very special conditions to satisfying results /McDo 
nald, Hall 1978/. To improve the performance of the 
remote sensing technique for yield estimation some 
more detailed and complex investigations are necessa 
ry. 
2 THE CONCEPTION OF THE PROJECT 
Main topic of the project is the improvement of the 
power of remote sensing techniques for yield estima 
tion of agronomic targets. That means the improvement 
of accuracy and reliability of the yield estimation 
and, in contrast to already existing methods, the 
application onto the typical ground cover characte 
ristics in Europe with relatively small fields and 
frequent changes in the cultivated plants. 
The spectral data which will found the base in a 
future stage of application will originate from 
spaceborne satellite sensors as they are used today. 
However, the spectral bands of the future systems 
should be stronger designated to the agronomic appli 
cation. 
It is aimed to approach the results for relations 
between reflected radiation and plant characteristics 
as they were found in the laboratory. The realization 
of this demanding aim needs in a first step a very 
extensive investigation of the spectral and agronomic 
parameters and their interaction. This will be done 
by a very broad data collection procedure in the 
field using sophisticated equipment. 
The main aspects of the project which should help to 
indicate how to realize the improvement and which 
should give better understanding of the relationships 
between plants and radiation read as follows: 
1. Taking a great number of frequently repeated 
field measurements allowing to record the influence 
of the yield relevant and plant typical phenology 
/Doerfel, 1978/. 
2. Collection of a broad spectrum of agronomic 
parameters like physiology, morphology and other 
informations describing the stage of the plant 
growth and health. 
3. Realization of spectral field measurements cove 
ring a broad window of the electromagnetic spectrum 
ranging from 0.4 - 2.2 jjm. 
4. High spectral resolution in the measurements 
(0.002 - 0.004pm) assuring good sensitivity in the 
detection of qualitative changes in the plant re 
flection. 
5. Extensive compensation of effects originating 
from exterior influences which may reduce the qua 
lity of the measurments. 
One major influence exists in the atmospheric situa 
tion during measurement which has to be taken into 
account, because very different illumination condi 
tions have to be expected for the high frequent 
repititions. Other important parameters are the mi 
croclimatic situation, the surface topography of the 
plant targets and the geometric relations between 
light source, targets and measuring device. 
3 ORGANIZATION OF THE MEASUREMENTS 
3.1 Plant cultivation 
The investigations will concentrate on two different 
plant species of different phenotype. The first one, 
way 
Figure 1 : Arrangement of cultivated plant species 
winter wheat, is an often used plant for which alrea 
dy successful yield estimation could be attained 
/McDonald, Hall 1978/. The second one, sugar beets, 
is of heterogenous shape and serves as touchstone for 
the improvement to be expected. 
The two plants are cultivated in a great field with 
six different spots. In each spot we have one of 
three plant species (sugar beet, winter wheat, bar 
ley), which are cultivated following the rotation 
principle (cf. fig.l). 
For each plant in consideration we have three indé 
pendant cultivation parameter. These parameters are 
plant density (D^,D 2 ), seed time (T^»T 2 ) and nitrogen 
fertilization (NpN 2 ) for sugar beets and fungizid 
treatment (F^,F 2 ), wheat species (S^,S 2 ) and nitrogen 
fertilization (N^,N 2 ) for winter wheat. These parame 
ters were chosen to produce distinct differences in 
plant growth, health and plant production in order to 
have good pre-conditions to find typical changes in 
the reflection characteristic. 
All parameters are varied with each other so that we 
have in total 8 plots of different cultivation (cf. 
fig. 2) 
Each plot has a special organization for the collec 
tion of agronomic and radiometric data. It is divided 
into 7 s 
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