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Remote sensing for resources development and environmental management
Damen, M. C. J.

Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986
The derivation of a simplified reflectance model
for the estimation of LAI
Dept, of Landsurveying and Remote Sensing, Wageningen Agricultural University, Netherlands
ABSTRACT: Information about crop reflectance obtained from the literature suggests that reflectance factors in
the near-infrared are most suitable for estimating leaf area index (LAI). A problem arises if a multitemporal
analysis is required. Soil moisture content is not constant during the season and differences in soil moisture
content greatly influence soil reflectance. A correction for soil background has to be made when ascertaining
the relationship between reflectance and crop(characteristics.
Since in the literature no satisfactory solution for correcting for soil background was found, an appropriate
simplified reflectance model for estimating LAI is presented. First of all, an apparent soil cover is defined.
Then, a corrected infrared reflectance is calculated by subtracting the contribution of the soil from the mea
sured reflectance. The assumption that there is a constant ratio between the reflectances of bare soil in
different spectral bands, independent 6f soil moisture content, enables the corrected infrared reflectance to
be calculated without knowing soil reflectances. Subsequently, this corrected infrared reflectance is used for
estimating LAI according to the inverse of a special case of the Mitscherlich function. Simulations with the
SAIL model confirmed the potential of this simplified (semi-empirical) reflectance model for estimating LAI.
Remote sensing techniques enable information about
agricultural crops to be obtained quantitatively,
instantaneously and, above all, non-destructively.
During the past decades knowledge about remote
sensing techniques and their application to fields
such as agriculture has improved considerably.
Bunnik (1978) demonstrated the possibilities of
applying remote sensing in agriculture, particularly
with regard to its relation with crop characteristics
such as soil cover, leaf area index (LAI) and dry
matter weight. LAI is regarded as a very important
plant characteristic because photosynthesis takes
place in the green plant parts.
One of the main results of the work done by
Bunnik (1978) was the identification of five wave
lengths based on optimum information about variation
in relevant crop characteristics. These wavelengths
were: one in the green at 550 nm, one in the red at
670 nm, one in the near-infrared at 870 nm and (to
a less extent) two in the middle-infrared - one at
1650 nm and the other at 2200 nm. In the literature
there is a certain consensus that bands in the green,
red and near-infrared regions are optimal if infor
mation about vegetation is to be obtained (e.g.
Kondratyev & Pokrovsky, 1979).
From the literature it is evident that, in the
visible region, vegetation absorbs much radiation
(for photosynthesis) and shows a relatively low
reflectance. This is especially true in the red
region, because of the large absorption of this
radiation by the chlorophyll in the leaves. In the
near-infrared region the opposite occurs. The spec
tral reflectance in this region is high. In the
visible and near-infrared region the reflectance and
transmittance of a green leaf are approximately equal
(e.g. Goudriaan, 1977; Youkhana, 1983).
The low transmittance of a green leaf in the
visible region implies that in this region only the
reflectance of the upper layer of leaves determines
the measured reflectance of that canopy. In the near-
infrared region the transmittance of a green leaf is
in the order of 50%, and there is hardly any infrared
absorptance by a green leaf. In this situation leaves
or canopy layers underneath the upper layer contri
bute significantly to the total measured reflectance.
This contribution decreases with increasing depth in
the canopy (and is negligible from 6-8 layers onwards).
This multiple reflectance indicates that the infrared
reflectance may be a suitable estimator of LAI.
Soil reflectance has an important influence on the
relationship between reflectance and LAI. At low soil
cover, soil reflectance contributes strongly to the
measured reflectance in the different spectral bands.
For a given soil type, soil moisture will be the main
factor determining soil reflectance. An increasing
moisture content of the soil causes the reflectance to
decrease, but the relative effect of soil moisture on
the reflectance at distinct wavelengths is similar
(Bowers & Hanks, 1965). Janse & Bunnik (1974) noticed
that reflectance decreases with increasing soil
moisture content, but this decrease is almost indepen
dent of wavelengths between 400 nm and 1000 nm for a
sandy soil. This means that the ratio of the reflec
tance in two spectral bands in this interval is nearly
independent of soil moisture content. Results obtained
by Condit (1970) and Stoner et al. (1980) confirm that
the ratio of the reflectance in two spectral bands is
independent of the soil moisture content.
The starting point of the study of this paper were
calibrated reflectance factors in the green, red and
near-infrared. These may be obtained, for instance, by
means of multispectral aerial photography. The
radiometric calibration and atmospheric correction of
such measurements are described by Clevers (1986a,
1986b). The main aim was to investigate some index or
model, derived from reflectance factors, for estima
ting LAI in a multitemporal analysis. In order to
enable such a multitemporal analysis a correction for
soil background should be made. The ideal model for
practical applications is one that is simple and
requires the least number of input variables. For
instance, if the agronomist has to ascertain a leaf
angle distribution (necessary for some existing
models), he will probably prefer to collect the
conventional field data as he has always done.