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•Where available, regression is chosen as the
preferred type of estimation. This approach essentially corrects the area
sample (ground only) estimate based on the relationship found between
reported data and classified pixels in each stratum where it is used.
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•A regression relationship should be based on 10
or more segments for any stratum used, however, as few as five segments have
been used in the past. Where there are
not enough segments in each stratum, a pixel based ratio estimator may be
used which essentially combines data across stratum to get the relationship.
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•Finally, the direct expansion (total number of
possible segments times the average for sampled segment) may be used in the
absence of pixel based methods.
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•Regression adjusts the direct expansion
estimate based on pixel information. It usually leads to an estimate with a
much lower variance than direct expansion alone.
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•Segments, called outliers, which do not fit the
linear relationship estimated by the regression are reviewed; if errors are
found, they are corrected or that segment may be removed from consideration
in the regression analysis.
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•This graph shows the approximately linear
relationship between acres reported during the ground survey and pixels
categorized to rice by the classification process.
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•Several possible outliers are visible.
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•The R-squared term measures how close the
relationship is to a straight line; the closer it gets to 1.00, the better it
is.
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