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shown give a more detailed picture of these areas and in this way eliminate some
of the problems encountered in previous studies.
There are two broad areas within the body of work on processing of remotely
captured spatial data which will be considered in the remainder of this review;
these can be considered spectral analysis methods, and the methods associated
with identifying polygons and the deviation of data from polygon patterns.
Before discussing these it might be useful to briefly run through the data capture
process as it stands in a traditional mapping environment (such as in OSI, the
former OSNI and OSGB). This process has been neatly explained by Bingcai
Zhang and Neal Olander in their paper to the 2000 ESRI user conference. They set
out the process as the captured imagery being manipulated by a user in a software
package (e.g. SOCKET SET) to produce a shape file of vector data from the
original hardcopy imagery. In this study the process of creating the data has
already been completed (along with the prior image control as described by Zhang
and Olander), so the thesis can be considered to be a method of re-visiting the
imagery to add value to the captured vectors/ features. It should be noted that the
process developed by this thesis is not dependant on expensive packages (such as
SOCKET SET) and could be applied to lower budget environmental monitoring
systems. Using low cost photogrammetric packages such as ShapeCapture there
would be a trade off in terms of consistency and accuracy (Aguilar et al, 2005).
Josef Kittlers 1983 Philosophical Times paper, as cited above, provides a useful
introduction to the subject matter of this thesis. It was written as an attempt to
summarize the various attempts that had been made towards automating the
analysis of aerial imagery at that time. The text is useful not just as a background
to the historical development of the field but also as an outline of the processes
involved (with respect to multispectral image segmentation). The author looked at
a wide number of previous studies (27 are cited) and summarized the work into a
series of categories. The technology available to process imagery has evolved
massively over the intervening quarter century but the basic techniques (in terms
of pixel analysis) and motivations (in terms of data required) remain similar today.
I have chosen this paper for the review as in some ways it sets the context for the
work being undertaken, that is the “interpretation of image segments that exhibit
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