The problem of characterization of marine currents using ocean remote sensing data is very challenging and has not been completely resolved by now. Optical and IR satellite images of the ocean have been traditionally used to estimate the current velocities when comparing color or temperature inhomogeneities in co-located subsequent scenes. SAR as all-weather and all-day instrument with high spatial resolution is very perspective for ocean remote sensing, and the procedure similar to the optical/IR observations seems to be usable for SAR for the current velocity estimation, too. Marine biogenic film slicks often observed on the sea surface as systems of “filamentary” structures at low/moderate wind conditions can be considered as appropriate features for marine current tracking. However, very few attempts have been made to study the current velocity field when studying slick features in SAR images acquired from different satellites at a comparably short time interval. In this paper two sequential satellite SAR images acquired with Envisat ASAR and ERS-2 SAR have been analyzed in order to estimate the surface marine currents. The acquisition time difference between the images was nearly 30 min. The images were characterized by a number of slick features which were nearly identical within the 30 min time shift, so that it was rather easy to track any chosen slick structure and to retrieve the velocity field. A Maximum Cross-Correlation (MCC) method has been used for the current retrieval, when analyzing correlation between the sequential images. It has been obtained that for some slick filamentary structures or for their parts the retrieved current velocities were directed nearly along the filaments, so that the slicks can be considered as the current streamlines. On the contrary, for some other slicks the retrieved current velocity vectors were directed at quite large angles to the filament tangent lines. We believe that the latter effect appears for varying currents due to the “memory” of slicks which cannot change their orientation or appear/disappear instantaneously according to fast changes of environmental conditions, in particular according to wind speed velocity/direction changes.
[1]
Ivan A. Kapustin,et al.
Modulation of Dual-Polarized X-Band Radar Backscatter Due to Long Wind Waves
,
2019,
Remote. Sens..
[2]
J. Jolliff,et al.
Estimating Advective Near-surface Currents from Ocean Color Satellite Images
,
2015
.
[3]
William J. Emery,et al.
Computing Ocean Surface Currents Over the Coastal California Current System Using 30-Min-Lag Sequential SAR Images
,
2014,
IEEE Transactions on Geoscience and Remote Sensing.
[4]
George O. Marmorino,et al.
Measurement of surface currents using sequential synthetic aperture radar images of slick patterns near the edge of the Gulf Stream
,
1998
.
[5]
M. Jeroen Molemaker,et al.
Airborne synthetic aperture radar observations of “spiral eddy” slick patterns in the Southern California Bight
,
2010
.
[6]
Martin Gade,et al.
Slicks as indicators for marine Processes
,
2013
.
[7]
Ivan A. Kapustin,et al.
Remote Sensing of Organic Films on the Water Surface Using Dual Co-Polarized Ship-Based X-/C-/S-Band Radar and TerraSAR-X
,
2018,
Remote. Sens..
[8]
Benjamin Holt,et al.
Satellite observations of small coastal ocean eddies in the Southern California Bight
,
2001
.
[9]
David P. Dobson,et al.
The FeSi phase diagram to 150 GPa
,
2010
.
[10]
Beniamino Gioli,et al.
Bridging the gap between atmospheric concentrations and local ecosystem measurements
,
2009
.
[11]
J. McWilliams,et al.
Cold filamentary intensification and oceanic surface convergence lines
,
2009
.
[12]
W. Emery,et al.
Extracting Multiyear Surface Currents from Sequential Thermal Imagery Using the Maximum Cross-Correlation Technique
,
2002
.