Spaceborne GNSS-R Sea Ice Detection Using Delay-Doppler Maps: First Results From the U.K. TechDemoSat-1 Mission

In this paper, a scheme is presented for detecting sea ice from Global Navigation Satellite System-Reflectometry (GNSS-R) delay-Doppler maps (DDM). Less spreading along delay and Doppler axes were observed in the DDMs of sea ice relative to those of seawater. This enables us to distinguish sea ice f...

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Bibliographic Details
Published in:IEEE journal of selected topics in applied earth observations and remote sensing 2016-10, Vol.9 (10), p.4795-4801
Main Authors: Yan, Qingyun, Huang, Weimin
Format: Article
Language:English
Subjects:
Delay
Delay-Doppler map (DDM)
Doppler
Doppler effect
Global Navigation Satellite System-Reflectometry (GNSS-R)
Ice
Marine
Melting
Remote sensing
Satellites
Sea ice
sea ice detection
Sea surface
Sea water
Sensors
Spreading
Thresholds
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Summary:In this paper, a scheme is presented for detecting sea ice from Global Navigation Satellite System-Reflectometry (GNSS-R) delay-Doppler maps (DDM). Less spreading along delay and Doppler axes were observed in the DDMs of sea ice relative to those of seawater. This enables us to distinguish sea ice from seawater through studying the values of various DDM observables, which describe the extent of DDM spreading. The area associated with a DDM that results in an observable below or above a threshold value will be classified as covered by sea ice and seawater, respectively. In particular, this study applies an adaptive incoherent summation to each DDM with efforts to increase signal-to-noise ratio and avoid the averaging between DDMs collected over surfaces of different types. Accordingly, an adaptive threshold is employed for the derived observable based on the incoherent summation interval for its corresponding DDM. The proposed sea ice detection method is tested with five different DDM observables. Through comparing DDM observable-based detection results with ground-truth sea ice data, the feasibility of this method is validated with an accuracy of up to 99.73% based on the pixel number observable.
ISSN:1939-1404
2151-1535
DOI:10.1109/JSTARS.2016.2582690