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3 Sampling for the Baseline Image Key<br />
Figure 1: Aerial view of sample area<br />
The main body of research in this study involved identifying areas which would<br />
make useful benchmarks for an automated image analysis to use as a search key;<br />
ten areas were selected for inclusion as they formed the most distinct sets which<br />
could be used. These ten area types sampled were: Roads (of all class), Water<br />
(Lake, River, Stream, Drain and Pond), Marsh, Coniferous forestry, Mixed<br />
Forestry, Track, Shade (to obtain reference values when a high level of standard<br />
deviation occurred), Building (roofs), Pasture and Rough pasture. Of these<br />
sample values four could not be determined from the vector data (Pasture, Marsh,<br />
Rough pasture and Bog) and were used to test the ability of the process to identify<br />
target values by their relationship to known values. The next section describes the<br />
findings for these sampling areas.<br />
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