Toward an Operational Method for Refined Snow Characterization Using Dual-Polarization C-Band SAR Data

This paper presents a method to characterize snow cover at a massif scale using dual-polarization C-band SAR data. It is demonstrated that it is crucial to exactly model the distribution of liquid water inside the snowpack in order to perform accurate snow characterization at C-band. Consequently, t...

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Bibliographic Details
Main Authors: Longepe, N., Allain, S., Pottier, E.
Format: Conference Proceeding
Language:English
Subjects:
Backscatter
Ice
Meteorology
Moisture
Nonhomogeneous media
Optical scattering
Permittivity
Remote monitoring
Remote Sensing
Shape
Snow
Synthetic Aperture Radar
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Summary:This paper presents a method to characterize snow cover at a massif scale using dual-polarization C-band SAR data. It is demonstrated that it is crucial to exactly model the distribution of liquid water inside the snowpack in order to perform accurate snow characterization at C-band. Consequently, the key point of this new method consists in using a multi-layer meteorological snow model. Based on a validated multi-layer EM backscattering model, SAR data and snow profiles estimated by the weather model can be combined. An adequate spatial reorganization of these snow profiles leads to a refined snow characterization. Accurate snow monitoring like Liquid Water Content is presented, opening the way for a new operational method.
ISSN:2153-6996
2153-7003
DOI:10.1109/IGARSS.2008.4778926