MEaSUREs Greenland Annual Ice Sheet Velocity Mosaics from SAR and Landsat, Version 5
Data set id:
NSIDC-0725
DOI: 10.5067/USBL3Z8KF9C3
This is the most recent version of these data.
Version Summary
Updates for Version 5:
* Improved correction for submergence/emergence velocity using an average of RACMO2.3 and MAR3.12 SMB for the period from 1958 to 2021
* Calibration improved by using an improved balance velocity estimate, computed as the average of RACMO2.3 and MAR3.12, and by excluding GPS points >2000 m from the 1990s.
* Solid Earth tides corrected using PySolid (https://github.com/insarlab/PySolid)
* Includes Landsat 9 data from 2022 onward
* Landsat-specific data files now designated by “LS” in the file name (instead of “LS8” as in previous versions).

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. Velocities are derived from synthetic aperture radar (SAR) data, obtained by TerraSAR-X/TanDEM-X and Sentinel-1A and -1B, and from optical imagery acquired by Landsat 8 and Landsat 9. See Greenland Ice Mapping Project (GrIMP) for related data.
Parameter(s):
ICE VELOCITY
Platform(s):
LANDSAT-8, LANDSAT-9, Sentinel-1A, Sentinel-1B, TDX, TSX
Sensor(s):
C-SAR, OLI, OLI-2, SAR, X-SAR
Data Format(s):
GeoTIFF, JPEG, Shapefile
Temporal Coverage:
1 December 2014 to 30 November 2023
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:
58.5
E:
8.32
W:
-90.9
Blue outlined yellow areas on the map below indicate the spatial coverage for this data set.

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) is directly accessible through our HTTPS file system using Wget or curl. This article provides basic command line instructions for accessing data using this method.