Coastal ocean surface current retrievals from sequences of TerraSAR-X images (original) (raw)
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Surface Currents from Satellite-based SAR: ATI and Intensity Images
2012
As compared to conventional methods of ocean surface currents measurement, spaceborne Synthetic Aperture Radar (SAR) offers cloud-penetrating ocean current observation capability at high spatial resolution. While some studies have shown the potential of SAR for studying ocean surface currents through feature tracking, they have only analyzed a few images to demonstrate the basic measurement technique, and no concise general technique has been developed. This paper shows the application of the Maximum Cross-Correlation (MCC) method to generate ocean surface currents from nearly 2 years of available sequential spaceborne C-band SAR imagery from the Envisat ASAR and ERS-2 AMI-SAR sensors over the coastal California Current System. The data processing strategies are discussed in detail, and results are compared with High Frequency (HF) radar measured currents. One-dimensional wavenumber spectra of the SAR-derived surface currents agree with the k −2 powerlaw as predicted by submesoscale resolution models. Comparisons with HF radar currents show encouraging results with MCC SAR vectors oriented slightly anticlockwise relative to HF radar vectors. MCC SAR surface currents are found to have larger magnitudes than HF radar currents, ≈11 cm/s, which may be due to the fact that SAR penetrates only a few cm into the ocean surface while HF radar currents are averaged over the top 1 m of the ocean surface. The larger part of this magnitude difference is contained in the along-shore component, which can be attributed to higher HF radar accuracy in the direct radial cross-shore measurements as compared to along-shore components derived from multiple cross-shore radial measurements.
Retrieval of surface currents from sequential satellite radar images
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020
Determination of characteristics of marine currents using satellite remote sensing data is a rather complicated problem that has not been completely solved yet. Synthetic aperture radars (SAR) are often used to estimate the velocities of surface currents. The "filamentary" structures associated with biogenic marine films (slicks), which are often observed on the water surface at low-to-moderate wind conditions, can be potentially used as tracers to determine the surface current velocities. In this paper, an attempt is made to characterize marine currents using pairs of sequential images obtained with Envisat ASAR and ERS-2 SAR. The Maximum Cross-Correlation technique has been used to retrieve the surface current field. It is obtained that for some slick structures the retrieved surface velocities are directed nearly along the "filaments", so the latter can be considered as markers of the current streamlines. However, for other slicks, the velocities are directed at rather large angles to the tangents of the "filamentary" structures, so the "filaments" differ from the current streamlines. Supposedly, this is because the currents may not be steady and marine slicks cannot change their orientation and shape instantly following fast changes of environmental conditions, in particular, to variations of wind speed/direction.
Computing Coastal Ocean Surface Currents From Infrared and Ocean Color Satellite Imagery
IEEE Transactions on Geoscience and Remote Sensing, 2000
Many previous studies have demonstrated the viability of estimating advective ocean surface currents from sequential infrared satellite imagery using the Maximum Cross Correlation (MCC) technique. This method has the potential of retrieving representative mesoscale surface currents when applied to 1.1 km resolution Advanced Very High Resolution Radiometer (AVHRR) thermal infrared imagery. However, when the technique is applied only to infrared imagery cloud cover and undesirable viewing conditions (gaps in satellite data and edge-of-scan distortions) limit the spatial and temporal coverage of the resulting velocity fields. MCC currents are also limited to those represented by the displacements of thermal surface patterns, and hence isothermal flow is not detected by the MCC method. This study examines the possibility of supplementing MCC currents derived from thermal AVHRR imagery with currents calculated from 1.1 km resolution MODIS and SeaWiFS ocean color imagery which often represents spatial patterns complimentary to the thermal infrared images. Statistical comparisons are carried out between yearlong collections of thermal and ocean color derived MCC velocities for the central California Current. It is found that the image surface patterns, and resulting MCC velocities, compliment one another to reduce the effects of poor viewing conditions and isothermal flow. In addition the ocean color MCC surface currents provide an additional sample of the surface currents thus increasing the sample size. The two velocity products are found to agree quite well with a mean correlation of 0.74, a mean RMS difference of 7.4 cm/s, and a mean bias less than 2 cm/s. The error between thermal and ocean color MCC velocities is considerably smaller than the established absolute error of the MCC method, indicating that surface currents can be accurately computed from sequential ocean color imagery. Merging the thermal and ocean color MCC velocity fields increases the spatial and temporal coverage by approximately 40% for this specific case study.
Computing Ocean Surface Currents from Infrared and Ocean Color Imager
Many previous studies have demonstrated the viability of estimating advective ocean surface currents from sequential infrared satellite imagery using the Maximum Cross Correlation (MCC) technique. This method has the potential of retrieving representative mesoscale surface currents when applied to 1.1 km resolution Advanced Very High Resolution Radiometer (AVHRR) thermal infrared imagery. However, when the technique is applied only to infrared imagery cloud cover and undesirable viewing conditions (gaps in satellite data and edge-of-scan distortions) limit the spatial and temporal coverage of the resulting velocity fields. MCC currents are also limited to those represented by the displacements of thermal surface patterns, and hence isothermal flow is not detected by the MCC method. This study examines the possibility of supplementing MCC currents derived from thermal AVHRR imagery with currents calculated from 1.1 km resolution MODIS and SeaWiFS ocean color imagery which often represents spatial patterns complimentary to the thermal infrared images. Statistical comparisons are carried out between yearlong collections of thermal and ocean color derived MCC velocities for the central California Current. It is found that the image surface patterns, and resulting MCC velocities, compliment one another to reduce the effects of poor viewing conditions and isothermal flow. In addition the ocean color MCC surface currents provide an additional sample of the surface currents thus increasing the sample size. The two velocity products are found to agree quite well with a mean correlation of 0.74, a mean RMS difference of 7.4 cm/s, and a mean bias less than 2 cm/s. The error between thermal and ocean color MCC velocities is considerably smaller than the established absolute error of the MCC method, indicating that surface currents can be accurately computed from sequential ocean color imagery. Merging the thermal and ocean color MCC velocity fields increases the spatial and temporal coverage by approximately 40% for this specific case study.
Ocean Surface Currents: What we can do with Earth Observation at finer resolutions?
2012
As compared to conventional methods of ocean surface currents measurement, spaceborne Synthetic Aperture Radar (SAR) offers cloud-penetrating ocean current observation capability at high spatial resolution. While some studies have shown the potential of SAR for studying ocean surface currents through feature tracking, they have only analyzed a few images to demonstrate the basic measurement technique, and no concise general technique has been developed. This paper shows the application of the Maximum Cross-Correlation (MCC) method to generate ocean surface currents from nearly 2 years of available sequential spaceborne C-band SAR imagery from the Envisat ASAR and ERS-2 AMI-SAR sensors over the coastal California Current System. The data processing strategies are discussed in detail, and results are compared with High Frequency (HF) radar measured currents. One-dimensional wavenumber spectra of the SAR-derived surface currents agree with the k −2 powerlaw as predicted by submesoscale resolution models. Comparisons with HF radar currents show encouraging results with MCC SAR vectors oriented slightly anticlockwise relative to HF radar vectors. MCC SAR surface currents are found to have larger magnitudes than HF radar currents, ≈11 cm/s, which may be due to the fact that SAR penetrates only a few cm into the ocean surface while HF radar currents are averaged over the top 1 m of the ocean surface. The larger part of this magnitude difference is contained in the along-shore component, which can be attributed to higher HF radar accuracy in the direct radial cross-shore measurements as compared to along-shore components derived from multiple cross-shore radial measurements.
Remote sensing of oceanic current features by synthetic aperture radar—achievements and perspectives
It is generally accepted that synthetic aperture radar (SAR) images can be quite useful for a better understanding of hydrodynamic processes in the ocean, because they provide valuable information on the location and spatial scales of oceanic features such as fronts, internal waves, and eddies. However, the retrieval of actual surface current fields from the shape and modulation depth of radar signatures is a much more challenging problem, since the imaging mechanism is a complex and nonlinear two-step-mechanism whi,~'hr cannot-be inverted easily. In this article we review the state-of-the-art in modeling radar signatures of current features, and we present the concept of an iterative scheme for inverting radar images into current fields, which will be implemented within the framework of the European project MARSAtS. We estimate the accuracy and spatial resolution of the proposed remote sensing system on the basis of findings from recent case studies and some dedicated simulations. According to the results of our analyses, it should be possible to retrieve spatial surface current variations and current gradients from a typical spaceborne C band SAR image with an accuracy on the order of 20% and a spatial resolution on the order of 50 m.
On the Remote Sensing of Current Features by Spaceborne Synthetic Aperture Radar
2004
Spatial variations in ocean surface currents can become visible in synthetic aperture radar (SAR) images via hydrodynamic modulation of the surface roughness. The interpretation of such SAR signatures is a challenging problem, since the imaging mechanism is quite complex and nonlinear and cannot be inverted easily. Furthermore, the distinction between SAR signatures of current features and other phenomena can be difficult. However, SAR is the only existing technique for the observation of current variations on spatial scales of some meters from satellites. There is a vital demand for such information, particularly in coastal regions. A variety of algorithms have been developed for the retrieval of information on current features from SAR images for different purposes. We give an overview of the state of the art, existing and potential applications, and future perspectives and requirements.
Status report on the remote sensing of current features by spaceborne synthetic aperture radar
Spatial variations in ocean surface currents can become visible in synthetic aperture radar (SAR) images via hydrodynamic modulation of the surface roughness. The interpretation of such SAR signatures is a challenging problem, since the imaging mechanism is quite complex and nonlinear and cannot be inverted easily. Furthermore, the distinction between SAR signatures of current features and other phenomena can be difficult. However, SAR is the only existing technique for the observation of current variations on spatial scales of tens of meters from satellites. There is a vital demand for such information, particularly in coastal regions. A variety of algorithms have been developed for the retrieval of information on current features from SAR images for different purposes. We give an overview of the state of the art, existing and potential applications, and future perspectives and requirements.
This paper considers the use of coupled wave-current models in combination with synthetic-aperture radar (SAR) and along-track interferometric SAR (ATI) observations for the interpretation of the spatial structure of surface currents. The present status of the development of these models is summarised. Examples over shelf seas, shallow-water bathymetry and estuaries are discussed, for both conventional SAR imagery and along-track interferometry (ATI). The potential practical benefits of combined SAR and model products are outlined.