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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

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Front. Earth Sci.    2015, Vol. 9 Issue (4) : 700-708    https://doi.org/10.1007/s11707-015-0506-7
RESEARCH ARTICLE
Internal wave parameters retrieval from space-borne SAR image
Kaiguo FAN1,2,7,Bin FU1,*(),Yanzhen GU3,6,Xingxiu YU2,5,*(),Tingting LIU4,Aiqin SHI1,Ke XU7,Xilin GAN1
1. State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China
2. Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China
3. Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China
4. Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430072, China
5. Shandong Provincial Key Laboratory of Soil Conservation and Environmental Protection, Linyi University, Linyi 276000, China
6. College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China
7. 91039 Army, PLA, China
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Abstract

Based on oceanic internal wave SAR imaging mechanism and the microwave scattering imaging model for oceanic surface features, we developed a new method to extract internal wave parameters from SAR imagery. Firstly, the initial wind fields are derived from NCEP reanalysis data, the sea water density and oceanic internal wave pycnocline depth are estimated from the Levites data, the surface currents induced by the internal wave are calculated according to the KDV equation. The NRCS profile is then simulated by solving the action balance equation and using the sea surface radar backscatter model. Both the winds and internal wave pycnocline depth are adjusted by using the dichotomy method step by step to make the simulated data approach the SAR image. Then, the wind speed, pycnocline depth, the phase speed, the group velocity and the amplitude of internal wave can be retrieved from SAR imagery when a best fit between simulated signals and the SAR image appears. The method is tested on one scene SAR image near Dongsha Island, in the South China Sea, results show that the simulated oceanic internal wave NRCS profile is in good agreement with that on the SAR image with the correlation coefficient as high as 90%, and the amplitude of oceanic internal wave retrieved from the SAR imagery is comparable with the SODA data. Besides, the phase speeds retrieved from other 16 scene SAR images in the South China Sea are in good agreement with the empirical formula which describes the relations between internal wave phase speed and water depths, both the root mean square and relative error are less than 0.11 m·s−1 and 7%, respectively, indicating that SAR images are useful for internal wave parameters retrieval and the method developed in this paper is convergent and applicable.
Keywords synthetic aperture radar      internal wave      retrieval     
Corresponding Author(s): Bin FU,Xingxiu YU   
Just Accepted Date: 10 July 2015   Online First Date: 12 August 2015    Issue Date: 30 October 2015
 Cite this article:   
Kaiguo FAN,Bin FU,Yanzhen GU, et al. Internal wave parameters retrieval from space-borne SAR image[J]. Front. Earth Sci., 2015, 9(4): 700-708.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-015-0506-7
https://academic.hep.com.cn/fesci/EN/Y2015/V9/I4/700
Fig.1  The flow chart of internal wave parameters retrieval by SAR.
Fig.2  ERS-2 SAR image with oceanic internal wave characteristics of elongated bright and dark features near Dongsha Island, imaging taken at 14:10 UTC on 23 June 1998, and the data line A→B represents the NRCS profile of the internal wave SAR images within the test site.
h1/m ρ1/(kg·m−3) ρ2/(kg·m−3) Δρ/ρ
88 1,022.98 1,026.57 0.0035
Tab.1  Water parameters estimated from the Levites data
Iterative times Wind speeds/(m·s−1) σ S M 0 /dB σ M 0 /dB Difference ε
1 2.81 −5.29 −7.46 2.17
2 2.21 −6.04 −7.46 1.42
3 1.71 −6.91 −7.46 0.55
4 1.21 −7.89 −7.46 −0.43
5 1.31 −7.61 −7.46 −0.15
6 1.41 −7.37 −7.46 0.09
Tab.2  The iterative process of the adjusted sea surface wind speeds
Iterative times h1/m Δρ/ρ η0/m SBD/dB RBD/dB Difference ε
1 88 0.0035 −18.7 2.86 3.31 0.45
2 100 0.0034 −26.0 3.50 3.31 0.19
3 94 0.0034 −22.0 3.08 3.31 0.23
4 97 0.0034 −23.9 3.26 3.31 0.05
Tab.3  The iterative process of the adjusted the pycnocline depth h1
Fig.3  The NRCS profile of the internal wave SAR image (the solid line) and the simulated signal of the internal wave (the dashed line) along the data line A→B in Fig. 2.
Fig.4  Temperature and salinity profiles from CARTON-GIESE SODA data at 116.5°E, 21.0°N at the vicinity of the internal waves observed in the SAR image.
Time Lon./(°) Lat./(°) Depth/m L/m h1/m η0/m Cp/(m·s−1) Cg/(m·s−1)
3-12-1997 116.466 20.383 732 965.91 205 52.1 2.39 2.2
11-5-1998 116.154 20.908 378 397.73 124 64.6 1.64 1.42
23-6-1998 116.641 21.035 290 246.21 85 55.5 1.43 1.15
22-4-1998 116.414 20.581 562 653.41 162 55.3 1.98 1.78
11-5-1998 116.597 21.694 167 681.82 78 11.6 0.99 0.98
23-6-1998 116.586 21.122 283 577.65 85 9.9 1.42 1.37
23-6-1998 116.585 21.122 282 587.12 85 9.56 1.42 1.37
12-4-2000 117.321 21.749 278 331.44 107 62.9 1.33 1.18
2-10-2000 116.69 21.171 322 501.89 109 27.5 1.56 1.47
29-4-2000 115.602 21.464 109 274.62 50 17.1 0.7 0.68
28-5-2001 117.289 21.719 282 274.62 97 65.7 1.34 1.13
5-5-2001 117.091 21.459 344 568.18 100 17.1 1.44 1.37
24-4-2001 117.439 21.840 270 558.71 99 16.8 1.27 1.23
24-4-2001 117.592 21.972 134 179.92 80 29.6 0.73 0.67
24-6-2002 116.719 21.198 357 473.48 95 22.2 1.57 1.45
24-6-2002 116.775 21.351 340 464.02 85 17.2 1.47 1.37
6-11-2005 113.843 19.212 691 965.91 176 34.5 2.35 2.2
29-6-2005 116.445 21.355 307 511.36 84 12.8 1.43 1.36
29-6-2005 114.248 20.718 83 170.46 30 5.04 0.6 0.58
Tab.4  The internal wave parameters retrieved from other SAR images
Fig.5  Comparison between both the phase speeds retrieved from SAR image and the results calculated from the empirical formula.
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