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

226
the smaller CV values for the estimates of LAI. How
ever, these latter CV values were larger than those
for infrared reflectance. Similar conclusions could
be drawn for other field trials (Clevers, 1986c).
The following practical procedure has been elabo
rated by Clevers (1986c):
In one field trial, the regression function of LAI
on corrected infrared reflectance was established
by analysing a few additional plots (a training set),
in which both LAI and reflectances were ascertained.
The inverse of a special case of the Mitscherlich
function was used for describing the regression
function of LAI on the infrared reflectance correct
ed for background. Subsequently, this regression
function was applied for estimating LAI in the en
tire field trial. To date there is insufficient evi
dence that the regression curves of different crops
or cultivars are easily transferable, or that the
curve of one growing season can be applied in the
following seasons, although the results of Clevers
(1986c) pointed in that direction. So, conventional
field measurements are still needed.
Verhoef, W., 1984. Light scattering by leaf layers
with application to canopy reflectance modelling
the SAIL model. Rem. Sens. Envir. 16: 125-141.
Youkhana, S.K., 1983. Canopy modelling studies.
Colorado State Univ., PhD., 84 pp.
5 CONCLUSIONS
1. If the ratio between the reflectance factors of
bare soil in any pair of the green, red and infra
red spectral bands is nearly one, the corrected
infrared reflectance may be ascertained as the dif
ference between the measured infrared and red re
flectance .
2. At the vegetative stage of cereals, the inverse
of a special case of the Mitscherlich function,
namely the one passing the origin, was suitable for
describing the regression function of LAI on cor
rected infrared reflectance.
3. If LAI was estimated by reflectance values, by
using a regression curve of LAI on corrected infra
red reflectance, the critical levels in testing for
treatment differences were in general smaller than
for the measured LAI of samples. This also applied
to the coefficients of variation. Even at large LAI
values (LAI 5-8) significant treatment effects could
be distinguished by means of multispectral aerial
photography.
6 REFERENCES
Bunnik, N.J.J., 1978. The multispectral reflectance
of shortwave radiation by agricultural crops in
relation with their morphological and optical
properties. Thesis, Meded. Landbouwhogeschool Wa-
geningen 78-1, 175 pp.
Clevers, J.G.P.W., 1986a. The derivation of a sim
plified reflectance model for the estimation of
LAI. Proc. Seventh Int. Symp. on Remote Sensing,
ISPRS Comm. VII, Enschede, The Netherlands.
Clevers, J.G.P.W., 1986b. Multispectral aerial
photography yielding well calibrated reflectance
factors with high spectral, spatial and temporal
resolution for crop monitoring. Proc. Third Int.
Coll, on Spectral Signatures of Objects in Remote
Sensing, Les Arcs, France.
Clevers, J.G.P.W., 1986c. The application of remote
sensing to agricultural field trials. Thesis (in
press).
Condit, H.R., 1970. The spectral reflectance of
American soils. Photogram. Eng. Rem. Sens. 36:
955-966.
Goudriaan, J., 1977. Crop micrometeorology: a simu
lation study. Thesis Landbouwhogeschool, Wageningen,
249 pp.
Stoner, E.R., M.F. Baumgardner, L.L. Biehl & B.F.
Robinson, 1980. Atlas of soil reflectance proper
ties. Agric. Exp. Station, Purdue Univ., W-Lafay-
ette, Indiana, Res. Bull. 962, 75 pp.