View/Open - ARAN

The software required for this step in the proposed algorithm includes an
application for viewing and analyzing raster data and capable of performing
transformations on sets of co-ordinates. For this study four sets of libraries were
used, packaged into open source applications known as Open EV, Mirone and
GDAL. The vector data was clipped using an application which forms part of a
geographical information system called Radius Vision. All the processes
necessary for the first part of this algorithm can be performed using GDAL, with
the exception of clipping to an irregular polygon, which is still under development
(GDAL, 2010). There is a license requirement for the Radius software, which was
used in this study for the step involving the user selecting the extent of the region
of interest in the vector mapping. It should be noted that this can also be
completed using any other vector mapping tools such as ArcView (which would
create a .shp file). Another alternative is for the user to manually create an ASCII
file of co-ordinates (with the convention of easting northing, separated by
newline). This alternative can be frustrating for the user and the suggested process
is to make use of software capable of designating the region of interest through a
viewer.
The data required for the aerial image analysis is ordnance survey ortho-rectified
colour aerial photography and matching digital mapping. The archive of aerial
imagery goes back to the 1970s and the algorithm being suggested is designed to
operate with any run of photography so users can discern dispersal patterns over
time through successive photography dates. The process, however, makes use of
the three colour bands present in colour photography and is limited to
photography with the red, green and blue colour bands. The vector data used will
take the form of 1:5000 or 1:2500 scale digital data and it is this data which forms
the basis of the search process. The vector data has the region of interest divided
into a mosaic of small area polygons the majority of which are coded according to
their use or content. The aim of this thesis is primarily to automatically register
additional data for those of unknown use type –and secondly to flag those of
known use type with specified (spectral) anomalies from user requests. In order to
be successful the data requires the coding, which may be useful to consider as a
data hierarchy at this stage in the process. The following hierarchy is only for
illustration. In practice each polygon will be analyzed according to its spectral
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