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ands was detected the standard deviation would be matched for its range outside
an expected value of 10; allowing the polygon to be coded as pasture. This routine
is not coded here but was executed using a set of comparative tables.
At the beginning of this step the image consists of several sets of known polygon
types, the clipped image polygons, associated vector codes and an image key.
After completion of the step there are several more known polygon sets and a set
of unknown areas which fell outside the ranges expected. This may be the result of
the samples being biased by high levels of shade or the fact that they represent a
transitional data type (bog to rough pasture etc.). These remaining polygons are
further analyzed in the next step but this stage of the algorithm is used to classify
as many known values as possible. These were obtained through a series of
comparative steps as follows:
The sampling during this study pointed to a number of interdependent
relationships between the spectral values found in the polygons studied. The fact
that the polygons are clearly defined (through the vector mapping) and that the
content of many of these the polygons in the image is known prior to analysis
means that the algorithm can focus on identifying a narrow range of additional
area types. To achieve this it is necessary to loop through a series of criteria for
four main land types; pasture, rough pasture, bog and marsh. The last two on this
list will have identifying symbols present in most cases, which can be used to
assist the automatic search. Once the four target areas have been identified (with
pasture being the main land use in most semi-urban imagery) the remaining
polygons form a small set of areas which are further analyzed in the next step of
the process.
The polygon is analyzed using the geomatica analysis tool and the histogram
values exported for comparison to the known values. If the sample has a mean
value for the red colour band 40% lower than that of road polygons, and the blue
colour band displayed a similar 40% lower mean value than roads, and the
standard deviation is lower than a value of 15 then the sample is matched to water
–if the mean for the red colour band is close to three times that of water, and has a
green value close to twice that of water the polygon is coded as pasture.
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