Processing and analysis of Doppler information from Sentinel 1A Interferometric Wide (IW) and Extra Wide (EW) modes are performed for assessing the capabilities of mapping ocean surface current field. Data from Agulhas (South-Africa) and Norwegian Coast are used in combination with numerical models, higher-order satellite products, and Lagrangian drifters. Results show strong Doppler signal and dynamics from coastal areas caused by a mixture of surface current and wind/wave induced drifts at a spatial resolution of around 2 km2 in IW mode and 4km2 in EW mode. Doppler values of up to 70 Hz are observed, corresponding to a surface drift velocity of 3.5 m/s. The Sentinel 1 retrieved surface current component is in reasonable agreement with the circulation models and drifter measurements. Surface current values up to 1.5 m/s are observed in the central Agulhas current, with a standard deviation of around 0.39 m/s with respect to Lagrangian drifters.

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Ocean doppler anomaly and ocean surface current from Sentinel 1 tops mode

In this paper, the capability of Sentinel-1 data to map ocean surface currents in the Skagerrak Sea, with a focus on the Norwegian Coastal Current (NCC), is investigated. Post-processing methods for removing artefacts in the data and improving of the geophysical interpretation are suggested. Scalloping is one major artefact, which significantly degrades the quality of the velocity maps. Two methods, in spatial and spectral domain, for correcting this effect are proposed. It is also found that the radial velocity provided in the Sentinel-1 ocean data is biased, hence land is used as a reference to correct for the absolute and inter-beam bias. Finally, the retrieved (corrected) velocity is compared to a regional ocean circulation model (ROMS). It is shown that there is a good agreement between the ocean model and the retrieved velocity with values of ≈ 0.8 m/s in the core of the NCC.

Using Sentinel-1 Ocean Data for Mapping Sea Surface Currents Along the Southern Norwegian Coast

A novel approach to a Bayesian ocean wind retrieval from high-range bandwidth synthetic aperture radar (SAR) data is demonstrated and validated using global Sentinel-1 (S1) A and B WV data acquired in October 2016 and January 2017. These spectral parameters are defined from the full-resolution image cross spectra. The first parameter is the integral spectral value (ISV) defined as the signed spectral energy at high-range wavenumber. Two other parameters, the azimuth phase plane slope (APPS) and range phase plane slope (RPPS), are the slope of the phase plane from the image cross spectra. Together with the normalized radar cross section (NRCS), these parameters form the input to our data-driven model for ocean wind retrieval. The model is trained on S1B from October 2016 data and validated on S1A and S1B from January 2017 data colocated with European Centre for Medium-Range Weather Forecast (ECMWF) atmospheric wind model as “ground” truth. The APPS proves to be the result of two sinusoidal functions, one symmetric and one antisymmetric, the antisymmetric part is in direct relation with the azimuth wind direction. Our Bayesian model achieves standard deviations of 1.73 m/s and 49.26° for January 2017 S1B data set with a bias of 0.03 m/s and −1.55°, corresponding results for January 2017 S1A data were 1.79 m/s and 49.95° with biases 0.41 m/s and −1.89°. Including data with ECMWF wind speed above 7 m/s we achieve standard deviations of 1.81 m/s and 33.16° with biases 0.1 m/s and −1.31° for the January 2017 S1B data set.

A Novel Approach to SAR Ocean Wind Retrieval

This paper presents a direct comparison of the sea surface radial velocity (RVL) derived from the two satellite SAR systems Sentinel-1 and TanDEM-X, operating at different frequencies and imaging modes. The RVL is derived from the Doppler centroid (Dc) provided in the Sentinel-1 OCN product and from the along-track interferometric phase of the TanDEM-X, respectively. The comparison is performed using an opportunistic collocated acquisition over the Pentland Firth strait, known for its strong tidal stream. This comparison shows that the two SAR systems observe similar sea surface circulation patterns with high spatial correlation coefficient (r ~10.8). It is also shown that, provided a common calibration reference is available, the two independently derived RVL are quantitatively in good agreement with a negligible bias and reasonable RMSE (~10.3 m/s). This encourages use of the synergy between different C- and X-band SAR systems, measuring sea surface velocity.

Comparison of the Sea Surface Velocity Derived from Sentinel-1 and Tandem-X

Synthetic aperture radar (SAR) is the most efficient tool to provide high-resolution data for Earth Observation (EO). Doppler centroid (DC) estimation is indispensable for high precision SAR data analysis such as extracting the ocean surface current, which is important for scientific pursuits. Correlation doppler estimation (CDE), and energy balancing (EB) based DC methods are implemented in this paper. A 2-D sliding window is deployed to estimate DC on small blocks of data while covering the whole scene so that all parts of the scene are potentially represented. We analyzed Sentinel-1 single look complex (SLC) data from the coastline of a non-homogeneous scene. The CDE method utilizes the azimuth shift in the time domain which is associated with the DC, and this $f_{Dc}$ history is used to extract ocean surface current. We find the results of DC estimates are confined to primitive baseband (±PRF/2). Moreover, the corresponding retrieved ocean surface current component is reasonable, particularly values vary within the limit of error bounds. Finally, the parameters of ocean surface current are compared with ocean wave models reported in the literature. Efficacy and simulation of implemented methods are good fit for Sentinel-1 SAR data.

https://zenodo.org/record/6642415/files/Doppler_Centroid_Estimation_for_Ocean_Surface_Current_Retrieval_from_Sentinel-1_SAR_Data.pdf

Doppler Centroid Estimation for Ocean Surface Current Retrieval from Sentinel-1 SAR Data

http://ieeexplore.ieee.org/iel7/6856711/6856712/06857044.pdf

Yngvar Larsen

Papers

Sentinel-1 Geophysical Doppler Product - Performance and Application