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Sea ice drift data for Fram Strait derived from a feature-tracking algorithm applied on Sentinel-1 SAR imagery
Stefan Muckenhuber1, Stein Sandven1
1Nansen Environmental and Remote Sensing Center (NERSC), Thormøhlensgate 47, 5006 Bergen, Norway.
Data in Brief
|June 16, 2018
Summary
Sea ice drift was measured using Sentinel-1 SAR images from 2014-2016 in Fram Strait. Monthly mean sea ice velocities were calculated at 79°N using feature tracking.
Area of Science:
- * Remote Sensing
- * Oceanography
- * Glaciology
Background:
- * Accurate sea ice drift data is crucial for climate modeling and navigation in Arctic regions.
- * Satellite Synthetic Aperture Radar (SAR) offers a reliable method for monitoring sea ice dynamics.
- * The Fram Strait is a key region for Arctic sea ice export.
Purpose of the Study:
- * To retrieve sea ice drift velocities using Sentinel-1 SAR data.
- * To analyze monthly mean sea ice velocities in the Fram Strait.
- * To validate the effectiveness of an open-source feature tracking algorithm for sea ice monitoring.
Main Methods:
- * Utilized 1541 Sentinel-1 SAR images acquired between 2014 and 2016.
- * Applied an open-source feature tracking algorithm for sea ice drift retrieval.
- * Processed 2026 (HH) and 3120 (HV) image pairs for velocity calculations.
Main Results:
- * Successfully retrieved sea ice drift data from Sentinel-1 SAR imagery.
- * Calculated monthly mean sea ice velocities at 79°N.
- * Demonstrated the capability of the feature tracking algorithm in deriving sea ice motion.
Conclusions:
- * Sentinel-1 SAR data is effective for monitoring sea ice drift in the Fram Strait.
- * The open-source feature tracking algorithm provides reliable sea ice velocity estimates.
- * The findings contribute valuable data for understanding Arctic sea ice dynamics.
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