoi Diagrams for Parallel Spatial Queries[J]. Geomatics and Information Science of Wuhan University, 2012, 37(12): 1490-1494.
    [5]HE Chu, LIU Ming, XU Lianyu, LIU Longzhu. A Hierarchical Classification Method Based on Feature Selection and Adaptive Decision Tree for SAR Image[J]. Geomatics and Information Science of Wuhan University, 2012, 37(1): 46-49.
    [6]ZHANG Lu, GAO Zhihong, LIAO Mingsheng, LI Xinyan. Estimating Urban Impervious Surface Percentage with Multi-source Remote Sensing Data[J]. Geomatics and Information Science of Wuhan University, 2010, 35(10): 1212-1216.
    [7]HAN Tao, XU Xiaotao, XIE Yaowen. Automated Construction and Classification of Decision Tree Classifier Based on Single-Temporal MODIS Data[J]. Geomatics and Information Science of Wuhan University, 2009, 34(2): 191-194.
    [8]LIAO Mingsheng, JIANG Liming, LIN Hui, YANG Limin. Estimating Urban Impervious Surface Percent Using Boosting as a Refinement of CART Analysis[J]. Geomatics and Information Science of Wuhan University, 2007, 32(12): 1099-1102.
    [9]YU Xin, ZHENG Zhaobao, YE Zhiwei, TIAN Liqiao. Texture Classification Based on Tree Augmented Naive Bayes Classifier[J]. Geomatics and Information Science of Wuhan University, 2007, 32(4): 287-289.
    [10]GUO Jing, LIU Guangjun, DONG Xurong, GUO Lei. 2-Level R-tree Spatial Index Based on Spatial Grids and Hilbert R-tree[J]. Geomatics and Information Science of Wuhan University, 2005, 30(12): 1084-1088.
  • Cited by

    Periodical cited type(13)

    1. 陈月,王磊,池深深,王羽,戚鑫鑫,朱尚军. 基于SBAS-InSAR和CNN-GRU模型的采动村庄地表沉降监测预计. 金属矿山. 2025(02): 138-144 .
    2. 何毅,姚圣,陈毅,闫浩文,张立峰. ConvLSTM神经网络的时序InSAR地面沉降时空预测. 武汉大学学报(信息科学版). 2025(03): 483-496 .
    3. 倪尔瑞,张建新,邱明剑,权力奥,朱晓峻. 基于SBAS-InSAR技术的淮北市地表沉降监测分析. 北京测绘. 2024(03): 312-317 .
    4. 吴启琛,于瑞鹏,王丽,赵乙泽,范开放. 利用Sentinel-1的山东枣庄高新区地面沉降监测与分析. 地理空间信息. 2024(06): 80-83 .
    5. 杨芳,丁仁军,李勇发. 基于SBAS-InSAR技术的金沙江流域典型滑坡时空演化特征分析. 测绘通报. 2024(11): 102-107 .
    6. 祝杰,李瑜,师宏波,刘洋洋,韩宇飞,邵银星,王坦. 鹤岗煤矿区地面沉降时空特征InSAR时间序列监测研究. 中国地震. 2023(03): 596-608 .
    7. 柴龙飞,魏路,张震. 基于SBAS-InSAR的安徽省宿州市埇桥区2019—2022年地面沉降监测及影响因素分析研究. 安徽地质. 2023(04): 348-352 .
    8. 祝杰,韩宇飞,王坦,李瑜,王阅兵,师宏波,刘洋洋,樊俊屹,邵银星. 2017年九寨沟M_S7.0地震同震地表三维形变场解算研究. 中国地震. 2022(02): 348-359 .
    9. 吴毅彬,葛红斌,刘光庆,刘海旺. 基于MT-InSAR技术的厦门新机场填海区沉降监测. 工程勘察. 2021(02): 57-61 .
    10. 翟振起. 基于InSAR沉降监测技术的城市供水管线安全监测系统开发. 水利科学与寒区工程. 2021(01): 103-106 .
    11. 廖明生,王茹,杨梦诗,王楠,秦晓琼,杨天亮. 城市目标动态监测中的时序InSAR分析方法及应用. 雷达学报. 2020(03): 409-424 .
    12. 熊寻安,王明洲,龚春龙. MT-InSAR技术监测水库土石坝表面变形研究. 测绘地理信息. 2019(05): 78-81 .
    13. 王茹,杨天亮,杨梦诗,廖明生,林金鑫,张路. PS-InSAR技术对上海高架路的沉降监测与归因分析. 武汉大学学报(信息科学版). 2018(12): 2050-2057 .

    Other cited types(4)

Catalog

    Article views PDF downloads Cited by(17)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return