697 
! calculated 
alength with 
Lon ratio at 
i respective 
on has large 
Kimation for 
gth than the 
r*W) differs 
n index. The 
ts the shape 
s with high 
can be esti- 
1 the red or 
nee of this 
nee angular 
ly, the new 
Lon as its 
mattering of 
significant 
d, 1993). In 
e estimated 
ctance data 
tances were 
visible and 
d are given 
model with 
msmittance 
af inclin- 
red soil 
calculated 
e measured 
discrepancy 
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 
reflectance. 
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. 
5. CONCLUSION 
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. 
Acknowledgements 
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.