View/Open - ARAN

(The previous samples were compared to statistics from the image as a whole of
Red: Grey Level Values: 6 – 255, Median: 115, Mean: 111.711, StdDev:27.2804;
Green: Grey Level Values: 30 – 255, Median: 135, Mean: 136.542,
StdDev:27.3776; Blue: Grey Level Values: 5 – 255, Median: 102, Mean: 102.636,
StdDev:17.8523)
The mean pixel values are a useful benchmark to base further analysis of the
imagery on and the fact that each sample displayed a more or less uniform
deviation from the image standard implies that there is some merit to applying the
results to a key which identifies impermeable surface area. In general such areas
in an urban area will contain similar properties to a road surface. Further iterations
of this sampling will involve sampling shingle against concrete and tar (see the
analysis of the spectral values contained in areas of track) in order to see if there is
a measurable spectral variation between them; this will, however, involve a small
amount of post processing to enhance the differences between them.
The road network is a useful point of reference in automated image analysis and
ways of analyzing imagery to capture road networks have been well studied (such
as pattern analysis techniques explored by van der Werff & van der Meer, 2008).
In this thesis the focus is not on capturing road data, something which has been
completed and is on a continuous revision cycle, but on utilizing this data to make
the image analysis process easier. Most study areas (and almost every part of the
island of Ireland) will have at least some part of the road network present (at the
risk of sounding pedantic this assumption is not verified here because it can be
assumed as general knowledge and can be discerned from a cursory look at any
online small scale representation of the network). This means that there are
polygons of a specific unique spectral value available for referencing most studies,
even when confined to a particular area or series of photographs. In order to get a
clearer insight into how this can be applied three areas close to roads around the
image were sample and compared to sample values from their closest road
polygon.
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