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surface area that might have been introduced to the landscape. The road network
is present in the vector dataset so subtracting this (along with the other known
polygons such as water, buildings etc.) from the means that polygons with a high
number of pixels corresponding to these values would indicate that the surface
contains an area of cover similar to track or road (hard impermeable cover).
This unique value has potential to increase the accuracy of flood mapping and
prediction but requires additional processing to ensure that the high values are the
result of permeable surface area. This could take place within an automated
software process by swapping the colour bands to increase the difference between
these areas and areas of vegetation.
The purpose for sampling the areas of track was to see if there could be any means
of determining if an area surrounding a private dwelling had been paved, or if
there were any paved yards/ areas of hard cover present in other semi urban
polygons. The test sampling took three areas to compare the values for track
against; an unpaved dirt track, an area of compacted gravel yard and an area of
paved yard. With the exception of the blue colour band the results were similar to
those from cut pasture. These can be discerned from cut pasture by setting the
search algorithm to look at the mean pixel value for the blue colour band, which
was 30% less for both the paved yard and dirt track. The values returned for the
yard of compacted dirt and gravel were similar to cut pasture but were within a
small polygon containing several roofed buildings. The algorithm can therefore be
set to accept values similar to cut pasture for small area polygons containing a
number of roofed buildings as gravel/ dirt hard cover. In the particular case of this
sample the results obtained are most likely due to pigment in the gravel biasing
the sample.
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