MEaSUREs Greenland Image Mosaics from Sentinel-1A and -1B, Version 4
Data set id:
DOI: 10.5067/WXQ366CP8YDE
This is the most recent version of these data.
Version Summary
This version contains the following changes:
-Updated temporal coverage
-Data reprocessed utilizing a corrected DEM. See user guide for details.


This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, consists of 6-day and 12-day 50 m resolution image mosaics of the Greenland coastline and ice sheet periphery. The mosaics are derived from C-band Synthetic Aperture Radar (C-SAR) acquired by the Copernicus Sentinel-1A and -1B satellites. See Greenland Ice Mapping Project (GrIMP) for related data sets.
Data Format(s):
GeoTIFF, JPEG, Shapefile
Temporal Coverage:
1 January 2015 to 31 January 2024
Temporal Resolution:
  • 6 days to 12 days
Spatial Resolution:
  • 50 m
  • 25 m
  • 500 m
  • 50 m
  • 25 m
  • 500 m
Spatial Reference System(s):
WGS 84 / NSIDC Sea Ice Polar Stereographic North

WGS 84
Spatial Coverage:
Blue outlined yellow areas on the map below indicate the spatial coverage for this data set.
Strengths and Limitations


  • Image and normalized backscatter (sigma0) data are good for interpreting geographical and glaciological features, such as glacier terminus positions.
  • Radiometrically terrain-corrected backscatter (gamma0) data are useful for looking at backscatter changes (e.g., from melt events), independent of the incident angle and topography.
  • Good for investigating temporal changes.
  • Relative geolocation accuracy is a few meters or less (except where large changes in surface elevation are present, e.g., the lower Jakobshavn catchment (Joughin et al., 2016).


  • In regions of high topography, sigma0 and gamma0 data can have much larger errors compared with flat areas.
  • Absolute geolocation is only as good as the DEM used for terrain corrections — an error of only a few meters for most of the ice sheet. However, location errors can be >20 m in steeply sloping terrain or in areas where the surface has changed (e.g., thinned) relative to the DEM.

Data Access & Tools

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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.