The synthetic aperture radar (SAR) has been proven to be a valuable tool for high resolution ocean surface wind measurements, which is especially important for coastal waters. However, oceanic surface phenomena observed by SAR and oceanic processes which can cause the change of backscatter in SAR imagery will influence the SAR wind retrieval. Upwelling is one of the main factors and it is prevalent in summer along the Zhejiang Coast. It smoothes the sea surface
which results in the lower backscatter cross section in SAR imagery. In this article, using sea surface temperature (SST) and chlorophyll2-a data derived from EOS MODIS, the low backscatter features in ENVISAT ASAR imagery are analyzed along the Zhejiang Coast in the East China Sea. And then CMOD4 algorithm is adopted to retrieve the sea surface wind speed, using wind directions from interpolated NCEP / NCAR reanalysis data. The result of wind speed is
negatively biased due to the low Normalized Radar Cross Section (NRCS) associated with the Zhejiang Coastal Upwelling. In order to resolve impact of the coastal upwelling on SAR wind retrieval, combining high resolution numerical meteorological model wind field data, a wind speed correction model is proposed using linear robust
regression. Results show that the accuracy of SAR wind retrieval is improved in upwelling region.
In this paper, submarine sand wave imaging by SAR in Taiwan shoal and their relationships with sea surface wind and sea surface current are discussed. A total of 69 synthetic aperture radar (SAR) images over 11 years between 1996 and 2006 are collected and 496 profiles of sand wave SAR images are used for the observations of sand wave SAR images. The sea surface wind estimated from NCEP/QSCAT blended wind data and the sea surface current calculated form highfrequency (HF) radar system are utilized for the study on the observations of sand wave SAR images with the wind
speed and current speed. The results show submarine sand waves in Taiwan Shoal are mainly distributed from 117.75°E
to 118.70°E and 22.7°N to 23.35°N with a high percent of 72.2. About 91% of sand waves are observed by SAR under
wind speed of 9 m/s while only 6% of sand waves are imaged above wind speed of 10 m/s. And under the adverse wind
direction, the observed sand wave reaches its maximum, while the crosswind has its minimum. These support that low
and middle wind speed and adverse wind direction are favorable for SAR imaging submarine sand waves, high wind
speed and crosswind are unfavorable. The observations of sand wave SAR images reach its seasonal maximum with a percentage of 49 in summer and have its minimum in autumn with 8%, while spring and winter has percentage of 20 and 23 respectively. The comparisons for monthly mean sea surface wind speed and monthly mean sea surface current speed with observed sand waves also shows strong relationships, which are lower sea surface wind speeds and higher sea surface current speed, the higher probability of sand waves observed by SAR. This may indicate that the higher observation of the sand waves by SAR is partly due to wind speed and current speed.
Oceanic internal waves are present on all levels of the water column in deep oceans as well as in marginal coastal seas.
They appear as elongated bright and dark features in synthetic aperture radar (SAR) images as they are associated with
variable surface currents that modify the sea surface roughness patterns via current-wave interaction. Because of the
influence of SAR noise and other factors, it will be disturbed when we use computer auto-detection technique to detect
the oceanic internal wave. In this paper, an automatic method has been developed for detection of oceanic internal wave
on satellite SAR images based on the nature of sea surface oceanic internal wave. The procedure includes the edge
detection, point joining and the determination and presentation of sea surface oceanic internal wave. Examples of
detection of the oceanic internal wave on SAR images by the procedure are illustrated. The results of the sea surface
oceanic internal wave detection shown that the procedure works well.
A new method for mapping shallow water topography surface currents from SAR image is introduced based on the
shallow water topography SAR imaging mechanism. M4S (presented by Romeiser R.) was used to forward simulate
radar signatures of the oceanic features over the ocean surface. The first guessed surface currents can be estimated from
the normalized radar cross section (NRCS) of the shallow water topography profile in the SAR image according to the
Apers-Hennings linear theory, the NRCS induced by the varying shallow water topography surface currents could be
simulated by the forward simulating model. The wind speed and shallow water topography surface currents gradients are
modified using the iterative method until the simulated radar signals close to the NRCS calculated from SAR image. By
this method, the wind speed and the surface currents can be retrieved finally. This method is tested on an ERS-2 SAR
image in the Taiwan Shoal. Results show that the simulated shallow water topography radar signal is consistent with the
NRCS extracted from SAR image, and their correlation coefficient is up to 90%, which means that this method is
convergent and applicable.
A new method for retrieving shallow water topography surface currents from SAR image is introduced based on the
shallow water topography SAR imaging mechanism. M4S was applied to forward simulate radar signatures of the
oceanic features over the ocean surface. The first guessed surface currents can be estimated from the normalized radar
cross section (NRCS) of the shallow water topography profile in the SAR image according to the AH linear theory, the
NRCS induced by the varying shallow water topography surface currents could be simulated by the forward simulating
model. The wind speed and shallow water topography surface currents gradients are modified using the iterative method
for the simulated radar signals close to the NRCS calculated from SAR image. Finally, the wind speed and the surface
currents can be retrieved. This method is tested on an ERS-2 SAR image in the Taiwan Shoal. The result shows that the
simulated shallow water topography radar signal is consistent with the NRCS measured from SAR image, and their
correlation coefficient is up to 90%, which means that this method is convergent and applicable.
One of the main problems in ship detection is the presence of sea clutter inherent to radar imagery. A moving ship
detection method with time sequential shipborne radar imagery has been developed based on the radar backscattering
properties of ships. The method consists of the coherence image computation, ship detection threshold estimation and
false alarm removal. It has been tested with the X-band shipborne radar imagery. The results show that the method works
well.
This paper discusses the relationship between the observations of submarine sand wave SAR images in Taiwan shoal and
sea surface wind. A total of 43 SAR images over 11 years are collected and 496 profiles of sand wave SAR images are
used, the wind are estimated from blended wind data and current direction is from mode. Results show submarine sand
waves are observed by SAR under wind speed of 10 m/s, only littlie are imaged above 10 m/s. The number of observed
sand waves reaches its maximum under the adverse wind direction, while the crosswind has its minimum. These support
that low and middle wind speed and adverse wind direction are favorable for SAR imaging submarine sand waves, high
wind speed and crosswind are unfavorable. The comparison between monthly mean wind speed and sand waves
observed by SAR also shows a strong correlation between both, which is lower wind speeds, the higher probability of
sand waves observed by SAR. This may indicate that the higher observation of the sand waves by SAR is partly due to
wind speed.
Analytical expression of normalized radar backscattering cross-section (NRCS) contrasts for shallow water bathymetry
SAR images has been firstly obtained by applying the continuity equation and the first order Bragg backscattering theory,
and replacing the surface wave action balance equation with high frequency ocean wave spectrum balance equation. Based
on the expression, we have simulated C band NRCS contrasts under different currents and sea surface winds firstly, results
show the trend of NRCS contrasts' change with the shallow water bathymetry, and preferable currents and sea surface
winds conditions for mapping shallow water bathymetry by SAR, which agree well with observations and shallow water
bathymetry SAR images simulations. Moreover, the NRCS contrasts index which means the relationship between each
currents and sea surface winds under given bathymetry parameters is first quantitatively calculated, which gives scientific
proof for carrying SAR shallow water bathymetry surveys according to the ocean and weather conditions.
A new remote sensing technique based on the analysis of Synthetic Aperture Radar (SAR) images of waves has been
developed for estimation of near-shore coastal water bathymetry. Near-shore coastal water regions generate a rich range
of surface signatures observable by SAR, mainly due to effects of spatially changing water depths that cause variations in
the ocean surface roughness. These signatures contain a great deal of information regarding wave's parameters and their
variation over the area including the wavelength of surface waves change over varying water depths. By approaching the
analysis of SAR images of waves, using images analysis techniques and the general desperation relation of ocean waves,
new indirect technique of remote sensing bathymetry is applied over near-shore coastal water regions in Wenzhou
Zhejiang province, China. Results show that this technique is especially suitable for the near-shore coastal water zone
where the water depths change.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.