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5 Literature Review<br />
The goal of this thesis is one that is in line with most work completed using<br />
remote sensing processing in that it is looking for traits in aerial imagery which<br />
can be used to derive useful information about the surface of the earth. One of the<br />
early studies of aerial image interpretation (Kittlers ‘Image processing for remote<br />
sensing’ paper) described the process as “the interpretation of image segments that<br />
exhibit similar statistical properties” (J.Kittler, 1983). One addition that could be<br />
made to that definition is that, for the majority of studies in this field the<br />
interpretation should be automatic, or as close to automatic as to make<br />
interpretation of a large volume of data viable.<br />
There is a vast body of work available which documents various methods for<br />
interpreting aerial and satellite imagery. In general terms there is always a focus<br />
for each study, e.g. identifying coffee plantations in Costa Rica (Corado-Sanches<br />
and Sader, 2005) and this influences the methodology. One result of this is that<br />
there are a large variety of methods employed. This literature review considers a<br />
representative sample of these in terms of their focus, in other words treating work<br />
that uses patterns or shapes as one category, spectral deviation for agricultural/<br />
forestry purposes as another and urban analysis as a further category. In terms of<br />
previous studies, the ones that are closest to what this thesis is attempting is the<br />
body of work that has been completed on what has been termed ISAs<br />
(impermeable surface areas, or, more usefully, hard ground). The focus of these<br />
works is to identify the percentage of hard ground within urban areas which can<br />
then be used in modeling flood events. During the early part of the study I made<br />
use use of the SWAP technique recommended by T.Knudsen in his 2005 analysis<br />
of color in aerial imagery to identify grey areas in the test imagery (Figure 5:<br />
Water Area Image Modification). In the context of the data being analyzed by this<br />
thesis (Irish peri-urban land parcels) these grey areas within the image can be<br />
made to correspond to hard ground.<br />
Before considering the body of work underlying this thesis it is probably useful to<br />
answer two questions which the reader might ask; is this not just<br />
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