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3.6 Track<br />
Figure 9: Typical Track Area Image<br />
This part of the study looks at values for track –corresponding to unpaved or<br />
gravel access roads and takes six sample areas for a comparison of spectral values.<br />
The purpose of the study was to see if there was a way of distinguishing between<br />
the spectral values for these type of roads and paved/ tarred roads (NRA category<br />
four upwards). Roads have unique spectral values in terms of an increase in mean<br />
pixel value of close to 30% for the three colour bands. This in itself is not<br />
particularly to an automated image analysis using OSI vector data as a baseline as<br />
the road network has been captured and is updated, however, if areas of paving or<br />
hard cover (similar to track) could be shown to have similar unique properties it<br />
might be possible to detect the presence of impermeable surface in recently<br />
developed suburban areas. I am conscious that the above explanation is long<br />
winded so the following example might explain things a bit better. A recently<br />
developed suburban area is experiencing problems with flooding and runoff –at<br />
present the mapping captures the water courses, buildings, roads and property<br />
boundaries (and street furniture/ utility details etc.) but does not indicate the extent<br />
of paving and patios within the individual plots; a survey filtering pasture using its<br />
spectral signature and known buildings, tarred road and footpath using vector data<br />
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