Data Set ID:

MEaSUREs Greenland Ice Velocity: Selected Glacier Site Velocity Maps from InSAR, Version 3

This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, provides velocity estimates determined from Interferometric Synthetic Aperture Radar (InSAR) data for major glacier outlet areas in Greenland, some of which have shown profound velocity changes over the MEaSUREs observation period. The InSAR Selected Glacier Site Velocity Maps are produced from image pairs measured by the German Aerospace Center's (DLR) twin satellites TerraSAR-X / TanDEM-X (TSX / TDX). The measurements in this data set are provided in addition to the ice sheet-wide data from the related data set, MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data.

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

This is the most recent version of these data.

Version Summary:

Processing steps include a new DEM for images acquired in 2015 and after:
- images created from data acquired on or after January 1, 2015 were processed using the MEaSUREs GIMP DEM V2 (NSIDC-0715)
- for data acquired prior to 2015, images were processed using the MEaSUREs GIMP DEM V1 (NSIDC-0645)
- A field has been added to the .meta file to indicate which DEM was used in the processing.

COMPREHENSIVE Level of Service

Data: Data integrity and usability verified; data customization services available for select data

Documentation: Key metadata and comprehensive user guide available

User Support: Assistance with data access and usage; guidance on use of data in tools and data customization services

See All Level of Service Details

Data Format(s):
  • JPEG
  • GeoTIFF
Spatial Coverage:
N: 82, 
S: 60, 
E: -20, 
W: -70
Spatial Resolution:
  • 100 m x 100 m
Temporal Coverage:
  • 12 June 2008
Temporal Resolution11 dayMetadata XML:View Metadata Record
Data Contributor(s):Ian Joughin, Ian Howat, Ted Scambos, Ben Smith

Geographic Coverage

Other Access Options

Other Access Options


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., I. Howat, B. Smith, and T. Scambos. 2020. MEaSUREs Greenland Ice Velocity: Selected Glacier Site Velocity Maps from InSAR, Version 3. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: [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.

16 January 2020
Last modified: 
31 August 2020

Data Description


Ice velocity is reported in meters per year. The velocity magnitude is reported in the vv files. The vx and vy files contain the velocity components 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. In some areas, small gaps have been filled via interpolation. Interpolated values are identifiable as locations where velocity data are present but no error estimates exist. Radar-derived velocities are determined using a combination of conventional InSAR and speckle tracking techniques.

Error estimates are provided for all non-interpolated, radar-derived velocity vectors. These estimates include the statistical uncertainty associated with the phase and speckle tracking error. See Joughin (2002) for more detail on errors and how they are computed.

The missing data value for the velocity magnitude (vv) and error estimate (exey) files is -1 and is set as the attribute in all files. The missing data value for the velocity component (vxvy) files is -2e+9.

File Information


For each grid and existing time period, the ice velocity magnitude (vv), its components (vx, vy), and the corresponding error estimates (ex, ey) are provided in Geographic Tagged Image File Format (GeoTIFF). A JPEG image of the velocity magnitude is provided for easy visualization. An ASCII formatted metadata file containing source satellite acquistion information is also included.

Naming Convention

Files are named according to the following convention:

Table 1 describes the existing options in the file naming convention. As an example, below are listed all the files for grid E61.10N for the 19-30 April 2014 period in version 3.0:

  • TSX_E61.10N_19Apr14_30Apr14_09-16-09_vv_v03.0.tif
  • TSX_E61.10N_19Apr14_30Apr14_09-16-09_vx_v03.0.tif
  • TSX_E61.10N_19Apr14_30Apr14_09-16-09_vy_v03.0.tif
  • TSX_E61.10N_19Apr14_30Apr14_09-16-09_ex_v03.0.tif
  • TSX_E61.10N_19Apr14_30Apr14_09-16-09_ey_v03.0.tif
  • TSX_E61.10N_19Apr14_30Apr14_09-16-09_v03.0.jpg
  • TSX_E61.10N_19Apr14_30Apr14_09-16-09_v03.0.meta
Table 1. File Naming Convention
Variable Description
TSX Data Source
  • TSX: denotes the twin satellites TerraSAR-X / TanDEM-X (TSX / TDX)
grid The grid name describes:
  • whether it is on the East (E), West (W), or South (S) coast
  • latitude (for E and W) or longitude (for S) in decimal degrees
startdate Date of first image (DDMMMYY)
enddate Date of second image (DDMMMYY)
hh-mm-ss Nominal time for pair
parameter Velocity magnitude, velocity component, or error estimate
  • vv: velocity magnitude
  • vx: x component of velocity
  • vy: y component of velocity
  • ex: error of x component
  • ey: error of y component
vXX.X Version of the data set
.ext File extensions:
  • .tif = GeoTIFF formatted file
  • .jpg = JPEG file; visualization of the velocity magnitude
  • .meta = ASCII text file; contains the Central Julian date and nominal time (HH:MM:SS) for the pair, the date for each image, production date, sensor combinations, and geographical information

Spatial Information


This data set contains velocity data for most of the outlet glaciers for the Greenland Ice Sheet. It is presented by study sites, with a total of 55 grids. The spatial coverage map in Figure 1 shows the locations of all grids on a map of Greenland.

Figure 1. This map shows the locations of all the grids around Greenland (click image for high-resolution version).


100 meters


Data are provided in subregions of a polar stereographic grid with a standard latitude of 70° N and a 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.

The origin specifies the polar stereographic coordinates for the center of the lower left pixel, i.e., the first sample in the file. This specification, using the middle of the reference pixel, differs from that used in some GeoTIFF and other formats where the reference coordinates are specified for the outer corner of the reference pixel.

Temporal Information


12 June 2008 to present. 
Data for 2008 were only obtained for three grids on a trial basis. Most grids have data starting in 2009.
This data set undergoes periodic updates as new data are collected and processed. Please check the Temporal Coverage table (available as an Excel spreadsheet under the Technical References tab) for a complete list of available dates by grid and by year. 

The Temporal Coverage table has not yet been updated for Version 3 to include file dates from Sep-2019 to Dec-2019.


The temporal resolution varies between 11, 22, and 33 days on an 11-day repeat cycle.

Data Acquisition and Processing

Theory of Measurements

The ice velocity maps in this data set were created using Synthetic Aperture Radar (SAR) data from the German Aerospace Center's (DLR) twin satellites TerraSAR-X / TanDEM-X (TSX/TDX). The methods include a combination of speckle tracking and conventional interferometry. See Joughin (2002) for more detail.

Sensor / Instrument Description

The twin satellites TerraSAR-X / TanDEM-X fly in close formation only a few hundred meters apart. For each time period in this data set, velocities were estimated from a pair of images. For any given pair, the images are obtained from either satellite and could have any of the possible sources: TSX/TSX,TSX/TDX, or TDX/TDX. 

Error Sources

Error estimates are provided for all non-interpolated, radar-derived velocity components (vx, vy). They include the statistical uncertainty associated with the phase and speckle tracking error inherent in the SAR data. Formal errors agree reasonably well compared with errors determined from GPS data (Joughin, 2002). However, the true uncertainty is likely larger and these estimates should be used as an indication of relative quality rather than as absolute error.

Software and Tools

GeoTIFF files can be viewed with a variety of Geographical Information System (GIS) software packages, including QGIS and ArcGIS.

Version History

Version 3 was released in August 2020. Refer to Table 2 for the data set version history:

Table 2. Version History
Version Release Date Description of Changes
V1 May 2011 Initial release
V1.1 February 2016 GeoTIFF file format added; binary format discontinued; contains improved temporal sampling for the Jakobshavn Isbrae, Helheim, and Kangerdlugssuaq glaciers. The improved sampling addresses previous artifacts related to slope discontinuities at these glaciers' termini for the years 2009 – 2016
V1.2 May 2017 Renamed files to include the nominal time for pair; added 3 TSX subdirectories missing from their respective region directories; removed extraneous files from several TSX subdirectories; included .meta files for metadata
V2 February 2020

1. Full reprocessing with accumulated minor updates. Output should be generally consistent with previous versions.
2. The tiffs are now cloud optimized and include scale-down by 2 and 4 pyramids.
3. Velocity magnitude is now included as a separate tiff to be consistent with other velocity products (so now there are vx, vy, and vv tiffs).
4. Correction of browse images (distortions, color bar placement, watermark, and color-scale consistency.)
5. Addition of consistent NoData values
6. Temporal coverage was extended.

V3 August 2020

Processing steps include a new DEM for images acquired in 2015 and after. For consistency with the MEAsUREs Greenland Ice sheet Mapping Project (GIMP) Sentinel-1 product (NSIDC-0723), and to account for the evolving ice sheet geometry, images created from data acquired on or after January 1, 2015 were processed using the MEaSUREs GIMP DEM V2 (NSIDC-0715). For images acquired prior to 2015, the processing steps included the MEaSUREs GIMP DEM V1 (NSIDC-0645). A field has been added to the .meta file to indicate which DEM was used in the processing. As a result of this change, there could be geolocation and other systematic differences when comparing images prior to 2015 with images from 2015 and after. Such artifacts are most likely to be found in regions with strong elevation changes or where there are large changes in terminus position. Since all of this product’s V2 data were produced with the MEaSUREs GIMP V1 DEM (NSIDC-0645), such artifacts should also be present when comparing V2 and V3 images for the same date if in 2015 and later. Other input data, algorithms, processing steps, and uncertainty estimates remain the same as in V2.

Related Data Sets

Related Websites

Contacts and Acknowledgments

Ian Joughin
Applied Physics Laboratory 
University of Washington

Ian Howat
Byrd Polar Research Center
Ohio State University

Ben Smith
Polar Science Center Applied Physics Laboratory
University of Washington

Ted Scambos
National Snow and Ice Data Center
Cooperative Institute for Research in Environmental Science
University of Colorado


Yushin Ahn, & Howat, I. M. (2011). Efficient Automated Glacier Surface Velocity Measurement From Repeat Images Using Multi-Image/Multichip and Null Exclusion Feature Tracking. IEEE Transactions on Geoscience and Remote Sensing, 49(8), 2838–2846.

Howat, I. M., Box, J. E., Ahn, Y., Herrington, A., & McFadden, E. M. (2010). Seasonal variability in the dynamics of marine-terminating outlet glaciers in Greenland. Journal of Glaciology, 56(198), 601–613.

Joughin, I. (2002). Ice-sheet velocity mapping: a combined interferometric and speckle-tracking approach. Annals of Glaciology, 34, 195–201.

Joughin, I., Abdalati, W., & Fahnestock, M. (2004). Large fluctuations in speed on Greenland’s Jakobshavn Isbræ glacier. Nature, 432(7017), 608–610.

Joughin, I., Smith, B. E., Howat, I. M., Scambos, T., & Moon, T. (2010). Greenland flow variability from ice-sheet-wide velocity mapping. Journal of Glaciology, 56(197), 415–430.

Joughin, I., Kwok, R., & Fahnestock, M. (1996). Estimation of ice-sheet motion using satellite radar interferometry: method and error analysis with application to Humboldt Glacier, Greenland. Journal of Glaciology, 42(142), 564–575.

No technical references available for this data set.

How To

Programmatic Data Access Guide
Data from the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) can be accessed directly from our HTTPS file system or through our Application Programming Interface (API). Our API offers you the ability to order data using specific temporal and spatial filters... read more
Filter and order from a data set web page
Many NSIDC data set web pages provide the ability to search and filter data with spatial and temporal contstraints using a map-based interface. This article outlines how to order NSIDC DAAC data using advanced searching and filtering.  Step 1: Go to a data set web page This article will use the... read more
How do I reproject a geoTIFF from polar stereographic to geographic lat/lon?
We recommend using the Geospatial Data Abstraction Library (GDAL) or GIS to reproject geoTIFF files. Here we outline command line or python options for using GDAL, and instructions for QGIS and ArcMap to... read more
How do I convert a GeoTIFF into a NetCDF file?
We recommend using the Geospatial Data Abstraction Library (GDAL) to convert GeoTIFF files into a different format. If you want to reproject to lat/lon as well, then we recommend reprojecting before converting to NetCDF (see the FAQ "How do I reproject a GeoTIFF to from polar steroegraphic to... read more


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