Retrieving dry snow density with SIR-C polarimetric SAR data |
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Authors: | Zhen Li Huadong Guo Jiancheng Shi |
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Institution: | (1) Laboratory of Remote Sensing Information Sciences, Institute of Remote Sensing Applications, Chinese Academy of Sciences, 100101 Beijing, China |
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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. |
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Keywords: | polarimetric SAR dielectric constant backscattering dry snow density retrieving |
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