On Wednesday, September19 from 9:00 a.m. to 12:00 p.m./noon (USA Mountain Time), the following data collections will not be available due to planned system maintenance: AMSR-E, Aquarius, ASO, High Mountain Asia, IceBridge, ICESat/GLAS, MEaSUREs, MODIS, NISE, SMAP, SnowEx, and VIIRS. 
Data Set ID:

MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, Version 2

This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, contains seasonal (winter) ice-sheet-wide velocity maps for Greenland derived from Interferometric Synthetic Aperture Radar (InSAR) data obtained by Canadian Space Agency's (CSA) RADARSAT-1, the Japan Aerospace Exploration Agency's (JAXA) Advanced Land Observation Satellite (ALOS), and the German Aerospace Center's (DLR) TerraSAR-X/TanDEM-X (TSX/TDX) satellites, and the European Space Agency's (ESA) C-band Synthetic Aperture Radar data from Copernicus Sentinel-1A and -1B.

See Greenland Ice Mapping Project (GIMP) for related data.

Note: These data are considered provisional pending a review by the MEaSUREs program. Once the data have been reviewed, this statement will be removed.

Version Summary:

For Version 2, all velocity maps underwent additional screening for quality control and bad data points were removed. In addition:

  • Improved baseline fits enhance consistency in the interior
  • Updated error estimates better represent the average behavior of the data
  • ALOS fine-beam data have been added to improve spatial coverage for select winters
  • Temporal coverage extended
  • The mosaics produced from Sentinel-1 data (2014/15, 2015/16, 2016/17) are provided at both 500 m and 200 m resolutions.
  • Ancillary shapefiles that contain information about the satellite tracks used to produce the mosaics have been added
  • Browse images have been added
  • Changed the magnitude file name from "greenland_vel_mosaic[RRR]_[yyyy_yyyy]_v2.ext" to "greenland_vel_mosaic[RRR]_[yyyy_yyyy]_vel_v2.ext."

Get Data

MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, Version 2


An Earthdata Login account is required to access these data. Please visit the Earthdata Login registration page to register for an account. Once you have logged in, data can be downloaded via a Web browser, command line, or client. For help with downloading data, please see Options Available for Bulk Downloading Data from HTTPS with Earthdata Login.


Worldview: This application allows you to interactively browse global satellite imagery within hours of it being acquired. You can also save it, share it, and download the underlying data.
Earthdata Search: NASA's newest search and order tool for subsetting, reprojecting, and reformatting data.

Geographic Coverage

  • Snow/Ice > Ice Velocity
Spatial Coverage:
  • N: 83, S: 60, E: -14, W: -75

Spatial Resolution:
  • 500 m x 500 m
  • 200 m x 200 m
Temporal Coverage:
  • 3 September 2000 to 24 January 2001
  • 13 December 2005 to 20 April 2006
  • 18 December 2006 to 6 June 2007
  • 7 September 2007 to 23 April 2008
  • 15 September 2008 to 16 June 2009
  • 2 September 2009 to 7 May 2010
  • 3 March 2012 to 5 April 2013
  • 1 September 2014 to 3 July 2015
  • 1 September 2015 to 28 June 2016
  • 1 September 2016 to 23 June 2017
(updated 2017)
Temporal Resolution: 12 years, 1 year
Data Format(s):
  • GeoTIFF
  • ESRI Shapefile
  • JPEG
Sensor(s): C-SAR, PALSAR, SAR
Version: V2
Data Contributor(s): Ian Joughin, Ben Smith, Ian Howat, Ted Scambos

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.

Joughin, I., B. Smith, I. Howat, and T. Scambos. 2015, updated 2017. MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, Version 2. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/OC7B04ZM9G6Q. [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.

  • Joughin, I., B. Smith, I. Howat, T. Scambos, and T. Moon. 2010. Greenland Flow Variability from Ice-Sheet-Wide Velocity Mapping, Journal of Glaciology. 56. 415-430.

Back to Top

Collapse All / Open All

Detailed Data Description

This data set contains Greenland ice sheet-wide velocity maps for ten winters derived from SAR data. The platform/sensor used as source data depends on the year. Refer to Table 2 in the Temporal Coverage section for the data sources for each year.

Shapefiles are included in the data to indicate the image pairs that were processed to produce the mosaic. Since speckle tracking may fail to produce results at some points within a SAR image pair, the swaths indicated in the shapefile only indicate which data could have contributed to a particular point (i.e., some data from that swath were used in the mosaic, but at any particular point, there may not have been a valid result from that swath).

Velocity maps (color log scale velocity that saturates at 3000 m/year) are included as a GeoTIFF.

For maps of glacier outlet areas, some of which demonstrated profound velocity changes during the observation period, see the related data set MEaSUREs Greenland Ice Velocity: Selected Glacier Site Velocity Maps from InSAR.


Data are available in GeoTIFF (.tif) format. Six GeoTIFF files are available for each data year: a velocity magnitude map; separate x- and y-component velocities (vx, vy); separate x- and y-component error estimates (ex, ey), and a browse file (.tif). In addition, a shapefile (.shp) of satellite tracks is included for each of the winters.

Background color on
File Naming Convention

The file naming convention used for this data set is:

greenland_vel_mosaic[RRR]_[yyyy_yyyy]_[vx OR vy]_v2.ext
greenland_vel_mosaic[RRR]_[yyyy_yyyy]_[ex OR ey]_v2.ext




The following table describes the variables in this data set's file naming convention.

Table 1. File Naming Convention
Variable Description
greenland_vel_mosaic Greenland velocity mosaic
RRR Resolution: 500 m or 200m
yyyy_yyyy Winter season
vx OR vy Velocity x-direction, velocity y-direction
ex OR ey Error x-direction, error y-direction
vel Magnitude mosaic
browse Browse image
v2 Version 2
.ext GeoTIFF (.tif)
Shapefile (.shp, .dbf, .shx, .prj)
JPEG (.jpg)
Background color on
File Size

The .tif data files range from 64 MB to 397 MB. Each shapefile (.shp, .dbf, .shx, .prj) ranges from 255 bytes to 229 KB. The entire data volume (141 files) is approximately 9.9 GB. Browse files (.jpg) are 67mb for 500 m resolution and 406mb for 200 m resolution.

Background color on
Spatial Coverage

This data set covers Greenland.

Southernmost Latitude: 60° N
Northernmost Latitude: 83° N
Westernmost Longitude: 75° W
Easternmost Longitude: 14° W

Spatial Resolution

500 m or 200 m


Data are provided in a WGS 84 polar stereographic grid with a standard latitude of 70° N and rotation angle of -45° (sometimes specified as a longitude of 45° W). With this convention, the y-axis extends south from the North Pole along the 45° W meridian (EPSG:3413).

Background color on
Temporal Coverage

This data set provides velocity data for the following winters listed in Table 2. "Winter" is broadly defined to be September 1 to May 31. See the note below the table for the agencies that provided the different data sources.

Table 2. Velocity Maps listed by Source Data and Temporal Coverage
Temporal Coverage SAR Data Source
2000-2001 RADARSAT-1
2005-2006 RADARSAT-1
2006-2007 RADARSAT-1, ALOS
2007-2008 RADARSAT-1, ALOS
2008-2009 RADARSAT-1, ALOS, TSX
2009-2010 ALOS, TSX
2012-2013 RADARSAT-1, TSX, TDX
2014-2015 S-1A, TDX, TSX
2015-2016 S-1A, TDX, TSX
2016-2017 S-1A, S-1B, TDX, TSX

NOTE: Canadian Space Agency (CSA)- RADARSAT-1; Japan Aerospace Exploration Agency (JAXA) - ALOS; German Aerospace Center (DLR) - TSX and TDX; European Space Agency (ESA) - S-1A and S-1B

Background color on
Parameter or Variable

Velocities are reported in meters per year. The vx and vy files contain component velocities in the x and y directions defined by the polar stereographic grid. These velocities are true values and not subject to the distance distortions present in a polar stereographic grid. Small holes have been filled via interpolation in some areas. Interpolated values are identifiable as locations that have velocity data but no error estimates. Radar-derived velocities are determined using a combination of conventional InSAR and speckle tracking techniques (Joughin, et. al., 2002).

Error estimates are provided for all non-interpolated, radar-derived velocity vectors in separate GeoTIFF files appended with _ex.tif and _ey.tif. These estimates include the statistical uncertainty associated with the phase and speckle tracking error. Formal errors agree reasonably well with errors determined by comparison with GPS data (Joughin, et al, 2002). The values, however, underestimate true uncertainty in several ways, and as such should be used more as an indication of relative quality rather than absolute error.  Refer to the Error Sources section for more details.  

Background color on

Software and Tools

GeoTIFF files and Shapefiles can be viewed with a variety of Geographical Information System (GIS) software packages including QGIS and ArcGIS. Extensible Markup Language files can be viewed within any browser.

Background color on

Data Acquisition and Processing

Theory of Measurements

The velocity maps in this data set were created using SAR data. The methods include a combination of speckle tracking and conventional interferometry. Velocity maps were produced by mosaicking multiple strips of InSAR-derived data. Individual images were selected based on two criteria: images should come from the same time of year; and images for each individual year should be chosen from as short a span as possible. For more detail, refer to Joughin, et. al., 2002.

Background color on
Derivation Techniques and Algorithms

Annual mosaics were created using data collected over an approximately 96-day period during the winter. Areas with no data correspond either to regions where no data were acquired or where the interferometric correlation was insufficient to produce an estimate, most often in areas with high snow accumulation. Regions with data represent the average of between one and three estimates (larger numbers may occur in regions of swath overlap, especially at higher latitudes).

The data are posted to a 0.5-kilometer grid, but the true resolution varies between 0.5 and 1 km. Many small glaciers are resolved outside the main ice sheet, but it is important to remember that for narrow (<1km) glaciers, the velocity represents an average of both moving ice and stationary rock, so while the glacier may be visible in the map, its speed is likely underestimated. Also on some of the smaller glaciers, interpolation produces artifacts where the interpolated value is derived from nearby rock, causing apparent stationary regions in the middle of otherwise active flow. The data have been screened to remove most of these, but please proceed with caution.

The missing data value for magnitude files is -0.1. The no data value is -2e+9 for vx, vy, ex, and ey files.

Processing Steps

The following sections briefly describe how each winter's velocity map was generated.


In late 2000 and early 2001, during RADARSAT-1 Modified Antarctic Mapping Mission, the Canadian Space Agency (CSA) acquired nearly complete coverage of Greenland with multiple passes suitable for InSAR (September 3 to January 24). All of the available data for Greenland were used to produce the 2000 to 2001 mosaic. In cases where the data quality was too poor, some products were discarded. All source data were obtained from the Alaska Satellite Facility (ASF).


In 2005 and 2006, RADARSAT-1 imaged most of Greenland four consecutive times, producing three InSAR pairs. Once all of the data were processed, poor coherence passes were screened out and the remaining data were used to assemble the velocity maps.


The 2006/2007 mosaic was produced with RADARSAT-1 fine beam data. Coverage is substantially improved by including ascending the Japan Aerospace Exploration Agency's (JAXA) ALOS quad-pol data, including coverage in the southeast. The ionospheric errors are often large (>20 m/year) in the ALOS data; therefore, points were manually removed where errors were excessive. This approach was chosen to strike a balance between maximizing coverage and minimizing error. Nonetheless, care should be exercised when interpreting these data, particularly in the southeast.


The 2007/2008 mosaic was produced with RADARSAT-1 fine beam data, in the same manner as the 2006/2007 mosaic, including using a substantial volume of ALOS fine-beam data, largely along the northwest coast.


The 2008/2009 map utilizes CSA's RADARSAT-1, the German Aerospace Center's (DLR) TSX, and JAXA's ALOS data.


The 2009/2010 mosaic consists almost entirely of ALOS SAR data collected in Fine-Beam, Single-Polarization (FBS) mode. Because L-band is more subject to ionospheric distortion of speckle-tracked azimuth offsets, streak errors for some areas are large (>10 m/year), often exceeding the magnitude of the accompanying error estimates. In other areas, these errors are barely perceptible. Some of the worst streaks were edited out. However, a number of lesser streaks were left in place to: a) preserve coverage; and b) illustrate the magnitude of these errors with obvious examples. Despite being more susceptible to the ionosphere, L-band data correlate well in areas with high accumulation. As a result, this map has better coverage in the southeast than many of the maps from other winters.

Twenty coastal sites in this mosaic utilize 30 km x 50 km TSX scenes. These X-band data greatly improve the results for many of the fast moving outlet glaciers.


The 2012/2013 data were collected during the last few months in the life of RADARSAT 1 from January 2013 to March 2013. These data were combined with TSX winter data (November 2012 to March 2013).

General Information for 2014-2017

The 2014-2017 mosaics were produced mostly with ESA's Copernicus Sentinel-1A/1B data and supplemented by DLR's TSX/TDX data for coastal outlets. The data were acquired in either 12 (through Sept 16) or 6-day repeat cycles (October 16 forward). In cases of missing acquisitions, the repeat periods may be longer (integer multiples of 6 or 12 days) for some of the image pairs.

Unlike earlier SAR acquisitions, Sentinel-1A/1B provides crossing ascending and descending orbit data over much of the ice sheet. In areas where crossing-orbit data were available, an error-weight range-offset only solution was included in the velocity product, eliminating azimuth offsets and reducing the error from ionospheric streaking in the azimuth offsets.

To take advantage of the year-round Sentinel coastal coverage, "winter" is defined to be September 1 to May 31, which corresponds approximately to the period with little or no melt. This definition of winter might produce small seasonal differences when comparing these data with mosaics from other years in which narrower periods of acquisitions were used. However, such differences are generally small relative to inter-annual variability and to the noise reduction accomplished by averaging a greater volume of data acquired over a longer period.

Due to the reduction in the resolution of Sentinel-1A/1B SAR data, some systematic differences between the mosaics produced by  RADARSAT, ALOS, and TSX/TDX data may exist, especially at sharp gradients or strong curvature. Smoothing earlier velocity results to ~1.5km resolution (~Sentinel-1 resolution) should improve agreement among data sets. In producing the mosaics, higher resolution TSX/TDX data are given more weight, so the degradation in resolution should be far less in these areas. These velocity mosaics are posted at both 0.2 km and 0.5 km spacing where the 0.5km posted data sample the original source data well. For work requiring a finer resolution, see MEaSUREs Greenland Ice Velocity: Selected Glacier Site Velocity Maps from InSAR, Version 1.

As a result of the large volume of data used, the overall quality of the data is good. Compared to earlier products, the coverage in the southeast is generally improved, particularly for 2016/17; however, high accumulation in the southeast reduces image to image correlation, resulting in higher noise. Additionally, in these regions there may be coherent displacement signals that are not associated with horizontal ice motion. If such displacement occurs with characteristics other than that assumed in the solution (e.g., predominantly vertical instead of horizontal displacement), then the result will be incorrectly mapped to horizontal motion, contributing to the overall level of noise.


These velocity mosaics are largely produced from TSX data, with the addition of Sentinel-1A data. Sentinel-1 data acquisitions began during this winter period, so there are almost no Sentinel-1 data prior to January 2015, with the exception of the region around Jakobshavn glacier. As a result of the limited satellite coverage, the 2014-2015 mosaic contains more noise and less spatial coverage than that found in the 2015-2016 and 2016-2017 products.


These velocity mosaics are largely produced from Sentinel-1A. The six tracks that covered nearly the entire coast were collected almost every 12-day satellite repeat cycle. In the interior, typically four images (three pairs were collected) with better coverage and fewer errors than the 2014-2015 mosaics.


These velocity mosaics are largely produced from Sentinel-1A/1B. In October 2016, Sentinel 1B started acquiring data over Greenland in an orbit that lags Sentinel-1A by six days. As a result, Sentinel-1A/1B pairs are often separated by only six days, providing better correlation and coverage, particularly in the southeast of Greenland. Thus, the mosaic for this winter provides approximately complete spatial coverage relative to all prior winter velocity products.

Background color on
Error Sources

Baseline Fits

Each image-pair that is used in the mosaic requires a 4-to-6 parameter fit for the baseline parameters (in other words, the separation between satellite tracks). For Version 1, the baseline was fitted to a sparse, common set of ground control points as described by Joughin et al., 2010. This led to errors exceeding 10 m/year being misinterpreted as actual change (Phillips et al., 2013). In Version 2, for a year where the data were not well controlled, control points from other years with adequate controls were used. This greatly improves consistency of the data from year to year. While this could mask some true change, the errors without this procedure were far larger than any change likely to occur.

As a result, these data should not be used to determine inter-annual change for interior regions of the ice sheet (roughly defined as areas above 2000 meters). In outlet glaciers close to the coast where the baselines are well constrained by bedrock, the velocity maps are well suited to this task. However, care should be exercised in interpreting any change observed in intermediate regions (roughly 1000 m to 2000 m), especially areas where the observed changes seem to follow swath boundaries.  Refer to Figure 5 in Phillips et al., 2013 for more information. Note that baseline errors are not included in the formal error estimates and thus actual errors can always be substantially larger than stated. In particular, where they are derived mostly from phase, the reported errors are extremely low (<0.5 m/year). With baseline errors included, the actual error is probably in the 1 to 3 m/year range in most cases.

Error Estimates

In general, the error maps represent the average behavior of the data. As a result, errors could be much lower than reported in some areas and much greater in others; care should be taken when assigning statistical significance based on the errors, especially given that the errors can be correlated over large areas. For example, even if the errors are correct in a global sense, one might compare two mosaics and find a large difference of over 5% of the ice sheet. However, because errors can be spatially correlated over broad areas, one should not assume significance at the 95% confidence level; this might be precisely the 5% that statistically should exceed the errors because the errors are not uniformly distributed. By contrast, if the errors were completely uncorrelated, one could average over neighborhoods to reduce the error.

Phase Data

Phase data (as opposed to speckle tracked) have been used for the x- and y-component of motion in the across-track direction, improving the accuracy in areas with slow-moving ice. In addition, some mosaics have more crossing orbit data (ascending and descending). This substantially improves the accuracy of both components in some areas by minimizing the use of noisy azimuth offsets.

Interpolated Points

Small holes in the final maps have been filled via interpolation. These points can be identified as those that have valid velocity data but no corresponding error estimate.

See Joughin, et al, 2002 for more detail on errors and how they were computed.

Background color on
Version History

Version 2 was released in December 2015. Refer to Table 3 for this data set's version history.

Table 3. Version History
Version Description Effective Date
  • 2014/2015, 2015/2016, 2016/2017 data published
  • Added shapefiles of satellite tracks for all winters
  • Added browse files for all winters
  • Changed the magnitude file name from "greenland_vel_mosaic[RRR]_[yyyy_yyyy]_v2.ext" to "greenland_vel_mosaic[RRR]_[yyyy_yyyy]_vel_v2.ext
August 2017
V2       2012/2013 data published January 2017
  • New map added for 2009/2010
  • ALOS fine-beam data added to improve coverage in 2006/2007, 2007/2008, 2008/2009
  • Corrected a substantial error on Rink glacier where the time interval was off by a factor of 2
  • Baseline fits improved for consistency in the interior
  • Updated error estimates that better represent the average behavior of the data
  • Additional quality control screening to remove bad data points
December 2015
V1.1 Binary data file format discontinued; data available in GeoTIFF only August 2015
V1 Initial version September 2010
Background color on

References and Related Publications

Contacts and Acknowledgments

Dr. Ian Joughin
University of Washington
Applied Physics Laboratory 
1013 NE 40th Street 
Box 355640 
Seattle, Washington 98105

Ben Smith
University of Washington
Polar Science Center Applied Physics Laboratory
Department of Earth and Space Sciences
Seattle, Washington 98195 USA

Ian Howat
Ohio State University
Byrd Polar Research Center
Scott Hall Room 108
1090 Carmack Road
Columbus, Ohio 43210 USA

Ted Scambos
National Snow and Ice Data Center
449 UCB, University of Colorado
Boulder, CO 80309-0449 USA


This project was supported by a grant (MEAS-12_0006) from the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program.

Contains modified Copernicus Sentinel data (2014-2017), acquired by the European Space Agency, distributed through the Alaska Satellite Facility, and processed by Joughin, I., B. Smith, I. Howat, and T. Scambos. Also contains data from the TanDEM-X and TerraSAR-X missions processed by DLR, as well as ALOS data processed by JAXA.

Document Information


December 2015


Do you have sample code to read GeoTiffs?
Sample image ouput from Python code. Below you will find  sample code in IDL, MATLAB, and Python to read in a GeoTIFF file, extract the metadata, and create an image. The code has been tested with... read more