Use of L- and C-Band SAR Satellites for Sea Ice and Iceberg Monitoring (LC-ICE)

2021 ◽  
Author(s):  
Wolfgang Dierking ◽  
Malcolm Davidson
Keyword(s):  
Sea Ice ◽  
Advisory Group ◽  
Automated Classification ◽  
Sar Images ◽  
Mutual Cooperation ◽  
Current State ◽  
L Band ◽  
Sar Imagery ◽  
Using Data ◽  
Wide Swath

<p>In support of ESA's Mission Advisory Group for ROSE-L (Radar Observing System for Europe at L-band), a project team consisting of members of operational ice services and the International Ice Charting Working Group,  the International Ice Patrol, and groups from universities and research institutes is investigating the benefits of using data from L-band SAR in addition to C-band SAR imagery for separating different sea ice classes and detecting icebergs. The tasks are: (1) a critical assessment of the current state-of-the-art in sea ice monitoring and iceberg detection, (2) matching C- and L-band SAR images acquired with temporal gaps of several hours, (3) tests and assessments of the practical use of L-band images in the operational mapping services, and (4) comparison of classification accuracies that can be achieved at C-band, L-band, and a combination of both, based on the results of automated segmentation and classification algorithms. Based on the suggestions of operational ice centers, data have been collected since April 2019 over six test sites for the Northern Hemisphere: Fram Strait, Belgica Bank, northern and southern parts of Greenland, Baffin Bay and Labrador Sea. The SAR images are acquired by Sentinel-1 at Extra Wide and Interferomeric Wide Swath modes, by RADARSAT-2 at ScanSAR mode, and by ALOS-2 PALSAR-2 at Wide Beam and Fine Beam modes. The PALSAR-2 data are provided through the 2019 to 2022 mutual cooperation project between ESA and JAXA on using SAR data in earth sciences and applications. The presentation - with contributions from project partners - will focus on the conclusions from the literature review, assessments of operational ice services regarding the gain they find in using L-band SAR images supplementary to routinely analyzed C-band imagery, and preliminary results of automated classification. </p>

scholarly journals Comparing C- and L-band SAR images for sea ice motion estimation

2014 ◽  
Vol 8 (3) ◽  
pp. 2721-2757
Author(s):  
J. Lehtiranta ◽  
S. Siiriä ◽  
J. Karvonen
Keyword(s):  
Motion Estimation ◽  
Sea Ice ◽  
Cross Correlation ◽  
Correlation Technique ◽  
Sar Images ◽  
L Band ◽  
Sar Imagery ◽  
The Baltic ◽  
Cross Correlation Technique ◽  
Multiyear Ice

Abstract. Pairs of consecutive C-band SAR images are routinely used for sea ice motion estimation. In addition to the surface roughness L-band SAR imagery provides information of the seasonal sea ice inner structure, which is especially useful in the Baltic Sea lacking multiyear ice and icebergs. In this work, L-band SAR images are investigated for sea ice motion estimation using the well-established maximal cross-correlation approach. This work provides the first comparison of L-band and C-band SAR images for the purpose of motion estimation. The cross-correlation calculations are hardware accelerated using new OpenCL-based source code, which is made available through the author's web site. It is found that L-band images are preferable for motion estimation over C-band images. It is also shown that motion estimation is possible between a C-band and an L-band image using the maximal cross-correlation technique.

scholarly journals Comparing C- and L-band SAR images for sea ice motion estimation

2015 ◽  
Vol 9 (1) ◽  
pp. 357-366 ◽  
Author(s):  
J. Lehtiranta ◽  
S. Siiriä ◽  
J. Karvonen
Keyword(s):  
Motion Estimation ◽  
Sea Ice ◽  
Cross Correlation ◽  
Correlation Technique ◽  
Sar Images ◽  
L Band ◽  
The Baltic ◽  
Cross Correlation Technique ◽  
Multiyear Ice ◽  
Band Image

Abstract. Pairs of consecutive C-band synthetic-aperture radar (SAR) images are routinely used for sea ice motion estimation. The L-band radar has a fundamentally different character, as its longer wavelength penetrates deeper into sea ice. L-band SAR provides information on the seasonal sea ice inner structure in addition to the surface roughness that dominates C-band images. This is especially useful in the Baltic Sea, which lacks multiyear ice and icebergs, known to be confusing targets for L-band sea ice classification. In this work, L-band SAR images are investigated for sea ice motion estimation using the well-established maximal cross-correlation (MCC) approach. This work provides the first comparison of L-band and C-band SAR images for the purpose of motion estimation. The cross-correlation calculations are hardware accelerated using new OpenCL-based source code, which is made available through the author's web site. It is found that L-band images are preferable for motion estimation over C-band images. It is also shown that motion estimation is possible between a C-band and an L-band image using the maximal cross-correlation technique.

Early detection of the Weddell polynya re-opening using SAR imagery

2020 ◽  
Author(s):  
Adriano Lemos ◽  
Céline Heuzé
Keyword(s):  
Early Detection ◽  
Sea Ice ◽  
Open Water ◽  
Weddell Sea ◽  
Small Scale ◽  
Ice Thickness ◽  
Sar Images ◽  
Sea Ice Thickness ◽  
Sar Imagery ◽  
Microwave Sensors

<p>The sea ice thickness in the Weddell Sea during the austral winter normally exceeds 1 m, but in the case of a polynya, this thickness decreases to 10 cm or less. There are two theories as to why the Weddell Polynya opens: 1) comparatively warm oceanic water upwelling from its nominal depth of several hundred metres to the surface where it melts the sea ice from underneath; or 2) opening of a lead by a passing storm, lead which will then be maintained open either by the atmosphere or ocean and grow. The objective of this study is to estimate how long in advance the recent Weddell Polynya opening could have been detected by synthetic aperture radar (SAR) images due to the decrease of the sea ice thickness and/or early appearance of leads. We use high temporal and spatial resolution SAR images from the Sentinel-1 constellation (C-band) and ALOS2 (L-band) during the austral winters 2014-2018. We use an adapted version of the algorithm developed by Aldenhoff et al. (2018) to monitor changes in sea ice thickness over the polynya region. The algorithm detects the transition of the sea ice thickness through changes in small scale surface roughness and thus reduced backscatter, and allowing us to distinguish three different categories: ice, thin ice, and open water. The transition from ice to thin ice and then to open water indicates that the polynya is melted from under, whereas a direct transition from ice to open water will reveal leads. The high resolution and good coverage of the SAR imagery, and a combined effort of different satellites sensors (e.g. infrared and microwave sensors), opens the possibility of an early detection of Weddell Polynya opening.</p>

Winter navigation in the Northern Sea Route using RADARSAT data

Polar Record ◽  
2000 ◽  
Vol 36 (199) ◽  
pp. 335-344 ◽  
Author(s):  
Vitali Yu. Alexandrov ◽  
Stein Sandven ◽  
Ola M. Johannessen ◽  
Lasse H. Pettersson ◽  
Øyvind Dalen
Keyword(s):  
Sea Ice ◽  
Kara Sea ◽  
Pixel Size ◽  
Large Area ◽  
Sar Images ◽  
Northern Sea Route ◽  
Ice Conditions ◽  
Ice Navigation ◽  
Near Future ◽  
Wide Swath

AbstractThe results are presented of the first winter ice navigation demonstration, using synthetic aperture radar (SAR) images from the Canadian satellite RADARSAT, onboard the nuclear icebreaker Sovetskiy Soyuz in the Kara Sea region in April–May 1998. While ERS SAR data only could cover part of the sea ice in this large area, the demonstration showed that RADARSAT ScanSAR images with 100 m pixel size could be used to map all relevant ice areas with a few 500 × 500 km scenes. SAR images transferred onboard icebreakers in near real time offer an excellent possibility to select optimal sailing routes in difficult ice conditions such as those that were encountered by this expedition. SAR images were also used for planning of operations prior to the expedition. This study compares sub-satellite sea-ice observations with RADARSAT SAR as well as Okean side-looking radar (SLR) signatures of the major ice types and features found in the Kara Sea during winter. Wide-swath SAR images will become available from several new satellites in the near future, such as Envisat, scheduled in 2001, and RADARSAT-2, in 2002. Satellite SAR images will therefore play an increasingly important role in operational ice monitoring both in the Northern Sea Route and in other ice areas.

ALOS-2/PALSAR-2 dual-polarized L-band data for sea ice parameter estimation and sea ice classification 

2021 ◽  
Author(s):  
Juha Karvonen
Keyword(s):  
Parameter Estimation ◽  
Sea Ice ◽  
Sea Ice Concentration ◽  
Sea Ice Thickness ◽  
Ice Concentration ◽  
Sea Ice Drift ◽  
L Band ◽  
Sar Data ◽  
Dual Polarized ◽  
Sar Imagery

<p>This research is related to the JAXA 6th Research Announcement for the Advanced Land<br>Observing Satellite-2 (ALOS-2) project "Improved Sea Ice Parameter Estimation with L-Band SAR (ISIPELS)".<br>In the study ALOS-2/PALSAR-2 dual-polarized Horizontal-transmit-Horizontal-receive/<br>Horizontal-transmit-Vertical-receive (HH/HV) ScanSAR mode L-band  Synthetic Aperture Radar (SAR) imagery<br>over an Arctic study area were evaluated for their suitability for operational sea ice monitoring.<br>The SAR data consisting of about 140 HH/HV ScanSAR ALOS-2/PALSAR-2 images were acquired during the winter 2017.<br>These L-band SAR data were studied for estimation of different sea ice parameters:<br>sea ice concentration, sea ice thickness, sea ice type, sea ice drift. Also some comparisons with nearly<br>coincident C-band data over the same study area have been made. The results indicate that L-band<br>SAR data from ALOS-2/PALSAR-2 are very useful for estimating the studied sea ice parameters and equally good<br>or better than using the conventional operational dual-polarized C-band SAR satellite data.</p><p> </p>

scholarly journals The Separation of Sea-Ice Types in Radar Imagery (Abstract)

1987 ◽  
Vol 9 ◽  
pp. 247-247
Author(s):  
Benjamin Holt ◽  
F.D. Carsey
Keyword(s):  
Surface Morphology ◽  
Sea Ice ◽  
Open Water ◽  
Classification Algorithm ◽  
First Year ◽  
Volume Scattering ◽  
Radar Imagery ◽  
L Band ◽  
Sar Imagery ◽  
Scale Surface

The ability to distinguish the several major types of sea ice with active radar instruments has been well studied in recent years. The separation of sea-ice types by radar results principally from variations in radar back-scatter due to characteristic differences of these ice types in surface morphology and brine content. When sea ice is viewed with an active radar at angles greater than about 20° from nadir, undeformed ice reflects radar waves and results in a low return, while ridges, hummocks, and small-scale surface features scatter the radar waves and produce a high return. The presence of salt increases the dielectric constant of ice; penetration by radar into the ice is then negligible, and the return is essentially determined by surface morphology. The absence of salt reduces the dielectric properties of ice; radar waves can then penetrate the ice to some depth and are scattered by air bubbles and brine-drainage channels (called volume scattering), thereby enhancing the return even for roughened surfaces. All these properties vary significantly with radar frequency and polarization as well as seasonally. For example, higher radar frequencies respond to smaller-scale surface features, while lower radar frequencies penetrate further into the ice with resulting volume scattering.The high-resolution imagery from synthetic aperture radars (SAR), mounted on aircraft, shuttle, or satellite platforms, is very effective for many sea-ice studies, including the separation of ice types. An aircraft-mounted X-band (9 GHz) SAR, for example, can discriminate smooth first-year ice, rough first-year ice, multi-year ice, and open water by the intensity (tone) of the radar returns and floe geometry. The preferred SARs to date for satellites and shuttle platforms have been L-band (1–2 GHz) systems. SAR imagery of sea ice was extensively acquired by Seasat in 1978 over the Beaufort Sea, with limited quantities obtained by the Shuttle Imaging Radar (SIR-B) over the Weddell Sea in 1984. While L-band SAR can discriminate rough and smooth ice along with roughened open water based on image intensity and floe geometry, the returns from thick first-year ice and multi-year ice are not clearly distinguishable. The fact that there is volume scattering from multi-year ice suggests that there may be textural or spatial frequency variations that could be used to separate these two major ice types in radar imagery. In order to investigate the separation of sea-ice types in the large amount of L-band SAR imagery available, image-analysis techniques including filtering and classification programs have been utilized, pointing towards an automatic classification algorithm for use in future SAR sea-ice data sets, especially from space.An important characteristic of all SAR imagery is the presence of image speckle, a coherent form of noise caused by the random variability of scatterers across even a uniform surface. Most SAR processors reduce this effect by averaging multiple independent samples but this is done at the cost of reducing resolution. Speckle reduction can also be accomplished by filtering. Several filters have been tested including median, box, and adaptive edge filters. Each filter has different characteristics in terms of smoothing speckle and in the response to sharp gradients or edges, such as ridge or lead openings, as well as computational requirements. Optimization of each filter’s parameters has been determined by the quality of classification of each ice type.The classification programs that have been tested are based on tone and texture image characteristics. The programs are supervised; that is, a small training area for each class is pre-selected for statistical analysis. From these statistics, the remainder of the imagery is subjected to the particular classification algorithm. The tone program separates classes based on the mean, standard deviation, and number of standard deviations of each class, and includes a Bayesian maximum-likelihood classifier for ambiguous elements. The texture program determines the statistical homogeneity of each class and the optimal segmentation of each small area into the various classes.

scholarly journals The Separation of Sea-Ice Types in Radar Imagery (Abstract)

1987 ◽  
Vol 9 ◽  
pp. 247
Author(s):  
Benjamin Holt ◽  
F.D. Carsey
Keyword(s):  
Surface Morphology ◽  
Sea Ice ◽  
Open Water ◽  
Classification Algorithm ◽  
First Year ◽  
Volume Scattering ◽  
Radar Imagery ◽  
L Band ◽  
Sar Imagery ◽  
Scale Surface

The ability to distinguish the several major types of sea ice with active radar instruments has been well studied in recent years. The separation of sea-ice types by radar results principally from variations in radar back-scatter due to characteristic differences of these ice types in surface morphology and brine content. When sea ice is viewed with an active radar at angles greater than about 20° from nadir, undeformed ice reflects radar waves and results in a low return, while ridges, hummocks, and small-scale surface features scatter the radar waves and produce a high return. The presence of salt increases the dielectric constant of ice; penetration by radar into the ice is then negligible, and the return is essentially determined by surface morphology. The absence of salt reduces the dielectric properties of ice; radar waves can then penetrate the ice to some depth and are scattered by air bubbles and brine-drainage channels (called volume scattering), thereby enhancing the return even for roughened surfaces. All these properties vary significantly with radar frequency and polarization as well as seasonally. For example, higher radar frequencies respond to smaller-scale surface features, while lower radar frequencies penetrate further into the ice with resulting volume scattering. The high-resolution imagery from synthetic aperture radars (SAR), mounted on aircraft, shuttle, or satellite platforms, is very effective for many sea-ice studies, including the separation of ice types. An aircraft-mounted X-band (9 GHz) SAR, for example, can discriminate smooth first-year ice, rough first-year ice, multi-year ice, and open water by the intensity (tone) of the radar returns and floe geometry. The preferred SARs to date for satellites and shuttle platforms have been L-band (1–2 GHz) systems. SAR imagery of sea ice was extensively acquired by Seasat in 1978 over the Beaufort Sea, with limited quantities obtained by the Shuttle Imaging Radar (SIR-B) over the Weddell Sea in 1984. While L-band SAR can discriminate rough and smooth ice along with roughened open water based on image intensity and floe geometry, the returns from thick first-year ice and multi-year ice are not clearly distinguishable. The fact that there is volume scattering from multi-year ice suggests that there may be textural or spatial frequency variations that could be used to separate these two major ice types in radar imagery. In order to investigate the separation of sea-ice types in the large amount of L-band SAR imagery available, image-analysis techniques including filtering and classification programs have been utilized, pointing towards an automatic classification algorithm for use in future SAR sea-ice data sets, especially from space. An important characteristic of all SAR imagery is the presence of image speckle, a coherent form of noise caused by the random variability of scatterers across even a uniform surface. Most SAR processors reduce this effect by averaging multiple independent samples but this is done at the cost of reducing resolution. Speckle reduction can also be accomplished by filtering. Several filters have been tested including median, box, and adaptive edge filters. Each filter has different characteristics in terms of smoothing speckle and in the response to sharp gradients or edges, such as ridge or lead openings, as well as computational requirements. Optimization of each filter’s parameters has been determined by the quality of classification of each ice type. The classification programs that have been tested are based on tone and texture image characteristics. The programs are supervised; that is, a small training area for each class is pre-selected for statistical analysis. From these statistics, the remainder of the imagery is subjected to the particular classification algorithm. The tone program separates classes based on the mean, standard deviation, and number of standard deviations of each class, and includes a Bayesian maximum-likelihood classifier for ambiguous elements. The texture program determines the statistical homogeneity of each class and the optimal segmentation of each small area into the various classes.

scholarly journals In-Orbit Validation of the FMPL-2 Instrument—The GNSS-R and L-Band Microwave Radiometer Payload of the FSSCat Mission

2020 ◽  
Vol 13 (1) ◽  
pp. 121
Author(s):  
Joan Francesc Munoz-Martin ◽  
Lara Fernandez ◽  
Adrian Perez ◽  
Joan Adrià Ruiz-de-Azua ◽  
Hyuk Park ◽  
...  
Keyword(s):  
Sea Ice ◽  
Microwave Radiometer ◽  
Data Sets ◽  
The North ◽  
Moderate Resolution ◽  
L Band ◽  
Temporal And Spatial ◽  
Synchronous Orbit ◽  
Using Data ◽  
Better Than

The Flexible Microwave Payload-2 is the GNSS-R and L-band Microwave Radiometer Payload on board 3Cat-5/A, one of the two 6-unit CubeSats of the FSSCat mission, which were successfully launched on 3 September 2020 on Vega flight VV16. The instrument occupies nearly a single unit of the CubeSat, and its goal is to provide sea-ice extension and thickness over the poles, and soil moisture maps at low-moderate resolution over land, which will be downscaled using data from Cosine Hyperscout-2 on board 3Cat-5/B. The spacecrafts are in a 97.5° inclination Sun-synchronous orbit, and both the reflectometer and the radiometer have been successfully executed and validated over both the North and the South poles. This manuscript presents the results and validation of the first data sets collected by the instrument during the first two months of the mission. The results of the validation are showing a radiometric accuracy better than 2 K, and a sensitivity lower than the Kelvin. For the reflectometer, the results are showing that the sea-ice transition can be estimated even at short integration times (40 ms). The presented results shows the potential for Earth Observation missions based on CubeSats, which temporal and spatial resolution can be further increased by means of CubeSat constellations.

Sign in / Sign up

Export Citation Format

Share Document