Improving Sea Ice Drift Retrieval from SAR Images Using Phase- and Cross-Correlation Techniques

2020 ◽  
Author(s):  
Denis M. Demchev ◽  
Victoria V. Kharchenko ◽  
Olga M. Andeeva ◽  
Petr V. Korobov ◽  
Leif E. B. Eriksson
Keyword(s):  
Sea Ice ◽  
Cross Correlation ◽  
Sar Images ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Correlation Techniques

Oceanic eddy signature on SAR-derived sea ice drift and vorticity

2021 ◽  
Author(s):  
Angelina Cassianides ◽  
Camillie Lique ◽  
Anton Korosov
Keyword(s):  
Sea Ice ◽  
Surface Current ◽  
Satellite Observation ◽  
The Arctic ◽  
Global Ocean ◽  
Sar Images ◽  
Surface Ocean ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Oceanic Eddy

<p>In the global ocean, mesoscale eddies are routinely observed from satellite observation. In the Arctic Ocean, however, their observation is impeded by the presence of sea ice, although there is a growing recognition that eddy may be important for the evolution of the sea ice cover. In this talk, we will present a new method of surface ocean eddy detection based on their signature in sea ice vorticity retrieved from Synthetic Aperture Radar (SAR) images. A combination of Feature Tracking and Pattern Matching algorithm is used to compute the sea ice drift from pairs of SAR images. We will mostly focus on the case of one eddy in October 2017 in the marginal ice zone of the Canadian Basin, which was sampled by mooring observations, allowing a detailed description of its characteristics. Although the eddy could not be identified by visual inspection of the SAR images, its signature is revealed as a dipole anomaly in sea ice vorticity, which suggests that the eddy is a dipole composed of a cyclone and an anticyclone, with a horizontal scale of 80-100 km and persisted over a week. We will also discuss the relative contributions of the wind and the surface current to the sea ice vorticity. We anticipate that the robustness of our method will allow us to detect more eddies as more SAR observations become available in the future.</p>

scholarly journals Operational SAR-based sea ice drift monitoring over the Baltic Sea

Ocean Science ◽  
2012 ◽  
Vol 8 (4) ◽  
pp. 473-483 ◽  
Author(s):  
J. Karvonen
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Vector Fields ◽  
Phase Correlation ◽  
The Baltic Sea ◽  
Sar Images ◽  
Envisat Asar ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
The Baltic

Abstract. An algorithm for computing ice drift from pairs of synthetic aperture radar (SAR) images covering a common area has been developed at FMI. The algorithm has been developed based on the C-band SAR data over the Baltic Sea. It is based on phase correlation in two scales (coarse and fine) with some additional constraints. The algorithm has been running operationally in the Baltic Sea from the beginning of 2011, using Radarsat-1 ScanSAR wide mode and Envisat ASAR wide swath mode data. The resulting ice drift fields are publicly available as part of the MyOcean EC project. The SAR-based ice drift vectors have been compared to the drift vectors from drifter buoys in the Baltic Sea during the first operational season, and also these validation results are shown in this paper. Also some navigationally useful sea ice quantities, which can be derived from ice drift vector fields, are presented.

scholarly journals Performance of a multiscale correlation algorithm for the estimation of sea-ice drift from SAR images: initial results

2011 ◽  
Vol 52 (57) ◽  
pp. 311-317 ◽  
Author(s):  
Thomas Hollands ◽  
Wolfgang Dierking
Keyword(s):  
Sea Ice ◽  
Displacement Vector ◽  
Winter Season ◽  
Image Resolution ◽  
Displacement Fields ◽  
Sar Images ◽  
High Entropy ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Ice Conditions

AbstractSea-ice drift fields were obtained from sequences of synthetic aperture radar (SAR) images using a method based on pattern recognition. the accuracy of the method was estimated for two image products of the Envisat Advanced SAR (ASAR) with 25 m and 150 m pixel size. For data from the winter season it was found that 99% of the south–north and west–east components of the determined displacement vector are within ±3–5 pixels of a manually derived reference dataset, independent of the image resolution. For an image pair with 25 m resolution acquired during summer, the corresponding value is 12 pixels. Using the same resolution cell dimensions for the displacement fields in both image types, the estimated displacement components differed by 150–300 m. the use of different texture parameters for predicting the performance of the algorithm dependent on ice conditions and image characteristics was studied. It was found that high entropy values indicate a good performance.

scholarly journals Comparing SAR-Based Short Time-Lag Cross Correlation and Doppler-Derived Sea Ice Drift Velocities

2018 ◽  
Vol 56 (4) ◽  
pp. 1898-1908 ◽  
Author(s):  
Thomas Kramer ◽  
Harald Johnsen ◽  
Camilla Brekke ◽  
Geir Engen
Keyword(s):  
Sea Ice ◽  
Cross Correlation ◽  
Time Lag ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Short Time

Sea Ice Drift Tracking From Sequential SAR Images Using Accelerated-KAZE Features

2017 ◽  
Vol 55 (9) ◽  
pp. 5174-5184 ◽  
Author(s):  
Denis Demchev ◽  
Vladimir Volkov ◽  
Eduard Kazakov ◽  
Pablo F. Alcantarilla ◽  
Stein Sandven ◽  
...  
Keyword(s):  
Sea Ice ◽  
Sar Images ◽  
Ice Drift ◽  
Sea Ice Drift

scholarly journals Assessment of error in satellite derived lead fraction in Arctic

2015 ◽  
Vol 9 (6) ◽  
pp. 6315-6344
Author(s):  
N. Ivanova ◽  
P. Rampal ◽  
S. Bouillon
Keyword(s):  
Sea Ice ◽  
Sar Images ◽  
Earth Observing System ◽  
Full Dataset ◽  
Original Dataset ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Climate Parameter ◽  
Ice Model ◽  
Ice Control

Abstract. Leads within consolidated sea ice control heat exchange between the ocean and the atmosphere during winter thus constituting an important climate parameter. These narrow elongated features occur when sea ice is fracturing under the action of wind and currents, reducing the local mechanical strength of the ice cover, which in turn impact the sea ice drift patterns. This makes a high quality lead fraction (LF) dataset to be in demand for sea ice model evaluation, initialization and for assimilation of such data in regional models. In this context, the available LF dataset retrieved from satellite passive microwave observations (Advanced Microwave Scanning Radiometer – Earth Observing System, AMSR-E) is of great value, providing pan-Arctic light- and cloud-independent daily coverage since 2002. Here we quantify errors in this dataset using accurate LF estimates retrieved from Synthetic Aperture Radar (SAR) images employing a threshold technique, also introduced in this work. We find a consistent overestimation by a factor of 2–4 of the LF estimates in the AMSR-E LF product. We show for a data sample from the AMSR-E LF dataset that a simple adjustment of the tie points used in the method to estimate the LF can reduce the pixel-wise error by a factor of 2 on average. Applying such adjustment to the full dataset may thus significantly increase the quality and value of the original dataset.

scholarly journals Sea ice drift and arch evolution in the Robeson Channel using the daily coverage of Sentinel-1 SAR data for the 2016–2017 freezing season

2020 ◽  
Vol 14 (11) ◽  
pp. 3611-3627
Author(s):  
Mohammed E. Shokr ◽  
Zihan Wang ◽  
Tingting Liu
Keyword(s):  
Sea Ice ◽  
Sea Water ◽  
Linear Trend ◽  
Ice Cover ◽  
The Arctic ◽  
Sar Images ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Ice Floes

Abstract. The Robeson Channel is a narrow sea water passage between Greenland and Ellesmere Island in the Arctic. It is a pathway of sea ice from the central Arctic and out to Baffin Bay. In this study, we used a set of daily synthetic aperture radar (SAR) images from the Sentinel-1A/1B satellites, acquired between September 2016 and April 2017, to study the kinematics of individual ice floes as they approach and then drift through the Robeson Channel. The tracking of 39 selected ice floes was visually performed in the image sequence, and their speed was calculated and linked to the reanalysis 10 m wind from ERA5. The results show that the drift of ice floes is very slow in the compact ice regime upstream of the Robeson Channel, unless the ice floe is surrounded by water or thin ice. In this case, the wind has more influence on the drift. On the other hand, the ice floe drift is found to be about 4–5 times faster in the open-drift regime within the Robeson Channel and is clearly influenced by wind. A linear trend is found between the change in wind and the change in ice drift speed components, along the length of the channel. Case studies are presented to reveal the role of wind in ice floe drift. This paper also addresses the development of the ice arch at the entry of the Robeson Channel, which started development on 24 January and matured on 1 February 2017. Details of the development, obtained using the sequential SAR images, are presented. It is found that the arch's shape continued to adjust by rupturing ice pieces at the locations of cracks under the influence of the southward wind (and hence the contour kept displacing northward). The findings of this study highlight the advantage of using the high-resolution daily SAR coverage in monitoring aspects of sea ice cover in narrow water passages where the ice cover is highly dynamic. The information will be particularly interesting for the possible applications of SAR constellation systems.

scholarly journals Error assessment of satellite-derived lead fraction in the Arctic

2016 ◽  
Vol 10 (2) ◽  
pp. 585-595 ◽  
Author(s):  
Natalia Ivanova ◽  
Pierre Rampal ◽  
Sylvain Bouillon
Keyword(s):  
Sea Ice ◽  
Original Data ◽  
The Arctic ◽  
Full Data ◽  
Sar Images ◽  
Data Set ◽  
Earth Observing System ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Climate Parameter

Abstract. Leads within consolidated sea ice control heat exchange between the ocean and the atmosphere during winter, thus constituting an important climate parameter. These narrow elongated features occur when sea ice is fracturing under the action of wind and currents, reducing the local mechanical strength of the ice cover, which in turn impact the sea ice drift pattern. This creates a high demand for a high-quality lead fraction (LF) data set for sea ice model evaluation, initialization, and for the assimilation of such data in regional models. In this context, an available LF data set retrieved from satellite passive microwave observations (Advanced Microwave Scanning Radiometer – Earth Observing System, AMSR-E) is of great value, which has been providing pan-Arctic light- and cloud-independent daily coverage since 2002. In this study errors in this data set are quantified using accurate LF estimates retrieved from Synthetic Aperture Radar (SAR) images employing a threshold technique. A consistent overestimation of LF by a factor of 2–4 is found in the AMSR-E LF product. It is shown that a simple adjustment of the upper tie point used in the method to estimate the LF can reduce the pixel-wise error by a factor of 2 on average. Applying such an adjustment to the full data set may thus significantly increase the quality and value of the original data set.

scholarly journals Operational SAR-based sea ice drift monitoring over the Baltic Sea

2012 ◽  
Vol 9 (1) ◽  
pp. 359-384 ◽  
Author(s):  
J. Karvonen
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Vector Fields ◽  
Phase Correlation ◽  
The Baltic Sea ◽  
Sar Images ◽  
Envisat Asar ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
The Baltic

Abstract. An algorithm for computing ice drift from pairs of synthetic aperture radar (SAR) images covering a common area has been developed at FMI. The algorithm has been developed based on the C-band SAR data over the Baltic Sea. It is based on phase correlation in two scales (coarse and fine) with some additional constraints. The algorithm has been running operationally in the Baltic Sea from the beginning of 2011, using Radarsat-1 ScanSAR wide mode and Envisat ASAR wide swath mode data. The resulting ice drift fields are publicly available as part of the MyOcean EC project. The SAR based ice drift vectors have been compared to the drift vectors from drifter buoys in the Baltic Sea during the first operational season and also these validation results are shown in this paper. Also some navigationally useful sea ice quantities, which can be derived from ice drift vector fields, are presented.

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