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Mesures physiques et signatures en télédétection

! calculated
alength with
Lon ratio at
i respective
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Kimation for
gth than the
r*W) differs
n index. The
ts the shape
s with high
can be esti1
esti1 the red or
nee of this
nee angular
ly, the new
Lon as its
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d, 1993). In
e estimated
ctance data
tances were
visible and
d are given
model with
af inclinred
inclinred soil
e measured
s where the
r than the
s to be the
lere should
be an obvious row structure of the
stand, and the assumption of homogeneity
is not fulfilled. A confirmation of that
is disagreement between the calculated
and the measured ground cover. A homo
geneous canopy with LAI =1.2 and leaf
inclination distribution, as given in
Fig. 2, should have the ground cover W
= 0.455, while the measured value was
W = 0.39 (Ranson et al., 1985). To
reduce the model ground cover to that
measured, the leaf area index must be
decreased to LAI = 1.0. The dashed line
in Fig. 4 shows the model canopy
reflectance spectrum of a canopy with
LAI = 1.0, with all other parameters as
given in Table 1. We note that the
agreement of the calculated and the
measured reflectance values has improved
in all spectral channels except
Channel 6 (1.55 - 1.75 pm). In that channel the soil is brighter than the green
vegetation and thus the decrease in the ground cover brings along the increase in
Figure 4. Corn canopy reflectance
spectrum (*) measured by Ranson et al.
(1985), ( ) calculated using the
measured and fitted input parameters,
( ) calculated for LAI = 1.0.
The new multispectral canopy reflectance model permits the calculation of the
directional reflectance of an homogeneous vegetation canopy with a high spectral
resolution for the whole optical spectral region. The set of model input parameters
includes 4 structural parameters, 4 geometrical and illumination parameters and 5
(to 8) parameters representing the optical properties of the leaves and the soil.
The number of model input parameters does not depend on the number of spectral
channels under consideration. The model may be used both for the theoretical
analysis of the stand reflectance as a function of biophysical and structural
characteristics of the canopy, and for the inference of vegetation parameters such
as the leaf area index, leaf inclination distribution, the soil reflectance
spectrum, the leaf water and chlorophyll content using remotely sensed data. Due
to limitations of the PROSPECT model we cannot analyse the influence of other
pigments on the canopy reflectance spectra.
The model is computationally efficient so that calculations can be performed
on a personal computer. Naturally the results of the model inversion depend on the
amount of information available. We cannot expect to determine all the input
parameters of the model with high accuracy from a few measurements of canopy
reflectance in a small number of spectral channels.
I am indebted to Dr. Stephane Jacquemoud for the Fortran code of the PROSPECT
model, and to Dr. Larry L. Biehl for the reflectance and phytometrical data of
corn. This research was partly supported by the Department of Forestry, University
of Joensuu.