Full text: Remote sensing for resources development and environmental management (Vol. 1)

INFRARED REFL. (X) 
FIELD TRIAL 92 in 1982 
Figure 5: Seasonal change in infrared reflectance 
as a function of fungicide treatment (FO and FI) 
for two sowing densities (SI and S2). Field trial 
92 in 1982. 
Figure 6: Seasonal change in infrared reflectance 
for field trial 92 in 1983. 
INFRARED REFL. (X) 
FIELD TRIAL 95 in 1983 
10 
Sso 
200 
250 300 
DAYS AFTER SOWING 
Figure 7: Seasonal change in infrared reflectance 
for field trial 95 in 1983. 
explanation. Moreover, the same phenomenon could 
be observed in field trial 116 in 1982 (figure 2). 
Probably an increased influence of soil background 
because of the wilting and even the dropping of dead 
leaves at the end of the growing season was respon 
sible for this decrease in reflectance. 
Both in field trials 116 in 1982 and in 1983 ef 
fects of nitrogen nutrition were most pronounced 
for the infrared reflectance. In general, Clevers 
(1986b) showed that treatment effects could be as 
certained with largest power by means of the infra 
red reflectance. Therefore, only results for the 
infrared reflectance will be presented for field 
trial 92 in 1982 and field trials 92 and 95 in 1983. 
Treatment effects for plots with and without fun 
gicide treatment and for two sowing densities in 
field trial 92 in 1982 and in field trials 92 and 
95 in 1983 are illustrated in figures 5, 6 and 7, 
respectively. In all three field trials the effect 
of the fungicide treatment was significant, posi 
tive, at the end of the growing season. The sowing 
density effect, in general, was evident up to the 
end of the growing season and then was overruled 
by the fungicide treatment effect. 
3.2 Estimation of LAI 
For estimating LAI a corrected infrared reflectance 
was calculated by subtracting the contribution of 
the soil from the measured reflectance as described 
by Clevers (1986b). For estimating LAI the growing 
season was subdivided into two stages: vegetative 
and generative. First, the corrected infrared re 
flectance was calculated by taking the difference 
between infrared and red reflectance. Subsequently 
this corrected infrared reflectance was used for 
estimating LAI according to the inverse of a special 
case of the Mitscherlich function. For this latter 
regression two parameters had to be estimated, which 
are different in the two stages. The inversion prob 
lem was solved in an empirical way. For the vege 
tative and the generative stages the regression of 
LAI on corrected infrared reflectance was described 
reasonably in all field trials by using this func 
tion. This is illustrated in figures 8 and 9 (see 
Clevers, 1986b, for details). In practice, the re 
gression function of LAI on corrected infrared re 
flectance can be established by analysing a training 
set of a few (additional) plots, in which both re 
flectances and LAI are ascertained. Subsequently, 
this regression function can be applied for estima 
ting LAI in an entire field trial (Clevers, 1986b). 
Results for field trial 116 in 1983 are analysed 
further since soil moisture content varied signif 
icantly during the beginning of the growing season 
(see figure 4). Results of the corrected infrared 
reflectance are given in figure 10. The influence 
of soil moisture content at the beginning of the 
growing season has been eliminated (cf. red and 
Figure 8: Regression of LAI on corrected infrared 
reflectance. Field trial 116, vegetative stage, 1982 
Figure 9: Regression of LAI on corrected infrared 
reflectance. Field trial 116, generative stage, 1982
	        
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