Volume 41 Issue 9
Aug.  2022
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Jinghan Wen, Zhongbiao Chen, Yijun He. Optical flow-based method to estimate internal wave parameters from X-band marine radar images[J]. Acta Oceanologica Sinica, 2022, 41(9): 149-157. doi: 10.1007/s13131-022-1988-2
Citation: Jinghan Wen, Zhongbiao Chen, Yijun He. Optical flow-based method to estimate internal wave parameters from X-band marine radar images[J]. Acta Oceanologica Sinica, 2022, 41(9): 149-157. doi: 10.1007/s13131-022-1988-2

Optical flow-based method to estimate internal wave parameters from X-band marine radar images

doi: 10.1007/s13131-022-1988-2
Funds:  The National Natural Science Foundation of China under contract Nos 41620104003 and 42027805; the National Natural Science Youth Foundation of China under contract No. 41506199.
More Information
  • Corresponding author: yjhe@nuist.edu.cn
  • Received Date: 2021-08-05
  • Accepted Date: 2022-01-18
  • Available Online: 2022-06-07
  • Publish Date: 2022-08-31
  • The velocity and direction of internal waves (IWs) are important parameters of the ocean, however, traditional observation methods can only obtain the average parameters of IWs for a single location or large area. Herein, a new method based on optical flow is proposed to derive the phase velocity vectors of IWs from X-band marine radar images. First, the X-band marine radar image sequence is averaged, and ramp correction is used to reduce the attenuation of gray values with increasing radial range. Second, the average propagation direction of the IWs is determined using the two-dimensional Fourier transform of the radar images; two radial profiles along this direction are selected from two adjacent radar images; and then, the average phase velocity of the IWs is estimated from these radial profiles. Third, the averaged radar images are processed via histogram equalization and binarization to reduce the influence of noise on the radar images. Fourth, a weighting factor is determined using the average phase velocity of a reference point; the phase velocities on the wave crest of the IWs are subsequently estimated via the optical flow method. Finally, the proposed method is validated using X-band marine radar image sequences observed on an oil platform in the South China Sea, and the error of the phase velocity is calculated to be 0.000 3–0.073 8 m/s. The application conditions of the proposed method are also discussed using two different types of IW packets.
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  • [1]
    Alpers W. 1985. Theory of radar imaging of internal waves. Nature, 314(6008): 245–247. doi: 10.1038/314245a0
    Badiey M, Wan Lin, Lynch J F. 2016. Statistics of nonlinear internal waves during the shallow water 2006 experiment. Journal of Atmospheric and Oceanic Technology, 33(4): 839–846. doi: 10.1175/JTECH-D-15-0221.1
    Briscoe M G. 1975. Preliminary results from the trimoored internal wave experiment (IWEX). Journal of Geophysical Research, 80(27): 3872–3884. doi: 10.1029/JC080i027p03872
    Chen Zhongbiao, Zhang Biao, Kudryavtsev V, et al. 2019. Estimation of sea surface current from X-Band marine radar images by cross-spectrum analysis. Remote Sensing, 11(9): 1031. doi: 10.3390/rs11091031
    Gong Xiaoliang, Bansmer S. 2015. Horn–Schunck optical flow applied to deformation measurement of a birdlike airfoil. Chinese Journal of Aeronautics, 28(5): 1305–1315. doi: 10.1016/j.cja.2015.07.005
    Horn B K P, Schunck B G. 1981. Determining optical flow. Artificial Intelligence, 17(1–3): 185–203. doi: 10.1016/0004-3702(81)90024-2
    Huang Xiaodong, Chen Zhaohui, Zhao Wei, et al. 2016. An extreme internal solitary wave event observed in the northern South China Sea. Scientific Reports, 6: 30041. doi: 10.1038/srep30041
    Jackson C. 2007. Internal wave detection using the Moderate Resolution Imaging Spectroradiometer (MODIS). Journal of Geophysical Research, 112(C11): C11012. doi: 10.1029/2007JC004220
    Jia Tong, Liang Jianjun, Li Xiaoming, et al. 2019. Retrieval of internal solitary wave amplitude in shallow water by tandem spaceborne SAR. Remote Sensing, 11(14): 1706. doi: 10.3390/rs11141706
    Jia Tong, Liang Jianjun, Li Qiang, et al. 2021. Generation of shoreward nonlinear internal waves south of the Hainan Island: Synthetic aperture radar observations and numerical simulations. Journal of Geophysical Research: Oceans, 126(6): e2021JC017334
    Kropfli R A, Ostrovski L A, Stanton T P, et al. 1999. Relationships between strong internal waves in the coastal zone and their radar and radiometric signatures. Journal of Geophysical Research: Oceans, 104(C2): 3133–3148. doi: 10.1029/98JC02549
    Lü Haibin, He Yijun, Shen Hui, et al. 2010. A new method for the estimation of oceanic mixed-layer depth using shipboard X-band radar images. Chinese Journal of Oceanology and Limnology, 28(5): 962–967. doi: 10.1007/s00343-010-9022-5
    Li Xiaofeng, Clemente-Colón P, Friedman K S. 2000. Estimating oceanic mixed-layer depth from internal wave evolution observed from radarsat-1 SAR. Johns Hopkins APL Technical Digest, 21(1): 130–135
    Liang Jianjun, Li Xiaoming, Sha Jin, et al. 2019. The lifecycle of nonlinear internal waves in the northwestern South China Sea. Journal of Physical Oceanography, 49(8): 2133–2145. doi: 10.1175/JPO-D-18-0231.1
    Liu A K, Chang Y S, Hsu M K, et al. 1998. Evolution of nonlinear internal waves in the East and South China Seas. Journal of Geophysical Research: Oceans, 103(C4): 7995–8008. doi: 10.1029/97JC01918
    Lund B, Graber H C, Xue Jingshuang, et al. 2013. Analysis of internal wave signatures in marine radar data. IEEE Transactions on Geoscience and Remote Sensing, 51(9): 4840–4852. doi: 10.1109/TGRS.2012.2230635
    Ning Jing, Sun Lina, Cui Haiji, et al. 2020. Study on characteristics of internal solitary waves in the Malacca Strait based on Sentinel-1 and GF-3 satellite SAR data. Acta Oceanologica Sinica, 39(5): 151–156. doi: 10.1007/s13131-020-1604-2
    Orr M H, Mignerey P C. 2003. Nonlinear internal waves in the South China Sea: Observation of the conversion of depression internal waves to elevation internal waves. Journal of Geophysical Research: Oceans, 108(C3): 3064. doi: 10.1029/2001JC001163
    Pan Jiayi, Jay D A. 2009. Dynamic characteristics and horizontal transports of internal solitons generated at the Columbia River plume front. Continental Shelf Research, 29(1): 252–262. doi: 10.1016/j.csr.2008.01.002
    Plant W J, Keller W C, Hayes K, et al. 2011. Characteristics of internal waves in the South China Sea observed by a shipboard coherent radar. IEEE Journal of Oceanic Engineering, 36(3): 441–446. doi: 10.1109/JOE.2011.2133030
    Ramos R J, Lund B, Graber H C. 2009. Determination of internal wave properties from X-Band radar observations. Ocean Engineering, 36(14): 1039–1047. doi: 10.1016/j.oceaneng.2009.07.004
    Sun Lina, Zhang Jie, Meng Junmin. 2019. A study of the spatial-temporal distribution and propagation characteristics of internal waves in the Andaman Sea using MODIS. Acta Oceanologica Sinica, 38(7): 121–128. doi: 10.1007/s13131-019-1449-8
    Tang Qixuan. 2019. Research on oceanic internal wave detection and parameter extraction technology based on SAR image (in Chinese) [dissertation]. Harbin: Harbin Engineer University
    Wang Juan, Huang Weigen, Yang Jingsong, et al. 2011. The internal waves’ distribution of whole South China Sea extracted from ENVISAT and ERS-2 SAR images. In: Proceedings Volume 8175, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2011. Prague, Czech Republic: SPIE, 411–417
    Wang Juan, Huang Weigen, Yang Jingsong, et al. 2013. Study of the propagation direction of the internal waves in the South China Sea using satellite images. Acta Oceanologica Sinica, 32(5): 42–50. doi: 10.1007/s13131-013-0312-6
    Watson G, Robinson I S. 1990. A study of internal wave propagation in the strait of gibraltar using shore-based marine radar images. Journal of Physical Oceanography, 20(3): 374–395. doi: 10.1175/1520-0485(1990)020<0374:ASOIWP>2.0.CO;2
    Xue Jingshuang, Graber H C, Lund B, et al. 2013. Amplitudes estimation of large internal solitary waves in the mid-atlantic bight using synthetic aperture radar and marine X-Band radar images. IEEE Transactions on Geoscience and Remote Sensing, 51(6): 3250–3258. doi: 10.1109/TGRS.2012.2221467
    Yang Jingsong, Huang Weigen, Zhou Changbao, et al. 2001. Simulation study on optimal conditions for internal wave observation by SAR. In: Scanning the Present and Resolving the Future. IEEE 2001 International Geoscience and Remote Sensing Symposium. Sydney, NSW, Australia: IEEE, 3288–3290
    Zha Guozhen, He Yijun, Yu Tan, et al. 2012. The force exerted on a cylindrical pile by ocean internal waves derived from nautical X-band radar observations and in-situ buoyancy frequency data. Ocean Engineering, 41: 13–20. doi: 10.1016/j.oceaneng.2011.12.014
    Zheng Quanan, Yuan Yeli, Klemas V, et al. 2001. Theoretical expression for an ocean internal soliton synthetic aperture radar image and determination of the soliton characteristic half width. Journal of Geophysical Research: Oceans, 106(C12): 31415–31423. doi: 10.1029/2000JC000726
    Zhou Liying, Yang Jingsong, Wang Juan, et al. 2016. Spatio-temporal distribution of internal waves in the Andaman Sea based on satellite remote sensing. In: 2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). New York: IEEE, 624–628
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