Data Set ID: 
NSIDC-0754

MEaSUREs Phase-Based Antarctica Ice Velocity Map, Version 1

This data set, as part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, combines interferometric phases from multiple satellite interferometric synthetic-aperture radar systems to derive the first comprehensive phase-based map of Antarctic ice velocity. The precision in ice speed and flow direction over 80% of Antarctica is better than prior mappings based on feature and speckle tracking by a factor of 10. Phase-derived velocity mostly covers the years between 2007 and 2018, while tracking-derived velocity (for regions along the coasts) is mostly found in the years from 2013 to 2017. Additional data acquired between 1996 and 2018 were used as needed to maximize coverage.

See Antarctic Ice Sheet Velocity and Mapping Data for related data.

This is the most recent version of these data.

Version Summary: 

Initial release

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Parameter(s):
  • SNOW/ICE > ICE VELOCITY
Data Format(s):
  • NetCDF
Spatial Coverage:
N: -60, 
S: -90, 
E: 180, 
W: -180
Platform(s):ALOS, ALOS-2, ENVISAT, ERS-1, ERS-2, LANDSAT-8, RADARSAT-1, RADARSAT-2, SENTINEL-1A, SENTINEL-1B, TDX, TSX
Spatial Resolution:
  • 450 m x 450 m
Sensor(s):ASAR, C-SAR, OLI, PALSAR, PALSAR-2, SAR
Temporal Coverage:
  • 1 January 1996 to 31 December 2018
Version(s):V1
Temporal ResolutionNot applicableMetadata XML:View Metadata Record
Data Contributor(s):Jeremie Mouginot, Eric Rignot, Bernd Scheuchl

Geographic Coverage

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As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.

Mouginot, J., E. Rignot, and B. Scheuchl. 2019. MEaSUREs Phase-Based Antarctica Ice Velocity Map, Version 1. [Indicate subset used]. doi: https://doi.org/10.5067/PZ3NJ5RXRH10. [Date Accessed].

Literature Citation

As a condition of using these data, we request that you acknowledge the author(s) of this data set by referencing the following peer-reviewed publication.

  • Mouginot, J., E. Rignot, and B. Scheuchl. 2019. Continent-wide, interferometric SAR phase-mapping of Antarctic ice velocity, Geophysical Research Letters. . .

Created: 
15 August 2019
Last modified: 
16 October 2019
This map was generated using InSAR phase analysis, which requires SAR data acquired in different directions to be available. The reason for this is that the interferometric phase is only sensitive to motion in look direction; thus, to resolve a 2D flow, the second direction is required. The map was ultimately mixed with a feature and speckle tracking-based map, specifically to cover coastal areas for which the phase technique does not work. The primary motivation of this map was to get a reference (or measurement) for every point of the Antarctic ice sheet; therefore, all available data sets were used over the period described in the documentation. The map is therefore associated with an acquisition period spanning several years, and not with a specific date. Another product which narrows the acquisition date, such as MEaSUREs Annual Antarctic Ice Velocity Maps 2005-2017, is more suitable for such a need. These maps also show the limitation of data availability for the region in question.

Data Description

Parameters

The main parameter in this data set is ice velocity, with associated errors and standard deviations (in m/yr). The variables included in the data file are described in Table 1. All variables are on a two-dimensional grid of 12445 by 12445 cells, except for x and y, which are unidimensional with 12445 cells each.

Table 1. Parameter Information
Parameter Description Units
CNT Scene count, used to estimate the values for each pixel Count
coord_system Coordinate system -
ERRX Ice velocity error in x-direction m/yr
ERRY Ice velocity error in y-direction m/yr
lat Latitude ° N
lon Longitude ° E
SOURCE Data source (0 = no data; 1 = tracking-based; 2 = phase-based; 3 = interpolation-tracking phase) -
STDX Standard deviation of ice velocity in x-direction m/yr
STDY Standard deviation of ice velocity in y-direction m/yr
VX Ice velocity in x-direction m/yr
VY Ice velocity in y-direction m/yr
x Cartesian x-coordinate m
y Cartesian y-coordinate m

Note: To convert the VX and VY ice velocity components into magnitude (speed) and direction (angle), as well as their relative errors, use the following equations (Mouginot et al., 2012):

  1. speed = sqrt (VX2 + VY2)
  2. angle = arctan (VY / VX)
  3. error = sqrt (ERRX2 + ERRY2)
  4. error of flow direction = error / (2*speed)

When computing the inverse tangent, users should take note of the function's inherent ambiguities. While the standard arctan function typically does not account for angles that differ by 180°, most modern computer languages and math software packages include the function ATAN2, which uses the signs of both vector components to place the angle in the proper quadrant.

File Information

Format

This data set includes one data file, antarctic_ice_vel_phase_map_v01.nc. The data file is provided in netCDF-4 (.nc) format, following version 1.6 of the Climate and Forecast (CF) metadata conventions.

File Contents

The velocity components for the x- and y-direction, as defined by the polar stereographic grid, are stored in the netCDF variables VX and VY and are recorded in m/yr. Error estimates for the velocity components are provided as variables ERRX and ERRY; however, these values should be used more as an indication of relative quality rather than absolute error. More information about the error estimates is provided in the Quality, Errors, and Limitations section as well as in Mouginot et al. (2019). The data also include the standard deviations for the velocity estimates (STDX, STDY), a count of scenes (CNT) used to estimate the values for each pixel, and an index denoting the SOURCE of the data, i.e., whether the velocity was estimated via tracking-based method, phase-based method, an interpolation of the two, or is missing altogether.

Spatial Information

Coverage

Spatial coverage includes the continent of Antarctica, namely the entire polar region southwards of 60° S.

Resolution

The spatial resolution of the grid is 450 m by 450 m.

Geolocation

The following table provides information for geolocating this data set.

Table 2. Geolocation Details
Geographic coordinate system WGS 84
Projected coordinate system Antarctic Polar Stereographic
Longitude of true origin
Latitude of true origin 71° S
Scale factor at longitude of true origin 1
Datum WGS 84
Ellipsoid/spheroid WGS 84
Units meters
False easting
False northing
EPSG code 3031
PROJ4 string +proj=stere +lat_0=-90 +lat_ts=-71 +lon_0=0 +k=1 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs
Reference https://epsg.io/3031

Temporal Information

Coverage

The data were collected between 1996 and 2018. Detailed information is provided in the Data Aquisition and Processing section.

Resolution

Not applicable. The maps are an averaged representation of the period in which data were collected.

Data Acquisition and Processing

Background

This data set provides a new map of Antarctic ice velocity that is ten times more precise than prior maps and reveals ice motion at a high precision over 80% of the continent versus 20% in the past. The ice motion vector map provides novel constraints on interior ice motion and its connection with the glaciers and ice streams that control the stability and mass balance of the Antarctic Ice Sheet.

Instrumentation

The ice velocity map was derived from a variety of satellite radar interferometry data from the sensors listed in Table 3.

Table 3. Characteristics of Source Sensors
Platform/Sensor Space Agency Radar Frequency Band (wavelength in cm) Look Direction Mode Repeat Cycle (days) Incidence Angle (°) Resolution Rg x Az (m) Frequency (GHz) Period Used
ERS-1/ERS-2/SAR European Space Agency (ESA) C (5.6) Right N/A 1 or 3 23 13x4 5.33 1992-1996
RADARSAT-1/SAR Canadian Space Agency (CSA) C (5.5) Left/Right Varies 24 18-47 12x5–17x6 5.33 1997–2001
RADARSAT-2/SAR CSA C (5.5) Left S5/EH4 24 41/57 12x5 5.33 2009–2018
ENVISAT/ASAR ESA C (5.6) Right IS2 35 23 13x5 5.33 2006–2010
ALOS/PALSAR Japan Aerospace Exploration Agency (JAXA) L (23.6) Right FBS 46 39 7x4 1.27 2006–2010
ALOS2/PALSAR2 JAXA L (23.6) Right/Left SBS 14 37 3x1 1.27 2015
Sentinel-1/SAR ESA C (5.5) Right IW-TOPS 12 20-46 12x43 5.405 2014–2018
Landsat-8/OLI USGS/NASA N/A N/A Panchromatic 16 N/A 15x15 N/A 2013–2018
TanDEM-X/TerraSAR-X/SAR German Space Agency (DLR) X (3.1) Right N/A 11 46.3 1.4x1.8 9.65 2011–2016

Note: Data from Sentinel-1/SAR, Landsat-8/OLI, and TanDEM-X/TerraSAR-X/SAR were only used for the speckle-tracking analysis, while data from ALOS2/PALSAR2 were only used in the phase analysis. Data from all the other sensors were used in both approaches.

Acquisition and Processing

Several analysis techniques using SAR data were used to generate the velocity maps:

  1. Combination of interferometric phases of two independent tracks to retrieve the surface flow vector (Mouginot et al., 2019), applied to a vast region of Antarctica
  2. Speckle tracking in both along-track (azimuth) and across-track (range) directions, used to augment the phase map in coastal areas (Rignot et al., 2011; Mouginot et al., 2012; Mouginot et al., 2017)
  3. Calculation of two-dimensional offsets in amplitude imagery (Mouginot et al., 2012)
  4. Combinations of (range) interferometric phases along two independent tracks (Mouginot et al., 2012)

In all cases, surface parallel flow is assumed, a conventional approach for ice sheets. The Landsat-8 data are processed using repeat image feature tracking (see Mouginot et al., 2017).

Phase-derived velocities were mostly acquired between 2007 and 2018, while regions covered by tracking-derived velocity (along the coasts) are mostly representative of the years 2013–2017. Additional data acquired between 1996 and 2018 were used as needed to maximize coverage. SAR acquisitions between 2006 and 2018 were coordinated by the International Polar Year (IPY) Space Task Group and its successor, the Polar Space Task Group (PSTG).

Figure 1 shows the distribution of data tracks from different data sources, as well as a complete map of ice motion in Antarctica.

Figure 1. Mapping of ice motion in Antarctica using synthetic-aperture radar interferometric phase data. Upper panels show the distribution of data tracks used from the Canadian RADARSAT-2, Japanese ALOS/PALSAR, European ERS and Canadian RADARSAT-1, and European ENVISAT/ASAR. Lower main panel shows a complete map of ice motion in Antarctica combining phase data in the interior and speckle-tracking in the fast-moving sectors, with speed colored on a logarithmic scale from brown (less than 1 m/yr) to red (more than 3 km/yr) and flow direction indicated by colored lines and showing the flow pattern of ice across the continent (from Mouginot et al., 2019).

The unwrapped phase uses C-Band sensors (~5.5 cm) with 1461 tracks from RADARSAT-1 and RADARSAT-2, 76 tracks from ERS-1 and ERS-2, 319 tracks from ENVISAT/ASAR; and L-Band sensors (~23.6 cm) with 556 tracks from ALOS/PALSAR and 3 tracks from ALOS2/PALSAR2 (Figure 1, top row). The combination of phase and tracking mosaics covers 99.8% of Antarctica (Figure 1, main map), with a significantly improved description of ice flow from the ice divides in the deep interior to the periphery. Figure 2 shows the ice velocity mosaics obtained from each method alone. 

Figure 2. Ice flow in Antarctica from synthetic-aperture radar interferometry using (a) speckle tracking only and (b) interferometric phase only (from Mouginot et al., 2019).

The phase mosaic (Figure 2B) itself does not cover all of Antarctica for two reasons: firstly, the interferometric phase is aliased in areas of fast flow due to the long temporal baseline of the data; and secondly, some sectors do not have sufficient multi-track coverage to provide reliable estimates of the vector ice motion. Overall, the phase-based map covers 71% of Antarctica, or 9.9 million square km, while the tracking-based map (Figure 2A) covers 99.6%, or 13.8 million square km (Mouginot et al., 2017). Figure 3 illustrates how the two mosaics are merged.

Figure 3. Mask showing where phase data (yellow) and speckle tracking data (blue) are applied, with an area of interpolation in between (from Mouginot et al., 2019, Supporting Information).

Quality, Errors, and Limitations

A detailed description of the data and their quality is provided in Mouginot et al. (2019). The precision of ice flow mapping varies with the sensor, the geographic location, the technique of interferometric analysis, the time period of analysis, the repeat cycle, and the amount of data stacking. Overall, there is notable improvement in precision from phase-based mapping relative to tracking-based mapping, which is especially significant along ice divides when examining the error in the flow direction. Figure 4 compares errors estimates for the two methods, for both speed and direction. 

Figure 4. Errors in ice flow speed (top row) and direction (bottom row), as quantified via tracking-based (left column) and phase-based (center column) analyses. Graphics in the right column compare the cumulative distribution of errors in speed (top) and direction (bottom) from both methods (from Mouginot et al., 2019).

Finally, Table 4 provides a phase error for each of the sensors utilized in the phase-based velocity mapping. Note that phase error is determined for a single unwrapped phase using the nominal repeat cycle and assuming a conservative error of π radians (½ cycle) (Mouginot et al., 2019).

Table 4. Phase Error by Source Sensor
Platform/Sensor Number of Unwrapped Phases Phase Error (m/yr)
ERS-1/ERS-2/SAR 76 5.11 or 1.70
RADARSAT-1/SAR 265 0.21
RADARSAT-2/SAR 1196 0.21
ENVISAT/ASAR 319 0.15
ALOS/PALSAR 556 0.47
ALOS2/PALSAR2 3 1.79
Composite Phase / Speckle Tracking Map N/A 0.15-0.2

Software and Tools

Unidata at the University Corporation for Atmospheric Research maintains an extensive list of freely available Software for Manipulating or Displaying NetCDF Data.

Related Data Sets

Related Websites

Contacts and Acknowledgments

Investigators:

Dr. Jeremie Mouginot1,2
1University of California, Irvine
Department of Earth System Science
Croul Hall
Irvine, California 92697
USA

2Institut des Géosciences de l’Environnement (IGE)
Université Grenoble Alpes
France

Dr. Eric Rignot
University of California, Irvine
Department of Earth System Science
Croul Hall
Irvine, California 92697
USA

Dr. Bernd Scheuchl
University of California, Irvine
Department of Earth System Science
Croul Hall
Irvine, California 92697
USA

Acknowledgments:

These data were generated through a grant from the NASA MEaSUREs program. Spaceborne Synthetic Aperture Radar (SAR) acquisitions were provided through the following data agencies:

  • ALOS PALSAR, ALOS-2/PALSAR-2: Japan Aerospace Exploration Agency (JAXA)
  • ENVISAT ASAR, ERS-1, ERS-2: European Space Agency (ESA)
  • Sentinel-1: Copernicus/ESA
  • RADARSAT-1, RADARSAT-2: Canadian Space Agency (CSA), MDA
  • TerraSAR-X, TanDEM-X as well as the TanDEM-X DEM of Antarctica: German Space Agency (DLR)
  • Landsat-8 (optical): made available by the United States Geological Survey (USGS).

Data acquisitions made between 2006 and 2018 are courtesy of the International Polar Year (IPY) Space Task Group and its successor, the Polar Space Task Group (PSTG). This data set contains modified Copernicus Sentinel data (2014–2017), acquired by the European Space Agency, distributed through the Alaska Satellite Facility, and processed by E. Rignot, J. Mouginot, and B. Scheuchl.

References

  • Rignot, E., Mouginot, J., & Scheuchl, B. (2011). Ice Flow of the Antarctic Ice Sheet. Science, 333(6048), 1427–1430. https://doi.org/10.1126/science.1208336
  • Mouginot, J., Scheuchl, B., & Rignot, E. (2012). Mapping of Ice Motion in Antarctica Using Synthetic-Aperture Radar Data. Remote Sensing, 4(9), 2753–2767. https://doi.org/10.3390/rs4092753
  • Scheuchl, B., Mouginot, J., & Rignot, E. (2012). Ice velocity changes in the Ross and Ronne sectors observed using satellite radar data from 1997 and 2009. The Cryosphere, 6(5), 1019–1030. https://doi.org/10.5194/tc-6-1019-2012
  • Mouginot, J., Rignot, E., & Scheuchl, B. (2014). Sustained increase in ice discharge from the Amundsen Sea Embayment, West Antarctica, from 1973 to 2013. Geophysical Research Letters, 41(5), 1576–1584. https://doi.org/10.1002/2013gl059069
  • Mouginot, J., Rignot, E., Scheuchl, B., & Millan, R. (2017). Comprehensive Annual Ice Sheet Velocity Mapping Using Landsat-8, Sentinel-1, and RADARSAT-2 Data. Remote Sensing, 9(4), 364. https://doi.org/10.3390/rs9040364
  • Mouginot, J., Rignot, E., & Scheuchl, B. (2019). Continent‐wide, interferometric SAR phase, mapping of Antarctic ice velocity. Geophysical Research Letters. https://doi.org/10.1029/2019gl083826
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