Acta Photonica Sinica, Volume. 48, Issue 12, 1228003(2019)

Amplitude Inversion Model and Application of Internal Solitary Waves of the Northern South China Sea Based on Optical Remote-sensing Images

Jing NING... Jing WANG*, Meng ZHANG, Hai-ji CUI and Ke-xiao LU |Show fewer author(s)
Author Affiliations
  • College of Information Science and Engineering, Ocean University of China, Qingdao, Shandong 266100, China
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    Figures & Tables(13)
    The ISWs on MODIS optical remote sensing images. The insert map is the grey image of a single ISWs and the spatial profile of the leading wave which indicated by the red box
    Two-dimensional topography of South China Sea
    The topological structure of the BP neural network
    ISWs observed in the MODIS image at 11:15 (UTC+8), Wenchang area, on May 14, 2005
    Isotherm profile of the measured position in Wenchang on May 14, 2005
    南海北部海域内孤立波振幅分布Amplitude distribution of ISWs in the South China Sea
    南海北部内孤立波振幅与水深关系Relationship between the depth of water and amplitudes of ISWs in the South China Sea
    MODIS内孤立波图像,红点为内孤立波提取位置The ISWs on MODIS optical remote sensing images. The red dot is the extracted positions of ISWs
    单条内孤立波的振幅分布The amplitudes distribution of ISWs, and the colored dots indicate the amplitude position
    内孤立波振幅与水深关系Relationship between the depth of water and amplitudes of ISWs
    • Table 1. The characteristic parameter based on MODIS images of ISWs

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      Table 1. The characteristic parameter based on MODIS images of ISWs

      Characteristic parameterISW1ISW2ISW3ISW2260
      Small gradient strength0.460.550.490.47
      Large gradient strength440.45378.87406.81410.60
      Grey uneven representation33.3734.9719.4110.75
      Gradient uneven representation64.0781.0651.1677.71
      Energy0.060.150.060.02
      Grey mean87.87223.71152.02118.75
      Gradientmean15.2412.8214.1314.29
      Grey mean square28.3031.1227.5255.41
      Gradient mean square14.4314.6514.3914.37
      Relevance-54.67-252.92-173.96-28.10
      Grey entropy0.920.911.021.42
      Gradient entropy0.600.490.590.60
      Mixing entropy1.351.181.361.76
      Inertia6 394.0746 164.5020 324.8714 243.93
      Inverse gap0.000 330.001 10.008 20.000 24
      Peak-to-peak distance/m787.77786.83722.12793.28
    • Table 2. Parameter setting of BP neural network model

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      Table 2. Parameter setting of BP neural network model

      BP neural networkNumber of hidden layersNumber of neurons of hidden layersLearning rateNumber of iterations
      Model 11290.7500
      Model 2236, 150.7550
      Model 3334, 15, 40.4550
      Model 4434, 16, 4, 20.4600
    • Table 3. Calculated and observed amplitudes of the ISWs

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      Table 3. Calculated and observed amplitudes of the ISWs

      MODIS imageObservation/mCalculated result
      Model 1/mModel 2/mModel 3/mModel 4/mNLS model/m
      MOD02QKM. A2005109.0320.005.201015117560616.419.119.918.318.819.4
      MOD02QKM. A2005118.0315.005.201015123123920.721.720.320.220.120.3
      MOD02QKM. A2005132.0325.005.201015215395622.920.225.723.120.823.8
      MOD02QKM. A2005136.0300.005.201016000372227.923.226.228.626.527.3
      MOD02QKM. A2005180.0325.005.201015406104516.216.815.817.316.015.8
      MOD02QKM. A2005134.0315.005.201015216451117.119.918.918.318.119.3
      MYD02QKM. A2005140.0540.005.200923013072523.828.925.730.324.921.8
      MYD02QKM. A2005179.0545.005.200923207240715.617.317.516.816.617.0
      MOD02QKM. A2013183.0255.061.201729908350442.035.931.239.438.447.1
      Average error/%13.0%11.2%8.1%6.5%7.9%
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    Jing NING, Jing WANG, Meng ZHANG, Hai-ji CUI, Ke-xiao LU. Amplitude Inversion Model and Application of Internal Solitary Waves of the Northern South China Sea Based on Optical Remote-sensing Images[J]. Acta Photonica Sinica, 2019, 48(12): 1228003

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    Paper Information

    Received: Jul. 4, 2019

    Accepted: Sep. 3, 2019

    Published Online: Mar. 17, 2020

    The Author Email: WANG Jing (wjing@ouc.edu.cn)

    DOI:10.3788/gzxb20194812.1228003

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