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these two fields will by necessity start to merge. This study looks at one small
aspect of mapping and how automated software could be used to increase the
amount of information available to a user. The premise of the study is that, given
enough previously captured and accurate data, it is possible to automatically read
the landscape. In short I hope to take point and line data, slice sections from aerial
photography, and run a spectral analysis. The focus of the study is in the
methodology so that a means for completing automated updating is identified. I
should point out that by updating I am referring to providing information relating
to the percentages of ground cover within a small area polygon. The task of
physically capturing new structures, roads, height values (even when considering
lidar) is probably something that will always require a human eye to interpret the
data to some degree, for example, if the structure is temporary or if road works are
underway.
It might be useful at this point to introduce some more background to this study.
The island of Ireland was fully digitally mapped in 2005 and recently a new
database for this data has been introduced which allows small area polygons to
retain unique identifiers linked to the surrounding geometry and features. The
mapping is on an update cycle but for the most part it can be assumed that these
polygons will remain constant (with the percentage change even lower following
the building boom of the last decade). This opens up the opportunity for someone
to visit the sections of surface area represented by the area polygons over
successive runs of aerial photography and extract land use change data.
I mentioned earlier that the focus of the study is on establishing a methodology;
this was because the motivation for assessing land use change would vary
according to the user. An example of this might be someone considering the
potential for flooding within an area. This person might want to take a look at the
water courses and new housing developments to determine the amount of
impermeable surface area (paving, patios etc.) over the course of their study. To
physically do this, either using a photogrammetry tool such as SOCKET SET or
field GPS, would be an onerous task. The aim of this thesis is to provide a method
for automatically doing this. It might seem an obvious point, but the more
information available to a process when commencing an examination of an area,
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