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TAES Filter
Yield maps often contain data points that are not correct estimates of the
yield in a given area. Often these erroneous points result from the manner in
which the harvester is operated. Incorrect yield estimates are a factor of
the number of combines used in a field, the shape of the field, and the type
of crops being harvested. Incorrect yield maps can lead to inappropriate
site-specific management decisions. Therefore, the accuracy of the yield data
collected with combine-mounted mapping systems needs to be improved.
Post-processing the yield map data with a filter can remove some of the
problem data and result in maps that are more accurate.
A filtering technique for exported yield files was developed and tested on
ten fields of corn, sorghum and rice. The incorrect yield points were
identified with filter functions based on acceptable yield values, acceptable
moisture values, appropriate travel distance, sudden surges in yield and
overlap of previously harvested ground. Results showed that this filtering
algorithm resulted in a higher field average and lower standard deviation
than either the unfiltered data or data filtered with maximum and minimum
thresholds alone. The filter was successful in eliminating many incorrect
yield estimates.
To read more about this program, download the paper presented at the 1999 ASAE/CSAE-SCGR Annual
International Meeting.
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TAES Filter
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Download the TAES Filter by using this link.
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Avenue Scripts to Delineate MUs
This study demonstrates and evaluates the creation of management units (MUs)
for the purpose of precision farming. The two factors, topography and water
infiltration rates, used to delineate MUs were hydrology based. The hydrology
model within the spatial analyst extension of ArcView, a GIS, was used to
create the subwatershed theme from the topography data and the soil maps from
United States Department of Agriculture (USDA) Soil Conservation Service
(SCS) were used to create the infiltration rate theme. A hydrologic
management unit algorithm (HMUA) was designed to use these two themes as
input and create MUs based on a minimum size input from the user. The results
were tested separately against MUs based on average slope and infiltration
rate. The conclusion was that the MUs generated with the HMUA were more
variable across MU boundaries and more homogeneous than that of the two other
methods tested.
HMUA User's Guide
The User's Guide walks the user through
the steps necessary to delineate MUs based on a size specification.
Avenue Scripts
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CalcArea Script
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This script will add separate columns to the first table
in the view, assuming the first theme is a polygon theme, with area (in
acres), perimeter, x centroid, and y centroid information.
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MergeArea Script
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This script is programmed to let the user input the
smallest size management unit that he/she wishes to work with and the
script will continue to merge all the small polygons with larger ones until
there are no more polygons smaller than what the user specified.
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To read more about this program, download the paper presented at the 1999 ASAE/CSAE-SCGR Annual
International Meeting.
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