rier 
ition 
sics, 
58. 
essung 
eri 
ltech/ 
p. Image 
Death 
rain 
nnual 
and 
pp. 
23. 
»cul- 
ind. 
Jniv. 
-61. 
mo 437, 
E 
H 
| 
+3,No.8. 
\ufnahmen", 
r Remote 
USA, 
Image 
ition of 
n Image 
al., USA. 
, God- 
PP. 
tral 
_L2(2). 
raphic 
on 
Cana- 
ALTERNATIVES IN CONDITIONAL TECHNOLOGIES 
Knut Bulow 
Remote Sensing Research Center 
U.S. Department of Agriculture 
Houston, USA 
I. Introduction 
Experience gained by analyzing several thousand scenes through the 
Large Area Crop Inventory Experiment (LACIE) (Ref 1) has taught the 
United States Department of Agriculture (USDA) analysts that there 
is no one optimum approach to processing all agricultural scenes. 
There exists an infinite number of ways to structure decisions in 
image interpretation, e.g. by spectral information, by procedures 
based upon variations in crop development, by relationship of 
spectral data to soil, climate, etc. It has been discovered that 
it is possible to "control" the variability among scenes by delin- 
eating areas that are relatively similar in soils, climate, and 
topography, (Ref 2), and by using alternate processing techniques 
based on scene characteristics. 
In remote sensing of agricultural activities there exists a wide 
variety of characteristics which dictates those candidate techniques 
which can be used in order to arrive at the best and most efficient 
results. Each of the different processing techniques, that have 
been developed in LACIE and other interpretation experiments has 
its own inherent limitations. Because of this, each technique should 
only be applied under certain conditions. When analyzing remotely 
sensed data in agriculture it is necessary to provide analysts with 
alternatives in conditional technologies versus those technologies 
which have no constraints and demand no alternatives. 
The constraints imposed upon a processing technique utilizing multi- 
spectral data are related to manpower, timeliness, data availability 
and characteristics, scientific limitations, accuracy and economic 
considerations. Each user can control several of these constraints 
through his requirements and resources. The two that he has little 
control over are scientific limitations and data availability and its 
characteristics. Since users have no control over scientific limi- 
tations one is forced to develop techniques for processing remotely 
sensed data around data availability and its characteristics. 
Space Administration (NASA), and the National Oceanographic and 
Atmospheric Administration (NOAA) to develop methods to estimate 
wheat production over designated areas. The method which was 
developed used meteorological and historical yield data to estimate 
wheat yields and Landsat data to estimate the areal extent of the 
wheat crop.