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Retrieving dry snow density with SIR-C polarimetric SAR data
Authors:Zhen Li  Huadong Guo  Jiancheng Shi
Institution:(1) Laboratory of Remote Sensing Information Sciences, Institute of Remote Sensing Applications, Chinese Academy of Sciences, 100101 Beijing, China
Abstract:For a given incidence angle at the snow surface, a greater snow density causes a greater change in the incidence angle at the snow-ground interface; for a given snow density, however, a larger incidence angle at the snow surface results in a greater change in the refractive angle in the snow layer, by comparing the difference of incidence angle at the snow-ground interface and the air-snow interface with different snow density. Algorithm for estimating dry snow density used backscattering measurements with polarimetric SAR at L-band frequency is developed based on simulation of the surface backscattering componentsσ g hh andσ g vv using the IEM model and regression analysis. The comparison of the estimated snow density from SAR L-band images with that from field measurements during the SIR-C/X-SAR overpass shows root means square error of 0.050 g/cm3. It shows that this algorithm can be accurately used to estimate dry snow density distribution.
Keywords:polarimetric SAR  dielectric constant  backscattering  dry snow density  retrieving
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