Remote
sensing is a useful tool for mapping and monitoring areas of our planet
where it would be difficult if not impossible. Remote sensing data can
be divided into two major categories: microwave and optical data.
Microwave data provide continuous temporal coverage because collected
data do not dependent on solar illumination
and clouds presence. Also, the high penetration depth of microwaves
allows us to observe not only the surface of the scene under study but
also the characteristics of its deeper layers. Microwave data are
collected with a coarse spatial resolution (i.e. 25 Km in the case of
brightness temperatures). Optical data require
free-clouds areas and solar illumination and they can provide
information only on the surface of the scene but have the benefits of
having high spatial resolution.
Snow
is a fundamental element of water and energy cycles, representing an
important source of fresh water storage. Remote sensing can be
used for extracting and monitoring geophysical parameters of
hydrological and climatological interest, such as snow water equivalent
(the amount of water stored within the snowpack), snow covered
area and snow depth. Optical sensors can provide information on the
snow covered areas, surface grain size, impurities. This information
can be used to improve the performance of Global Circulation Models or
Budget Energy Models. On the other hand, microwaves provide information
on the amount of liquid water stored
within the snowpack, the onset melting of snow, mean grain size.
In
this talk, we will give an overview on the different aspects involved
in the remote sensing of snow: modeling, experimental observations and
retrieval techniques. All of these components are fundamental for
different aspects such as understanding the physical processes,
developing and validating models, improving and/or proposing
retrieval techniques. We will talk about the 'state of the art' of
electromagnetic modeling for snow, we will describe several experiments
carried out in both Europe and U.S.A. and we will review techniques
used for the extraction of snow parameters.