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Greenland Ice Sheet CCI Products

Products generated by the Greenland Ice Sheet CCI project

 

The consortium

DTU Space
S[&]T
ENVEO
University of Leeds
GEUS""
DMI
NBI
NERSC
TU Dresden
ASIAQ

Details for product :


Upload date 29 Sep 2020
ECV IV
Product file greenland_iv_250m_s1_20191214_20200131_v1_3.zip
File size 632.8 MB

Preview image :
Description :

Greenland Ice Sheet Velocity 2019/20 from SENTINEL-1 winter campaign from 2019/12/14 to 2020/01/31.

Comments :

Greenland Ice Sheet Velocity - Winter Campaign 2019/2020: 250m gridded velocity map, generated applying coherent and incoherent offset tracking using SENTINEL-1 data acquired between 2019-12-14 and 2020-01-31.

This data set is part of the ESA Greenland Ice sheet CCI project. The file is including all measurements and annotation.
It provides components of the ice velocity, along with maps showing the horizontal magnitude, valid pixel count and uncertainty (based on the std.) within a NetCDF file.
The ice velocity map is provided on a polar stereographic grid (EPSG 3413) with 250m grid spacing.
The horizontal velocity is provided in true meters per day, towards Easting (x) and Northing (y) direction of the grid. The vertical displacement is derived from a digital elevation model.
The product was generated by ENVEO.

The Filename of the IV Products consists of:
greenland_iv_250m_s1___.
greenland: area
iv: parameter (ice velocity)
250m: grid spacing in meter
s1: platform (Sentinel-1)
: Date of first acquisition
: Date of last acquisition
: Version of the product in the format vMAJOR_MINOR
: Fileformat (nc: NetCDF)

see "Detailed IV product specifications" of "Product Specification Document" at "http://esa-icesheets-greenland-cci.org/"

ChangeLog:
v1.3: June 29, 2020 by markus.hetzenecker@enveo.at
Created Dataset

Citable as:
Greenland Ice Sheet velocity map from Sentinel-1, winter campaign 2019/2020 [version 1.3]

References:
Nagler, T., Rott, H., Hetzenecker, M., Wuite, J., Potin, P. (2015). The Sentinel-1 Mission: New Opportunities for Ice Sheet Observations.
Remote Sensing, 2015, 7, 9371-9389, doi:10.3390/rs70709371.