MEaSUREs Greenland Annual Ice Sheet Velocity Mosaics from SAR and Landsat, Version 3
Data set id:
NSIDC-0725
DOI: 10.5067/C2GFA20CXUI4
There is a more recent version of these data.
Version Summary
Version updates include:
-Reprocessed with a variation of DEM NSIDC-0715 corrected to address a 15 m horizontal shift
-Cloud optimized GeoTIFFS created with GDAL 3.2.1
-Extended temporal coverage

Overview

This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, contains annual ice velocity mosaics for the Greenland Ice Sheet derived from Synthetic Aperture Radar (SAR) data obtained by the German Space Agency's TerraSAR-X/TanDEM-X (TSX/TDX) and the European Space Agency's Copernicus Sentinel-1A and -1B satellites, and from the US Geological Survey's Landsat 8 optical imagery for years 2015 to 2020. See Greenland Ice Mapping Project (GIMP) for related data.
Parameter(s):
ICE VELOCITY
Platform(s):
LANDSAT-8, Sentinel-1A, Sentinel-1B, TDX, TSX
Sensor(s):
C-SAR, OLI, SAR, X-SAR
Data Format(s):
GeoTIFF, JPEG, Shapefile
Temporal Coverage:
1 December 2014 to 30 November 2020
Temporal Resolution:
  • 1 year
Spatial Resolution:
  • 200 m
  • 200 m
Spatial Reference System(s):
WGS 84 / NSIDC Sea Ice Polar Stereographic North
EPSG:3413

WGS 84
EPSG:4326
Spatial Coverage:
N:
83
S:
60
E:
-14
W:
-75
Blue outlined yellow areas on the map below indicate the spatial coverage for this data set.

Data Access & Tools

This data set has been retired. There is a more recent version of these data.

Sample Data Image

Image
Annual ice velocity mosaic

This color-coded map shows an annual ice velocity mosaic for the Greenland Ice Sheet. Highest velocities appear in magenta and red, intermediate velocities appear in blue and green, and lowest velocities appear in yellow and peach. Credit: NASA MEaSUREs GrIMP Data: DLR, ESA, USGS

Help Articles

How to Articles

Many NSIDC DAAC data sets can be accessed using the NSIDC DAAC's Data Access Tool. This tool provides the ability to search and filter data with spatial and temporal constraints using a map-based interface.Users have the option to
Below the image in this article, 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 the following data products:
We recommend using the Geospatial Data Abstraction Library (GDAL) to convert GeoTIFF files into a different format.
We recommend using the Geospatial Data Abstraction Library (GDAL) or a GIS to reproject geoTIFF files.
There are external Jupyter notebooks available that can be used to search for GrIMP products and incorporate them into a new QGIS project:
There are external Jupyter notebooks available that can be used to download user-defined spatial subsets of the following MEaSUREs GrIMP products:
All 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, using wget or curl. Basic command line instructions are provided in the article below.