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Mesures physiques et signatures en télédétection

were made in cold laboratory in Grenoble. These pictures allows to characterize snow grains morphology.
Moreover, an image analysis system gives out the mean convex radius of these snow grains. This parameter
is computed from the mean convex radius of curvature of randomly chosen clusters of about 30 to 50
different crystals. The mean convex radius of snow grains can be taken as an objective snow grains size
factor. Previous study (Sergent et al., 1993) established a relationship between mean convex diameter and
theoretical spherical diameter according to Warren and Wiscombe (1980) modeling.
3.1.2. Optical parameters measurements
For some sites, measurements of optical parameters of surface snow were made. For these measurements,
large amount of surface snow was collected in the field and brought back in isothermal boxes to the cold
laboratory in Grenoble and the measurements made in the following days. The optical parameters were
measured under diffuse incident light on large snow samples according to the semi-infinite assumption. The
measurement device gives out the spectral albedo by step of 10 nm from 0.4 to 1.0 pm.
3.2. Remote sensing data
3.2.1 Geometrical corrections
Because we need to merge different set of data (Landsat TM, SPOT, Push-Broom) with a DEM (Digital
Elevation Model) in order to get the local incidence angles and to compare with the CROCUS results, we
have to produce geolocated images with a misregistration error less than 30 m. All the images 'were
corrected by using a resampling method based on Spline-B functions with a set of ground control points.
The geometrically corrected image coordinates are given in the Lambert-III French cartesian projection.
The DEM was used to test the quality of the result by comparison between the cartographic and the image
coordinates of each measurement site. The DEM we used is very precise with elevations on a 30 m x 30
m grid.
Because ISM is not an imaging system there is no geometrical correction to do but the difficulty is to locate
the pixels. To do so we use the video records or the the push-broom images when available.
3.2.2 Reflectance determination
For the Landsat, SPOT and Push-Broom data the radiances measured by the satellite are computed from
the calibration coefficients given by EOSAT on the tape or by the CNES. The 5S model (Simulation of the
Satellite Signal in the Solar Spectrum, Tanre et al., 1986) is used to retrieve the apparent ground reflectance
for an horizontal surface and, then, a DEM to get the real ground reflectance. Water reflectance on lakes
or laboratory measurements of snow reflectance are useful to calibrate the data.
For the ISM spectrometer the determination of absolute values is more difficult We still are processing the
data. For the reflectance determination we will use the transfer functions as measured in laboratory but also
sky measurements which were done on the top of the aircraft.
Snow cover evolution at a given location is mainly depending on the prevailing meteorological conditions.
They govern its energy and mass balance and therefore the metamorphism of each different layer. They
govern also the presence of liquid water inside the snowcover. A physically-based numerical model, called
CROCUS, has been developed to simulate all these phenomena (Brun et al., 1992). It derives a complete
description of the snow cover including temperature, density, liquid water content, age and stratigraphy of
the different layers as a function of the prevailing meteorological conditions.
In many applications, as for the present Field experiment, no complete serie of meteorological observations
are available at the particular experiment points. For these reasons, a meteorological objective analysis
model has been developed (SAFRAN), in order to provide Crocus with its necessary input data. It aims to
establish hourly surface meteorological conditions at different idealized particular points of the Alpine
ranges. Based on the statistical interpolation, it uses all the available observations as well as numerical