Measurement of the Doppler shift in forward-scattered waves caused by moderate sea surface motion in shallow waters

2005 ◽  
Vol 6 (4) ◽  
pp. 250-256 ◽  
Author(s):  
Pierre-Philippe J. Beaujean ◽  
Guenael T. Strutt
2012 ◽  
Vol 50 (7) ◽  
pp. 2901-2909 ◽  
Author(s):  
Alexis A. Mouche ◽  
Fabrice Collard ◽  
Bertrand Chapron ◽  
Knut-Frode Dagestad ◽  
Gilles Guitton ◽  
...  

2021 ◽  
Vol 9 ◽  
Author(s):  
Richard Fiifi Annan ◽  
Xiaoyun Wan

A regional gravity field product, comprising vertical deflections and gravity anomalies, of the Gulf of Guinea (15°W to 5°E, 4°S to 4°N) has been developed from sea surface heights (SSH) of five altimetry missions. Though the remove-restore technique was adopted, the deflections of the vertical were computed directly from the SSH without the influence of a global geopotential model. The north-component of vertical deflections was more accurate than the east-component by almost three times. Analysis of results showed each satellite can contribute almost equally in resolving the north-component. This is attributable to the nearly northern inclinations of the various satellites. However, Cryosat-2, Jason-1/GM, and SARAL/AltiKa contributed the most in resolving the east-component. We attribute this to the superior spatial resolution of Cryosat-2, the lower inclination of Jason-1/GM, and the high range accuracy of the Ka-band of SARAL/AltiKa. Weights of 0.687 and 0.313 were, respectively, assigned to the north and east components in order to minimize their non-uniform accuracy effect on the resultant gravity anomaly model. Histogram of computed gravity anomalies compared well with those from renowned models: DTU13, SIOv28, and EGM2008. It averagely deviates from the reference models by −0.33 mGal. Further assessment was done by comparing it with a quadratically adjusted shipborne free-air gravity anomalies. After some data cleaning, observations in shallow waters, as well as some ship tracks were still unreliable. By excluding the observations in shallow waters, the derived gravity field model compares well in ocean depths deeper than 2,000 m.


2008 ◽  
Vol 57 (6) ◽  
pp. 3464
Author(s):  
Guo Li-Xin ◽  
Wang Rui ◽  
Wang Yun-Hua ◽  
Wu Zhen-Sen

2021 ◽  
Author(s):  
Anis Elyouncha ◽  
Leif E. B. Eriksson

<p><span>Synthetic aperture radar (SAR) has become an essential component in ocean remote sensing due it’s </span><span>high</span> <span>sensitivity</span><span> to sea surface dynamics and its high spatial resolution. </span><span>The ALOS-</span><span>2 SAR</span><span> data are </span> underutilized <span>for</span><span> ocean surface wind and current retrieval. Althou</span><span>g</span><span>h the primary goals of the </span><span>ALOS-2</span><span> mission are focused on land applications, the extension of the satellite scenes over the coast</span><span>al areas</span><span> offers an opportunity for ocean applications. Th</span><span>e</span><span> underutilization </span><span>of ALOS-2 data </span><span>is mainly due to the fact that at low radar frequencies, e.g. L-band, the sensitivity of the radar scattering coefficient to wind speed and the sensitivity of the Doppler frequency shift to sea surface velocity is lower than at higher frequencies, e.g. C- </span><span>and</span><span> X-</span><span>band</span><span>. </span><span>This is also due to the fact that most of ALOS-2 images are acquired in HH or HV polarization while the VV polarization is often preferred in ocean applications due the higher signal to noise ratio. </span></p><p>The wind speed is retrieved from Sentinel-1 and ALOS-2 using the existing empirical C- and L-band geophysical model functions. For Sentinel-1, the Doppler frequency shift provided in the OCN product is used. For ALOS-2, the Doppler frequency shift is estimated from the single look complex data using the pulse-pair processing method. The estimated Doppler shift converted to the surface radial velocity and the velocity is calibrated using land as a reference. The estimated L-band Doppler shift and surface velocity is compared to the C-band Doppler shift provided in the Sentinel-1 OCN product. Due the difference in the local time of ascending node (about 6 hours at the equator) of the two satellites, a direct pixel-by-pixel comparison is not possible, i.e. the wind and surface current can not be assumed to be constant during such a large time difference. Thus, the retrieved wind from each sensor is compared separately to model data and in-situ observations.</p><p>In this paper, the quality of the wind speed retrieved from the L-band SAR (ALOS-2) in coastal areas is assessed and compared to the C-band SAR (Sentinel-1). In addition, the feasibility of the surface current retrieval from the L-band Doppler frequency shift is investigated and also compared to Sentinel-1. Examples will be shown and discussed. This opens an opportunity for synergy between L-band and C-band SAR missions to increase the spatial and temporal coverage, which is one of the main limitations of SAR application in ocean remote sensing.</p>


1984 ◽  
Vol 16 (1) ◽  
pp. 87-90 ◽  
Author(s):  
Andrew C. Vastano ◽  
Stephen E. Borders

1998 ◽  
Vol 49 (8) ◽  
pp. 875
Author(s):  
Michael McGoldrick ◽  
Joseph Leach

The study was designed to identify the connection between features on the satellite image and the sea floor in Lonsdale Bight, Victoria, Australia, and to produce a map based on the findings. It used a semi-submersible vessel with an observation pod that can be lowered 1 m below the sea surface; this provides a stable platform from which spatially accurate data can be collected in the sub-marine environment, free from atmospheric effects. The results indicated a link between the depth and composition of the seabed and the spectral values found in the associated satellite image. Hence, the semi-submersible vessel is an ideal tool for seafloor imaging in shallow waters, without the disadvantages associated with diving.


2014 ◽  
Vol 52 (11) ◽  
pp. 7120-7129 ◽  
Author(s):  
David Miret ◽  
Gabriel Soriano ◽  
Frederic Nouguier ◽  
Philippe Forget ◽  
Marc Saillard ◽  
...  

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