Author(s): Markku Simila; Marko Makynen; Istvan Heiler
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Abstract: A statistical analysis was performed for nearly simultaneously acquired C-band SAR images and ice freeboard statistics. The data analyzed were collected during a CryoSat ca librationvalidation campaign in March 2005 in the Baltic Sea. A 3-D ice freeboard topography along transects with a total length about 150 km and width 300 m was constructed from cross-track scanning airborne laser scanner measurements. Two nearly co-incident ENVISAT ASAR APP and IMP images at HH-polarization with the incidence angle ranges deviating about 20 degrees constituted the SAR image set. The data set for the low-salinity sea ice was gathered in cold weather conditions w ith the snow cover being very thin. The variance of the mean freeboard increased with increasing mean freeboard with the chosen window size (300 m) up to the mean freeboard of 15 cm. This multiplicative character of sea ice cover forms the basis why we can expect that the C-band backscattering coefficient response, which depends only on the ice surface characteristics and the top part of ice layer, can convey information about the sea ice thickness. A nonlinear regression model with three control variables, the backscattering coefficient, the dominant thickness of the level ice which has deformed, and a variable accounting the effect of the incidence angle was established to predict the variation of the ice freeboard. The applied Bayesian approach provided means to estimate also the uncertainty range for the model fitting and the model predictions. The modeled predictions were mostly in good agreement with the measured values. The predictions for three different test lines accounted from 67 \% to 85 \% from the measured freeboard variance in 300 m scale. In cold conditions with thin snow cover it was possible to quantitatively estimate the degree of ice deformation and ice thickness from Cband SAR images.
Year: 2010