continents. North America was split 
by quadrants [northeast , northwest, 
southeast and southwest], Euro-Asia 
by sub-continents [Europe, USSR, 
China, India and SE Asia], and 
Africa into Northeast, Middle East 
and Gulf countries. 
Figures 4 through 6 were prepared to 
show the variation in the data and 
the growth curves. In general, the 
northern hemisphere did not have a 
good year being below 100% of 1988. 
The greatest drop was USSR. The 
other sub-continents listed where in 
their low yield or non rainy season 
(India, SE Asia, and Africa). 
Southeast North America in fact 
dropped in weekly growth from the 
third week. This probably indicates 
a higher percent of forage over 
cereal crop and also reflecting 
frost and drought in Florida in 
1989. 
CONCLUSION 
Cloud cover has always been a major 
deterrent in using satellite data. 
The process of producing a weekly 
composite of the data proved to be a 
successful solution to this problem. 
Crop and forage estimates using 
rainfall data were compared to field 
and ground survey information for 
Saskatchewan only. The results were 
within a reasonable range of 
estimation for the 3 year test 1985- 
87 and were used for the 1988 data. 
The Polaroid photographs produced 
from the enhanced NOAA Satellite 
data were evaluated by futures 
brokers as to their potential use as 
a management tool to provide crop, 
and forage conditions and 
production. 
Normally, farmers have a planting 
rotation derived from tradition. 
The year-to-year rotation is uniform 
for a region. But even if the 
farmers change their cropping 
practice due to market or climate 
conditions, the changes will show on 
the resulting image. The image will 
quickly point out where it maybe 
beneficial to produce images showing 
changes greater than 20 or 40%. 
Thus showing areas which warrant 
further investigation. With the use 
of GIS (Geographic Information 
Systems), last year's crop yield can 
be multiplied by the weekly percent 
yield map to produce an estimate of 
this year's estimated yield on a 
weekly basis. 
This study is part of a continuing 
effort to develop operational 
remote sensing analysis techniques 
for the estimation of crop and 
grazing conditions 
One essential part of global 
monitoring is our ability to watch 
our food supply. But more 
importantly, we must be able to 
react to changes in our food supply. 
The monitoring capability must be at 
a temporal and spatial scale 
adequate to detect these changes. 
The purpose of hemispherical crop 
monitoring is to record change in 
the crops as some measure of average 
yield. Our paper describes a new 
way of presenting the information so 
yields in kg ha can be provided if 
we monitor last year yield in a 
digital form. 
Acknowledgements 
Canada Centre for Remote Sensing, 
Manitoba Centre for Remote Sensing, 
Saskatchewan Crop Insurance, 
Saskatchewan Agricultural 
Development Fund New Pastures and 
Grazing Technology Projects helped 
this project. George Chu of PFRA is 
particularly thanked for supplying 
his calibration data. 
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