GeoComputation - GeoComputation - page 4

faster, more spatially appropriate methods have started to emerge, but much of the damage still
needs to be undone. The geo is extremely important and distinctive, and sadly, it has historically
been de-emphasised far too much because of the additional complexity that a more explicit recogni-
tion would have caused. Today this is no longer an acceptable excuse.
Secondly, the computation subphrase in GC is also special. It is the intensity of the computation
that is especially distinctive. As computers become faster the very concept of a solution changes.
GC is about finding new or better solutions to existing problems via a computational route. It also
involves thinking about tackling new classes of problems that previously were unthinkable or insol-
uble. The hope is that it is now becoming possible to compute solutions to previously insoluble
problems, to compute improved solutions to other problems and to begin to identify new ways of
working and new subjects for study that are computational in their methodology.
Thirdly, just as important and maybe even more significant is the underlying mindset. Computers
can be used for many different purposes and to argue that number crunching is a distinctive feature
ignores the fact that a spreadsheet is also a number crunching device, whilst processing 100 mil-
lion billion characters would not seemingly involve many megaflops! Computation implies a very
particular paradigm based on numerical approximation rather than analytical precision. It can be
based on data-driven high-performance computer-powered inductive tools rather than data-free,
analytically based, deductive methods. It involves trying to compute solutions to problems that
could not previously be solved at all. It is based on substituting vast amounts of computation as a
substitute for missing knowledge or theory and even to augment intelligence. It could be data driven
in a data mining sense, or it could be entirely data-free with large-scale computer experimentation
being used as a purely theoretical tool for understanding how complex systems work via modelling
and simulation of their dynamics and behaviours.
1.4 HOW DOES GEOCOMPUTATION RELATE TO
QUANTITATIVE GEOGRAPHY?
It is quite simple. GC includes all the tools of quantitative geography, but it also encompasses
far more than quantitative geography ever did as it has a very different emphasis. It also has the
potential to negate most of the weaknesses and to reexpress quantitative geography in a form
more suitable for the twenty-first century; see Openshaw (1998a). Also, GC offers a new perspec-
tive and a paradigm for applying science in a geographical context. It is true that superficially it
does not seem to be much different from quantitative geography. It is merely (some critics will
argue) the application of operationally intensive approaches to the problems of doing physical and
human geography in particular and the geosciences in general. Indeed it is, but it is important to
appreciate what this means and to try and understand some of the potential power of adopting a
computational paradigm that views statistical methods as only one small part of a far more flexible
and expansive toolbox.
GC is concerned with new computational techniques, algorithms and paradigms that are depen-
dent upon and can take advantage of HPC. In fact, it involves four leading edge technologies:
1. GIS, which creates the data
2. Artificial intelligence (AI) and computational intelligence (CI), which provide smart tools
3. HPC, which provides the power
4. Science, which provides the philosophy
So GC is much more than just using computers in geography and neither is it an attempt to rejuve-
nate a moribund quantitative geography in the style of 30 years ago! It is simultaneously a tool, a
paradigm and a way of thinking. It is not just about using computers to do arithmetic; it is the scale
or amount of arithmetic computation that makes it distinctive! As high-performance computers
become faster and larger, the attractions of developing computational approaches increase its appeal