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making up the boundary, e.g. fence/ forestry/ building/ water). By identifying a
value that this shade should fall under it is possible to derive a corresponding
relationship in the histogram and adjust the results of the study accordingly.
The final result of the authors work in Costa Rica was only “moderately
successful” (Cordero-Sancho & Ader, P.1589). This would seem to have been
largely due to the altitude with which the imagery they used was captured, by their
own admission the results would probably be better had the imagery been low
flown or of better resolution. The methods the authors employed in the study are
useful examples of how inconsistencies in results obtained during the process of
completing this thesis might be countered –in particular potential methods for
reducing the effect shade might have on altering the results could be applied.
In this thesis, as with most automatic aerial imagery analysis, the classification of
target areas in the photo (usually according to spectral values) is a vital part of the
process. One solution is to develop a key to differentiate between features. The
level of detail that can be obtained can be quite precise, but is dependant on the
resolution of the imagery and the complexity in the patterns of distribution of the
target. This is illustrated by Megan Lewis 1998 study of vegetation communities
in an area of westerns New South Wales. In this study she attempted to develop a
key to differentiate between vegetation types. The problem she was attempting to
counter was that of identifying particular species. She noted that existing aerial
analysis could detect the presence of vegetation and in an attempt to improve this
process she divided these species into colour bands. She took sample plots of
250sqm corresponding to 8*8 blocks of pixels in a relatively homogenous area
and calibrated the relationship between field verified data and fifty of these blocks
(using them as training areas for the study). The study used 12 colour bands which
were allocated into nine classes and identified a link between these and vegetation
classes. In the conclusion to the study the author noted that it was possible to
portray sub-polygon variation using pixel-based imagery.
In order to complete this study it was necessary to make the best use of the
available imagery. This imagery can benefit from preprocessing in order to
highlight the areas being captured. One method for achieving this might be to
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