241 
a 35mm KODAK 
4 RESULTS AND DISCUSSION 
> or minus 2 
solar zenith 
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lm by 1.5m 
~ey card with 
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1 was judged 
etween camera 
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ght meters do 
tter speed 
Lsions. Hence 
ons were made 
0 ASA. It was 
suitable for 
-ding to NASA 
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ras used for 
points were 
sion densito- 
WRATTEN No 94 
red) filters 
ties relating 
jspectively, 
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ensities were 
unit spectral 
reen, red and 
1 number of 
it ions were 
re determined 
ison (1982). 
Tasseled Cap 
tained: 
for further 
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(Vegetation 
ence or ND 
Perpendicular 
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Lew). 
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;he amount of 
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28 S 
K 
ent. 
4.1. Green Leaf Area Index (GLAI) 
Development of GLAI was is markedly different for 
both growing seasons (Figure 2). It is supposed that 
significantly more rainfall, - April and June 
featured almost the double amount as usual caused 
stronger leaf development in 1985. In general the 
measured values agree with data given by other 
authors for sugar beets (Evans 1972, Thorne 1971). 
Figure 2. Sugar beet cover percentage (full line) and 
GLAI (dashed line) in function of time in 1984 (x) 
and 1985 (+). 
Linear relationships of low GLAI values with VI have 
been reported by Hinzmann et al (1986) for wheat and 
Badhwar et al (1986) for aspen forest. 
Asymptotic behaviour of retained ratios and 
combinations of reflectance could be observed for 
GLAI values larger than 2 (Figure 3), which is in 
agreement with results reported by Tucker (1977). Due 
to saturating reflectance large GLAI values cannot 
be estimated very accurately by spectral parameters. 
This puts severe constraints on yield prediction 
procedures as photosynthesis levels off at much 
higher GLAI values. 
Figure 3. Asymptotic behaviour of ND in function of 
sugar beet GLAI. 
Best fit regression analysis was run on the GLAI data 
and spectral parameters obtained in 1984 (Table 1). 
The indicated regressions were used to calculate 
predicted values based on 1985 spectral parameters 
and plotted against averaged measured GLAI values 
(Figure 4). Dispersion around the 1:1 line increases 
for high GLAI values, and PVI appears to be most 
powerful predictor for this biomass parameter. It 
should be noted that regression correlation 
coefficients were not indicative of predictive 
power. 
Table 1. Regressions of sugar beet GLAI and spectral 
parameters in 1984. 
Parameter Regression type 
Corr. coeff. 
VI 
power fit 
.77 
PVI 
power fit 
.79 
ND 
power fit 
.90 
GREENNESS 
logarithmic fit 
.81 
Figure 4. Relationship between measured (1985) and 
predicted GLAI for sugar beets. Dashes represent 1:1 
line. 
4.2. Cover percentage 
Complete closure of sugar beet canopy occurs in a 
relatively short time span (Figure 2). Hence few 
experimental data are available for low cover 
percentage. It is precisely for these low values that 
linear relationships with certain spectral parameters 
are reported in litterature (Colwell et al 1977 for 
wheat using VI, McDaniel 1982 for grasslands using 
ND). 
As can be seen in Figure 5 100 % coverage can yield 
varying spectral values. 
Figure 5. Asymptotic behaviour of ND for cover 
percentage of sugar beets.