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currently available for all areas and has not been included in the study. It should<br />

be noted that its addition has the potential to improve the accuracy of this type of<br />

study.<br />

A couple of sample sections of the image were selected with varying degrees of<br />

shade present in the image. This was to determine if it is possible to introduce a<br />

step into the algorithm which would correct for areas of shade in otherwise<br />

uniform closed polygons. The first sample involved selecting an area of pasture<br />

which contained a large amount of shaded ground from some high trees along one<br />

of the border vector boundaries i.e., along the hedge. The area of shade<br />

corresponded to roughly half the area of the test polygon. It should be noted that a<br />

degree of shade will be present in all of the orthophotos to which this study<br />

applies; this is because aerial survey takes place in bright sunshine by necessity.<br />

The sample was analyzed for mean pixel values along the colour bands, and also<br />

the standard deviation displayed.<br />

Shade test sample 1<br />

(pasture with app. 50% shade)<br />

Mean pixel value Standard deviation<br />

Red 88.457 37.387<br />

Green 135.151 40.01<br />

Blue 100.616 20.386<br />

Table 16: Shade test sample value 1<br />

The results for this were as might be expected; with an increase in the standard<br />

deviation for the first red and green colour bands reflecting the variety of tone<br />

present in the sample. This, however, does not give a complete representation of<br />

the data and a histogram (see below), reveals peaks for the shade value, and a peak<br />

for the pasture value in both the red and green colour bands. These two peaks<br />

indicate that the area is pasture, and that the high pixel count for the lower values<br />

in the red and green colour bands is a result of shade.<br />

74

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