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Data Set ID:
NSIDC-0484

MEaSUREs InSAR-Based Antarctica Ice Velocity Map, Version 2

This data set, as part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, provides the first comprehensive, high-resolution, digital mosaics of ice motion in Antarctica assembled from multiple satellite interferometric synthetic-aperture radar systems. Data was largely acquired during the International Polar Year 2007 to 2009, as well as between 2013 and 2016. Additional data acquired between 1996 and 2016 was used as needed to maximize coverage.

For more information on version 2, please refer to the Version Summary.

Version Summary:

Version 2 includes data acquired from 2011-2016 from RADARSAT-2, Sentinel-1, TerraSAR-X (TSX), and TanDEM-X (TDX). Landsat-8 optical imagery also was integrated into the data to improve coverage. The mosaicking method was updated to make best use of the large number of scenes used for the mosaic. In addition, several new parameters are included for assessing the quality of the data including: the standard deviation of vx and vy for each pixel and count of scenes used for each pixel.

In version 2, coverage increased from 95.1% to 99.6% and a reduction in error was achieved due to the utilization of more data.

Geographic Coverage

Parameter(s):
  • Snow/Ice > Ice Velocity
Spatial Coverage:
  • N: -60, S: -90, E: 180, W: -180

Spatial Resolution:
  • 450 m x 450 m
Temporal Coverage:
  • 1 January 1996 to 31 December 2016
Temporal Resolution: 240 month
Data Format(s):
  • NetCDF
Platform(s) ALOS, ENVISAT, ERS-1, ERS-2, Landsat 8, RADARSAT-1, RADARSAT-2, SENTINEL-1A, TDX, TSX
Sensor(s): ASAR, OLI, PALSAR, SAR
Version: V2
Data Contributor(s): Eric Rignot, Jeremie Mouginot, Bernd Scheuchl
Data Citation

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.

Rignot, E., J. Mouginot, and B. Scheuchl. 2017. MEaSUREs InSAR-Based Antarctica Ice Velocity Map, Version 2. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/D7GK8F5J8M8R. [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.

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Detailed Data Description

Format

The data are formatted in Network Common Data Form, Version 4 (NetCDF-4) (.nc) following version 1.6 of the Climate and Forecast (CF) metadata conventions. For more information about working with NetCDF formatted data, visit the UCAR Unidata Network Common Data Form Web site.

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File and Directory Structure

Data are available on the HTTPS site in the https://daacdata.apps.nsidc.org/DATASETS/nsidc0484_MEASURES_antarc_vel_v02/ directory.

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File Naming Convention

This data set includes one file named antarctica_ice_velocity_450m_v2.nc (450 m grid spacing).

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File Size

The size of this data set is approximately 4 GB.

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Spatial Coverage

The data set spans the continent of Antarctica. Figure 1 provides a map of the spatial coverage.

Southernmost Latitude: 90° S 
Northernmost Latitude: 60° S 
Westernmost Longitude: 180° W 
Easternmost Longitude: 180° E

Spatial Coverage Map

Figure 1. Antarctic ice velocity derived from RADARSAT-1, ERS-1 and 2, ALOS PALSAR, ENVISAT ASAR, RADARSAT-2, Landsat-8, and Sentinel-1, color-coded on a logarithmic scale and overlaid on a MODIS mosaic of Antarctica. Projection is polar stereographic at 71° S secant plane.

Spatial Resolution

The spatial resolution of the velocity map is 450 m.

Projection 

Polar stereographic with true scale at 71° S. Refer to Polar Stereographic Projection and Grid page for more information and polar stereographic grid definitions.

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Temporal Coverage

The data were collected between 1996 and 2016. Detailed information is provided in the Data Acquisition and Processing section. 

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Parameter or Variable

This data set provides a comprehensive ice velocity map of the Antarctic Ice Sheet posted at 450 m grid spacing. The velocity components for the x and y direction, as defined by the polar stereographic grid, are stored in the NetCDF variables named 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 Assessment section as well as in Rignot, et al. 2011. The data also include the standard deviations for the velocity estimates (STDX,STDY), as well as a count of scenes (CNT) used to estimate the values for each pixel. Figure 2 shows the error and standard deviation estimates, and Figure 3 shows the total number of measurements used to estimate the velocity. Figure 4 shows a sample image of the data as a whole.  Table 1 provides a complete list of the variables and their descriptions.

Figure 2. Standard deviation of vx and vy (top row) and standard error of the mean vx and vy on a linear scale color-coded from 1 to greater than 32 m/yr

Figure 3. Number of measurements per pixel in the ice velocity mosaic (all sensors included)

Variable Description

The variables included in the NetCDF file are described in Table 1. All variables have grid dimensions of 12445 x 12445 and are posted at 450 m spacing.

Table 1. Variable Description
Variable Description Data Type
VX Component of velocity in m/yr in x direction float
VY Component of velocity in m/yr in y direction float
ERRX Estimated error in m/yr in x direction float
ERRY Estimated error in m/yr in y direction float
STDX Standard deviation of vx float
STDY Standard deviation of vy float
CNT Count of scenes used per pixel integer

To convert the VX and VY velocity components into magnitude (speed) and direction (angle), use the following equations:

(1)   speed = √(vx2 + vy2)
(2)   angle = arctan (vy / vx)
(3)   error = √(errx2 + erry2)
(4)   error of flow direction = error/(2*speed) (see Mouginot et al., 2012)

However, users should take care when computing the inverse tangent due to 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.

Sample Image

Figure 4. Antarctic ice velocity derived from RADARSAT-1, ERS-1 and 2, ALOS PALSAR, ENVISAT ASAR, RADARSAT-2, TerraSAR-X, TanDEM-X, Sentinel-1, and Landsat-8, color-coded on a logarithmic scale.
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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.

Quality Assessment

A detailed description of these data and their quality is provided in Rignot, et al., 2011. The precision of ice flow mapping varies with the sensor, the geographic location, the technique of interferometric analysis (refer to Data Acquisition and Processing for details), the time period of analysis, the repeat cycle, and the amount of data stacking. The error estimates are summarized in Table 2. The error map in Figure 2 takes into account the following error sources:

  • Error of speckle tracking and interferometric phase analysis respectively (SAR only)
  • Errors caused by ionospheric perturbations (strongest in the azimuth direction, stronger in L-band compared to C-band, stronger in the East Antarctic Ice Sheet (EAIS) compared to the West Antarctic Ice Sheet (WAIS) because ionospheric perturbations are more abundant near the magnetic pole
  • Error of feature tracking analysis (Landsat-8 only)
  • Data stacking (reduces the error noise as the square root of the number of interferometric pairs averaged)
  • Respective weight of each instrument in the mosaicking

The total error is the square root of the sum of the independent errors squared. More details on the error estimates are provided in Mouginot, et al., 2017. Table 2 provides the error in ice velocity mapping for each sensor, without data stacking, in range (Rg) and azimuth (Az).

Platform/Sensor Nominal Repeat Cycle
(day)
Error (m/yr)
Rg Az
Table 2. Error in Ice Velocity Mapping (m/yr)
ALOS (WAIS)/PALSAR 46 6 17
ALOS (EAIS)/PALSAR 46 6 5
ENVISAT/ASAR 35 21 4
RADARSAT-2/SAR 24 26 8
RADARSAT-1/SAR 24 26 8
Sentinel-1/SAR 12 12 43
Landsat-8/OLI 16 34* 34*
TanDEM-X (TDX)/TerraSAR-X (TSX)/SAR 11 8 8
Tandem ERS-1 and -2 (phase)/SAR 1 1 N/A

*Landsat uses repeat image feature tracking in x and y

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Data Acquisition and Processing

Theory of Measurements

This data set provides a comprehensive ice velocity map for the entire Antarctic ice sheet, derived from a variety of satellite radar interferometry data. (See the Data Sources section for a complete list.) Several analysis techniques using SAR data were used to generate the maps:

  1. Speckle tracking in both along (azimuth) and across (range) track directions
  2. Calculation of two dimensional offsets in amplitude imagery
  3. Combinations of (range) interferometric phases along two independent tracks
  4. Combination of interferometric phases of two independent tracks to retrieve the surface flow vector

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).

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Data Acquisition Methods

This digital image mosaic was built from the sources listed in Table 3, as well as the following:

  • The RADARSAT-2 data acquired during spring 2009 was augmented by a 2011 gap-filling campaign
  • Envisat Advanced Synthetic Aperture Radar (ASAR) data acquired during spring 2007, 2008, and 2009
  • Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data acquired during fall 2007-2008

The Version 2.0 mosaic also uses RADARSAT-2 (CSA) and Sentinel-1 (ESA/EU) data acquired between 2012 and 2016, Landsat-8 data acquired between 2013 and 2016, TanDEM-X and TerraSAR-X (DLR) between 2011 and 2014, and additional PALSAR (ALOS/JAXA) between 2006 and 2010. SAR acquisitions between 2006 and 2016 were coordinated by the IPY Space Task Group and its successor, the Polar Space Task Group (PSTG).

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Data Sources

Table 3 describes the data sources used in this data set.

Table 3. Temporal and spatial coverage of source satellite data
Platform/Sensor Space Agency Look Dir. Mode Repeat Cycle
(day)
Incidence Angle Resolution 
Rg x Az (m)
Frequency (GHz) Year
ERS-1 & 2/SAR European Space Agency (ESA) Right N/A 1-3 23 13x4 5.33 1996
RADARSAT-1/SAR Canadian Space Agency (CSA) Left/Right Varies 24 18-47 12x5-17x6 5.33 1997/2000
ENVISAT/ASAR ESA Right IS2 35 23 13x5 5.33 2007-2009
RADARSAT-2/SAR CSA Left S5/EH4 24 41/57 12x5 5.33 2009-2016
ALOS/PALSAR Japan Aerospace Exploration Agency (JAXA) Right FBS 46 39 7x4 1.27 2006-2010
Sentinel-1/SAR ESA Right IW-T OPS 12 12x43 5.33 2006-2016
Landsat-8/OLI USGS/NASA N/A Panchromatic 16 N/A 15x15 2013-2016
TanDEM-X/TerraSAR-X/SAR German Space Agency (DLR) right N/A 11 46.3 1.4x1.8 9.65 2011-2016
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Version History

Version 2.0 was released April 2017. Refer to Table 4 for this data set's version history:

Table 4. Version History
Version Description
V2.0 Added post 2011 SAR data (RADARSAT-2, Sentinel-1, TanDEM-X/TerraSAR-X) and Landsat-8 optical data (March 2017). The mosaicking method was updated to make best use of the large number of scenes used for the mosaic.  New quality parameters including the standard deviation and count variables are provided in the NetCDF file.
V1.2 Binary data file format discontinued. Data available in NetCDF only (August 2015).
V1.1 Added a second mosaic at 450 m resolution (September 2013)
V1 Initial version (October, 2011)
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References and Related Publications

Contacts and Acknowledgments

Investigators

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

Dr. Jeremie Mouginot
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: Japan Aerospace Exploration Agency (JAXA)
  • Sentinel-1, ENVISAT ASAR, ERS-1, ERS-2: European Space Agency (ESA)
  • RADARSAT-1, RADARSAT-2: Canadian Space Agency (CSA)
  • Landsat-8 (optical) data were made available by United States Geological Survey (USGS)

Data acquisitions between 2006 and 2016 are courtesy of the International Polar Year (IPY) Space Task Group and its successor, the Polar Space Task Group (PSTG).

Document Information

DOCUMENT CREATION DATE

April 2017

DOCUMENT REVISION DATE

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