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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