台湾浅滩多尺度沙波地貌的地形傅里叶分解

朱超; 吴自银; 周洁琼; 阳凡林; 赵荻能; 刘洋; 鲁号号

doi:10.3969/j.issn.0253-4193.2019.09.013

台湾浅滩多尺度沙波地貌的地形傅里叶分解

doi: 10.3969/j.issn.0253-4193.2019.09.013

朱超^{1, 2, 3, 4,},
吴自银^{2, 3, 4, 5, ,},
周洁琼^{2, 3, 5},
阳凡林¹,
赵荻能^{2, 3},
刘洋^{2, 3},
鲁号号^{2, 3, 6}

1.
山东科技大学测绘科学与工程学院，山东青岛 266590
2.
自然资源部第二海洋研究所，浙江杭州 310012
3.
国家海洋局海底科学重点实验室，浙江杭州 310012
4.
浙江大学海洋学院，浙江舟山 316021
5.
浙江大学地球科学学院，浙江杭州 310027
6.
南京大学地理与海洋科学学院，江苏南京 210023

基金项目: 国家自然科学基金（41830540，41476049）；公益性科研院所基本科研业务费专项资金重点项目（JZ1902）；卫星海洋环境动力学国家重点实验室自主项目（SOEDZZ1802）；科技基础性工作专项（2013FY112900）；全球变化与海气相互作用专项（GASI-EOGE-01）。

详细信息

作者简介:
朱超（1991—），男，山东省济南市人，主要从事多波束海底地形地貌及海洋地球物理勘测研究。E-mail：chaozhu1114@163.com

通讯作者:
吴自银（1972—），男，河南省光山县人，研究员，研究方向为多波束海底地形地貌探测与研究。E-mail：zywu@vip.163.com

中图分类号: P737.2
计量
- 文章访问数: 482
- HTML全文浏览量: 57
- PDF下载量: 250
- 被引次数: 3
出版历程
- 收稿日期: 2018-10-29
- 修回日期: 2019-03-18
- 网络出版日期: 2021-04-21
- 刊出日期: 2019-09-25

Fourier decomposition of multi-scale sand wave fields on the Taiwan Banks

Zhu Chao^{1, 2, 3, 4
,},
Wu Ziyin^{2, 3, 4, 5
, ,},
Zhou Jieqiong^{2, 3, 5},
Yang Fanlin¹,
Zhao Dineng^{2, 3},
Liu Yang^{2, 3},
Lu Haohao^{2, 3, 6}

1.
College of Geomrtics, Shandong University of Science and Technology, Qingdao 266590, China
2.
Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
3.
Key Laboratory of the Submarine Geosciences, State Oceanic Administration, Hangzhou 310012, China
4.
Ocean College, Zhejiang University, Zhoushan 316021, China
5.
School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
6.
School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

摘要

摘要: 海底沙波在全球广泛分布、成因复杂，但往往多种尺度的沙波叠加在一起形成复杂的沙波地貌体系，导致难以进行量化研究。针对该问题，本文提出一种实用的傅里叶分析方法，设计了巴特沃斯滤波器，将水深数据变换到频率域，进而将复杂沙波地貌分解成不同频率的单一类型沙波。并以台湾浅滩复杂的沙波地貌体系为例进行了分析研究，分解量化出3种空间尺度的沙波：巨型沙波(波长>100 m，波高>5 m)、中型沙波(波长5～100 m，波高0.4～5 m)和沙波纹(波长<5 m，波高<0.4 m)。本文提出的海底沙波地貌量化分析方法，有助于研究不同尺度海底沙波的成因与机理，对沙波区海洋工程的安全评估也具有实用价值。
- 海底沙波 /
- 傅里叶分析 /
- 多尺度分解 /
- 台湾浅滩 /
- 多波束测深
Abstract: Sand waves are widely distributed in the world and have complex genesis. And multi-scale complex sand waves often overlap to form a complex sand wave geomorphology system, which makes it difficult to conduct quantitative research. To solve this problem, a practical Fourier analysis method is proposed in this paper, and Butterworth filter is designed to transform water depth data into frequency domain, and then decompose complex sand wave geomorphology into a series of single types of sand waves in different frequencies. Taking the complex sand wave geomorphology system of Taiwan Banks as an example, three spatial scales of sand waves are quantitatively decomposed, which are: giant sand waves (over 100 m in length, over 5 m in height), medium sand waves (wavelength of 5–100 m, wave height of 0.4–5 m) and sand ripples (wavelength less than 5 m, wave height less than 0.4 m). The quantitative analysis method of sand waves proposed in this paper is helpful to study the genesis and mechanism of sand waves in different scales, and is also of practical value to the safety assessment of marine engineering in sand wave fields.
- submarine sand waves /
- Fourier analysis /
- multi-scale decomposition /
- Taiwan Banks /
- multi-beam echo sounding

HTML全文

图 1 实验区平面地形图（a）和A–B水深剖面（b）

Fig. 1 Bathymetric map of the experimental area (a), and water depth of Profile A–B (b)

下载: 全尺寸图片幻灯片

图 2 研究区沙波几何参数定义

水深的极大值点C表示波峰点，极小值点T代表波谷点，C和T之间的垂向高差H表示波高，相邻两个T之间的水平距离L为波长

Fig. 2 Characterized parameters of sand waves

Point C represents crest, T represents crest trough, H is wave height and L is wave length

下载: 全尺寸图片幻灯片

图 3 方法流程图

Fig. 3 Workflow of the Fourier decomposition method

下载: 全尺寸图片幻灯片

图 4 傅里叶变换的频谱图

红色部分代表低频，蓝色部分代表中频，黑色部分代表高频

Fig. 4 Spectral plot by Fourier transform

The red part represents the low frequency, blue part represents the medium frequency, and black part represents the high frequency

下载: 全尺寸图片幻灯片

图 5 傅里叶变换各个频率累加效果图

图中展示了复合沙波地貌的3种主要组成：巨型沙波、中型沙波和沙波纹，图6是3种沙波分离的结果

Fig. 5 Cumulative constituents of the Fourier analysis

The figure showing three groups of constituents that each represent a bedform type: giant sand waves, small sand waves, and megaripples, Fig. 6 is the separation results of sand waves

下载: 全尺寸图片幻灯片

图 6 一维傅里叶变换分离结果

a.低频沙波信号；b.中频沙波信号；c.高频沙波信号

Fig. 6 1-D separation results of the Fourier analysis

a. The separated low frequency sand wave signals；b. the intermediate frequency sand wave signals; c. the residual high frequency sand wave signals

下载: 全尺寸图片幻灯片

图 7 二维傅里叶变换分离结果

a.低频沙波信号；b.中频沙波信号；c.高频沙波信号

Fig. 7 2-D separation results of the Fourier analysis

a. The low frequency sand wave signals；b. the medium frequency sand wave signals; c. the high frequency sand wave signals

下载: 全尺寸图片幻灯片

图 8 分离的3个尺度与原始水深的对比

Fig. 8 Separation results of the three scales of sand waves compared with the original water depth

下载: 全尺寸图片幻灯片

图 9 提取的沙波峰线散点图

红点为提取的巨型沙波波峰点，蓝点为中型沙波波峰点

Fig. 9 Plots of the extracted sand wave crests

Red points represent the crests of the giant sand waves, and blue points are the crests of the small sand waves

下载: 全尺寸图片幻灯片

表 1 3种尺度沙波主要几何参量的统计结果

Tab. 1 Statistical results of the main characteristics of the separated three scales of sand waves

沙波类型		波长/m	波高/m	走向/（°）
巨型沙波	最大值	366.89	8.03	82.80
	最小值	192.47	5.13	73.80
	平均值	280.68	6.76	77.30
中型沙波	最大值	91.08	3.93	106.20
	最小值	42.96	1.27	81.10
	平均值	65.59	2.97	77.30
沙波纹	最大值	5.16	0.91	—
	最小值	1.25	0.06	—
	平均值	3.93	0.23	—

下载: 导出CSV

参考文献(40)

[1]	Allen J R L. Simple models for the shape and symmetry of tidal sand waves: (1) statically stable equilibrium forms[J]. Marine Geology, 1982, 48(1/2): 31−49.
[2]	杜晓琴, 李炎, 高抒. 台湾浅滩大型沙波、潮流结构和推移质输运特征[J]. 海洋学报, 2008, 30(5): 124−136. doi: 10.3321/j.issn:0253-4193.2008.05.017 Du Xiaoqin, Li Yan, Gao Shu. Characteristics of the large-scale sandwaves, tidal flow structure and bedload transport over the Taiwan Bank in southern China[J]. Haiyang Xuebao, 2008, 30(5): 124−136. doi: 10.3321/j.issn:0253-4193.2008.05.017
[3]	庄振业, 林振宏, 周江, 等. 陆架沙丘(波)形成发育的环境条件[J]. 海洋地质动态, 2004, 20(4): 5−10. doi: 10.3969/j.issn.1009-2722.2004.04.002 Zhuang Zhenye, Lin Zhenhong, Zhou Jiang, et al. Environmental conditions for the formation and development of sand dunes (waves) in the continental shelf[J]. Marine Geology Letters, 2004, 20(4): 5−10. doi: 10.3969/j.issn.1009-2722.2004.04.002
[4]	程和琴, 胡红兵, 蒋智勇, 等. 琼州海峡东口底形平衡域谱分析[J]. 海洋工程, 2003, 21(4): 97−103. doi: 10.3969/j.issn.1005-9865.2003.04.016 Cheng Heqin, Hu Hongbing, Jiang Zhiyong, et al. Equilibrium range spectra analysis of nearshore bedforms in the East Qiongzhou Strait[J]. The Ocean Engineering, 2003, 21(4): 97−103. doi: 10.3969/j.issn.1005-9865.2003.04.016
[5]	Dorst L L, Roos P C, Hulscher S J M H. Spatial differences in sand wave dynamics between the Amsterdam and the Rotterdam region in the southern North Sea[J]. Continental Shelf Research, 2011, 31(10): 1096−1105. doi: 10.1016/j.csr.2011.03.015
[6]	Zhou Qikun, Hu Guanghai, Sun Yongfu, et al. Numerical research on evolvement of submarine sand waves in the northern South China Sea[J]. Frontiers of Earth Science, 2017, 11(1): 35−45. doi: 10.1007/s11707-016-0571-6
[7]	Guillén J, Acosta J, Chiocci F L, et al. Atlas of Bedforms in the Western Mediterranean[M]. Cham: Springer International Publishing, 2017.
[8]	韩孝辉, 陈卫, 陈文. 海底输油气管线对海洋环境影响性分析[J]. 海洋开发与管理, 2018, 35(1): 83−87. doi: 10.3969/j.issn.1005-9857.2018.01.015 Han Xiaohui, Chen Wei, Chen Wen. Analysis on influence of subsea oil-gas pipeline on marine environment[J]. Ocean Development and Management, 2018, 35(1): 83−87. doi: 10.3969/j.issn.1005-9857.2018.01.015
[9]	Ye Yincan. Marine Geo-Hazards in China[M]. Amsterdam: Elsevier, 2017.
[10]	Lindenbergh R C. Parameter estimation and deformation analysis of sand waves and mega ripples[C]//Proceedings of the 2nd International Conference on Marine Sandwave and River Dune Dynamics. Enschede, The Netherlands: University of Twente, 2004.
[11]	van Dijk T A G P, Kleinhans M G. Processes controlling the dynamics of compound sand waves in the North Sea, Netherlands[J]. Journal of Geophysical Research: Earth Surface, 2005, 110(F4): F04S10.
[12]	Falqués A, Ribas F, Idier D, et al. Formation mechanisms for self-organized kilometer-scale shoreline sand waves[J]. Journal of Geophysical Research: Earth Surface, 2017, 122(5): 1121−1138. doi: 10.1002/2016JF003964
[13]	Damen J M, van Dijk T A G P, Hulscher S J M H. Spatially varying environmental properties controlling observed sand wave morphology[J]. Journal of Geophysical Research: Earth Surface, 2018, 123(2): 262−280. doi: 10.1002/jgrf.v123.2
[14]	夏东兴, 吴桑云, 刘振夏, 等. 海南东方岸外海底沙波活动性研究[J]. 黄渤海海洋, 2001, 19(1): 17−24. doi: 10.3969/j.issn.1671-6647.2001.01.003 Xia Dongxing, Wu Sangyun, Liu Zhenxia, et al. Research on the activity of submarine sand waves off Dongfang, Hainan Island[J]. Journal of Oceanography of Huanghai & Bohai Seas, 2001, 19(1): 17−24. doi: 10.3969/j.issn.1671-6647.2001.01.003
[15]	鲍晶晶. 台湾浅滩沙波动力特征研究[D]. 武汉: 中国地质大学, 2014. Bao Jingjing. Hydrodynamic characteristics of sand waves in the Taiwan shoal[D]. Wuhan: China University of Geosciences, 2014.
[16]	唐秋华. 东海北部外陆架海底底形特征及其成因研究[D]. 青岛: 中国海洋大学, 2009. Tang Qiuhua. Submarine bedforms and formation cause in the outer shelf of the north of the East China Sea[D]. Qingdao: Ocean University of China, 2009.
[17]	Jain C S, Kennedy J F. The growth of sand waves[C]//International Symposium on Stochastic Hydraulics. Pittsburgh: University of Pittsburgh School of Engineering Publication Series, 1971: 449-472.
[18]	Moll J R, Schilperoort T, de Leeuw A J. Stochastic analysis of bedform dimensions[J]. Journal of Hydraulic Research, 1987, 25(4): 465−479. doi: 10.1080/00221688709499263
[19]	Jerolmack D, Mohrig D. Interactions between bed forms: topography, turbulence, and transport[J]. Journal of Geophysical Research: Earth Surface, 2005, 110(F2): F02014.
[20]	van der Mark C F, Blom A, Hulscher S J M H. Variability in bedform characteristics using flume and river data[C]//Proceedings of the 5th IAHR Symposium on River, Coastal and Estuarine Morphodynamics. London: Taylor and Francis Group, 2007: 923–930.
[21]	阳凡林, 李家彪, 吴自银, 等. 多波束测深瞬时姿态误差的改正方法[J]. 测绘学报, 2009, 38(5): 450−456. doi: 10.3321/j.issn:1001-1595.2009.05.012 Yang Fanlin, Li Jiabiao, Wu Ziyin, et al. The methods of removing instantaneous attitude errors for multibeam bathymetry data[J]. Acta Geodaetica et Cartographica Sinica, 2009, 38(5): 450−456. doi: 10.3321/j.issn:1001-1595.2009.05.012
[22]	赵荻能, 吴自银, 周洁琼, 等. 声速剖面精简运算的改进D-P算法及其评估[J]. 测绘学报, 2014, 43(7): 681−689. Zhao Dineng, Wu Ziyin, Zhou Jieqiong, et al. A method for streamlining and assessing sound velocity profiles based on improved D-P algorithm[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(7): 681−689.
[23]	赵荻能, 吴自银, 李家彪, 等. CUBE曲面滤波参数联合优选关键技术及应用[J]. 测绘学报, 2019, 48(2): 245−255. doi: 10.11947/j.AGCS.2019.20180082 Zhao Dineng, Wu Ziyin, Li Jiabiao, et al. The key technology and application of parameter optimization combined CUBE and surface filter[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(2): 245−255. doi: 10.11947/j.AGCS.2019.20180082
[24]	吴自银, 阳凡林, 罗孝文, 等. 高分辨率海底地形地貌——可视计算与科学应用[M]. 北京: 科学出版社, 2017. Wu Ziyin, Yang Fanlin, Luo Xiaowen, et al. High Resolution Submarine Gemorphology—Theory and Technology for Surveying and Post-Processing[M]. Beijing: Science Press, 2017.
[25]	吴自银, 阳凡林, 李守军, 等. 高分辨率海底地形地貌——探测处理理论与技术[M]. 北京: 科学出版社, 2017. Wu Ziyin, Yang Fanlin, Li Shoujun, et al. High Resolution Submarine Gemorphology—Visual Computation and Scientific Applications[M]. Beijing: Science Press, 2017.
[26]	Wu Ziyin, Jin Xianglong, Li Jiabiao, et al. Linear sand ridges on the outer shelf of the East China Sea[J]. Science Bulletin, 2005, 50(21): 2517−2528. doi: 10.1007/BF03183643
[27]	Wu Ziyin, Jin Xianglong, Cao Zhenyi, et al. Distribution, formation and evolution of sand ridges on the East China Sea shelf[J]. Science in China Series D: Earth Sciences, 2010, 53(1): 101−112.
[28]	Wu Ziyin, Jin Xianglong, Zhou Jieqiong, et al. Comparison of buried sand ridges and regressive sand ridges on the outer shelf of the East China Sea[J]. Marine Geophysical Research, 2017, 38(1/2): 187−198.
[29]	Wu Ziyin, Li Jiabiao, Jin Xianglong, et al. Distribution, features, and influence factors of the submarine topographic boundaries of the Okinawa Trough[J]. Science China Earth Sciences, 2014, 57(8): 1885−1896. doi: 10.1007/s11430-013-4810-3
[30]	Gutierrez R R, Abad J D, Parsons D R, et al. Discrimination of bed form scales using robust spline filters and wavelet transforms: methods and application to synthetic signals and bed forms of the Río Paraná, Argentina[J]. Journal of Geophysical Research: Earth Surface, 2013, 118(3): 1400−1418. doi: 10.1002/jgrf.20102
[31]	Knaapen M A F. Sandwave migration predictor based on shape information[J]. Journal of Geophysical Research: Earth Surface, 2005, 110(F4): F04S11.
[32]	余威, 吴自银, 周洁琼, 等. 台湾浅滩海底沙波精细特征、分类与分布规律[J]. 海洋学报, 2015, 37(10): 11−25. doi: 10.3969/j.issn.0253-4193.2015.10.002 Yu Wei, Wu Ziyin, Zhou Jieqiong, et al. Meticulous characteristics, classification and distribution of seabed sand wave on the Taiwan bank[J]. Haiyang Xuebao, 2015, 37(10): 11−25. doi: 10.3969/j.issn.0253-4193.2015.10.002
[33]	周洁琼, 吴自银, 赵荻能, 等. 海底沙波特征线的最优方向剖面自动识别方法[J]. 海洋学报, 2015, 37(7): 97−107. doi: 10.3969/j.issn.0253-4193.2015.07.010 Zhou Jieqiong, Wu Ziyin, Zhao Dineng, et al. Automatic recognition of sand wave topographic features based on optimally-directional profiling method[J]. Haiyang Xuebao, 2015, 37(7): 97−107. doi: 10.3969/j.issn.0253-4193.2015.07.010
[34]	Zhou Jieqiong, Wu Ziyin, Jin Xianglong, et al. Observations and analysis of giant sand wave fields on the Taiwan Banks, northern South China Sea[J]. Marine Geology, 2018, 406: 132−141. doi: 10.1016/j.margeo.2018.09.015
[35]	Ashley G M. Classification of large-scale subaqueous bedforms; a new look at an old problem[J]. Journal of Sedimentary Research, 1990, 60(1): 160−172. doi: 10.2110/jsr.60.160
[36]	Flemming B W. Underwater sand dunes along the southeast African continental margin—observations and implications[J]. Marine Geology, 1978, 26(3/4): 177−198.
[37]	Press W H, Teukolsky S A, Vettering W T, et al. Numerical Recipes in C++[M]. Beijing: Publishing House of Electronics Industry, 2003.
[38]	陈传峰, 朱长仁, 宋洪芹. 基于巴特沃斯低通滤波器的图像增强[J]. 现代电子技术, 2007, 30(24): 163−165, 168. doi: 10.3969/j.issn.1004-373X.2007.24.057 Chen Chuanfeng, Zhu Changren, Song Hongqin. Image enhancement based on buterworth low pass filter[J]. Modern Electronics Technique, 2007, 30(24): 163−165, 168. doi: 10.3969/j.issn.1004-373X.2007.24.057
[39]	van Dijk T A G P, Lindenbergh R C, Egberts P J P. Separating bathymetric data representing multiscale rhythmic bed forms: a geostatistical and spectral method compared[J]. Journal of Geophysical Research: Earth Surface, 2008, 113(F4): F04017.
[40]	Smith S W. The Scientist and Engineer's Guide to Digital Signal Processing[M]. San Diego, California: California Technical Publishing, 1997.

施引文献

期刊类型引用(2)

1.	杜跃，欧阳锡钰. 基于多波束的海底复杂地貌图像识别方法研究. 机械设计与制造工程. 2023(02): 127-130 . 百度学术
2.	汪九尧，周洁琼，吴自银，朱超，赵荻能. 基于近底原位观测的小尺度海底沙波地形小波分解. 海洋学研究. 2022(02): 32-41 . 百度学术