223 
should 
ulE as in 
= r . ) - 
s, ir' 
term r 
it may Y)'e r 
nating the 
lit in the 
(8) 
nating LAI, 
red reflec- 
bhis paper) 
>) must be 
md (8) is 
lodel. In 
; the asymp- 
frared and 
:tances in 
umed to be 
;quivalent 
= C 2 = 1. 
situation 
; green, red 
roach will 
a set cal- 
, and pro- 
ified with 
LAI SAIL MODEL LAI SAIL MODEL 
LM SAIL MOOEL SAIL MODEL 
)EL 
ration index 
g the cor- 
ired to the 
Lf soil re 
stions with 
swing vari- 
red reflec- 
= 24.2 %); 
■ed reflec- 
= 12.1 %); 
Le: 45°). 
/nwards. 
mce of a 
-ed reflec- 
45 %, 
î the fol 
ios) 5.0 
SAIL MODEL LM SAIL MODEL 
Figure 1: Three methods of correction for differ 
ences in soil moisture content in estimating LAI. 
Spherical leaf angle distribution, 
xx: calculated points SAIL model 
—: simplified reflectance model. 
(Rw is used for r . and a is used for a in this 
figure; CV = coefficient of variation, cf. section 
4.5). 
:e factors 
lodel for 
tance was 
lently this 
:or estima- 
¡quation (6) 
corrected 
oe called 
splied with- 
I. In prac- 
-e not known, 
sred reflec 
tances are 
/ill be test- 
Ltion to me- 
36a), ascer- 
by taking 
and red re 
pared with 
for all 
three meth- 
3 expected, 
the estimate of r was slightly less for method 
2 as compared witn'¥he one for the other methods, 
due to the different interpretation which has to be 
given to this parameter. The drastic simplification 
by method 2 yielded results that were, in general, 
not much worse than those obtained with the other 
methods. 
A more extensive verification of the infrared-red 
vegetation index by means of calculations with the 
SAIL model for several leaf angle distributions and 
also for skylight only are presented by Clevers 
(1986c). One of the questions that have to be in 
vestigated with real data in a multitemporal anal 
yses is whether the leaf angle distribution of a 
crop varies strongly during the growing season and 
disturbs the relationship between corrected infra 
red reflectance and LAI (see section 4.5). Results 
presented by Clevers (1986c) show that distinct leaf 
angle distributions cause distinct asymptotic values 
for the infrared reflectance, calculated from the 
SAIL model. 
4 RESULTS 
4.1 Field data 
The research was carried out at the ir. A.P. Minder- 
houdhoeve, experimental farm of the Wageningen Agri 
cultural University (the Netherlands), situated in 
one of the new polders, Oost-Flevoland, which was 
reclaimed about 30 years ago. The new polders are 
flat, uniform and highly productive agricultural 
lands with a loamy topsoil. 
For investigating the relationship between re 
flectances and LAI results of a field trial in 1982 
were used. The trial considered (No. 116) was a 
split-plot design with three replicates with barley, 
cultivar "Trumpf". Whole-plot treatments were 2 so 
wing dates: 26 March (Zl) and 22 April (Z2). Split- 
plot treatments were 6 randomized nitrogen levels 
(applied before sowing): 0, 20, 40, 60, 80 and 
100 kg/ha nitrogen (N1 to N6). Each subplot was 
6 m by 18 m and the row width was 13 cm. 
4.2 Method of gathering data 
LAI was ascertained by harvesting all the plants 
within a row section of 1.0 metre length (0.13 m 2 ). 
After ascertaining fresh weight of the whole sample, 
a subsample was separated into leaf blades, stems 
and ears. Each component was weighed and the area 
of the green leaf blades was measured with an op 
tically scanning area meter. These measurements 
were converted to give LAI values. LAI was measured 
on three harvest dates during the vegetative stage 
of the barley crop. 
Reflectances presented in section 4.5 of this pa 
per were obtained by means of multispectral aerial 
photography (MSP). Calibrated reflectance factors 
were obtained by atmospheric correction and radio- 
metric calibration of the digitized photographs on 
5 dates during the vegetative stage. This technique 
has been described extensively by Clevers (1986b, 
1986c). 
4.3 Data analysis 
The main field of interest in this study was to in 
vestigate the possibilities of estimating LAI by 
some corrected infrared reflectance factor. One of 
the complications of sampling agricultural field 
trials in the conventional way for LAI ascertain 
ment is that this procedure is destructive. To keep 
the plots fairly intact, only small samples are 
taken. The resulting variability of such data will 
be relatively large. These disturbances may be de 
creased by data smoothing (see Clevers, 1986c). In 
the present study, the means per treatment were 
smoothed. An important aspect of this smoothing is 
that it also involved an interpolation technique ; 
thus, it was possible to estimate the LAI on every 
date during the growing season. 
The smoothed estimated LAIs from field measure 
ments for the dates of flying missions were then 
related to reflectance measurements. Subsequently, 
the relationship between LAI (field measurements) 
and reflectance was used as a regression curve for 
estimating LAI per plot from the reflectance measure 
ments . 
4.4 Reflectance of bare soil 
The main assumption introduced by Clevers (1986a) 
was that there is a constant ratio between the re 
flectance factors of bare soil in two spectral 
bands, which is independent of soil moisture con 
tent for the soil type used in this research. In 
this paper the assumption was even that this ratio 
nearly equals one in order to apply the vegetation 
index derived in section 2.2.