modelling for forecasting the effects of climate change has great potential
for providing reliable, appropriate data and subsequent predictions in a
visually effective manner. ALS data provides appropriate data from which
DEMs can be generated. Once TINs that are representative of sea level are
transformed onto these DEMs, a variety of useful information regarding
inundation due to sea level rise can be extracted.
identifying the features that are subject to inundation in a particular
scenario, a time frame can be established when this may be likely to happen.
Additionally, the economic cost that may be incurred due to this inundation
can also be predicted. Consequently, this information can be used when
assessing the risk that an area of land may be subject to and, potentially,
can form a basis from which preventative planning can be made and
engineering solutions can be derived.
methodology described in this thesis to represent rises in sea level has
shortcomings which limit its reliability and its accuracy. This would need
modification for future investigations.
ArcGIS 9.2 has limitations for potential end-users. ArcGIS cannot process files that exceed 40 Mb in size, hence large-scale modelling cannot be performed using this software. However, for smaller scale modelling, such as the size of those generated in this thesis, it is possible to use it, albeit it is still time consuming to run. It has been recommended that another modelling program be sought for future investigations.