Geocomputation, Sustainability and Environmental Planning

Beniamino Murgante, Giuseppe Borruso and
Alessandra Lapucci (Eds.)

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GeoComputation using cellular automata

Michael Batty

Cellular automata as GeoComputation
Cellular automata (CA) are computable objects existing in time and space whose characteristics, usually called states, change discretely and uniformly as a function of the states of neighboring objects, i.e. those that are in their immediate vicinity. The objects are usually conceived as occupying spaces
which are called cells, with processes for changing the state of each cell through time and space usually articulated as simple rules which control the influence of the neighborhood on each cell. This formulation is quite general and many systems can be represented as CA but the essence of such modelling consists of ensuring that changes in space and time are always generated locally, by cells which are strictly adjacent to one another. From such representation comes the important notion that CA simulate processes where local action generates global order, where global or centralized order ‘emerges’ as a consequence of applying local or decentralized rules which in turn embody local processes. Systems which cannot be reduced to models of such local processes are therefore not likely to be candidates for CA, and although this might seem to exclude a vast array of geographical processes where change seems to be a function of actionata distance, this criterion is not so restrictive as might appear at first sight.
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Stan Openshaw

GeoComputation (GC) is new, exciting, and here, but what is it? Some writers
seem to think it has been around as long as there have been computers being
used in geography. Others that GC is more or less a ‘brand new’ invention.
There is seemingly an understandable confusion so the purpose of this chapter is
to examine some of the alternative definitions, identify the more appropriate
ones, and then outline some examples of what it may mean in practice.

GeoComputation is linked by name to what is broadly termed computational
science with which it is clearly related and shares many of its aims.
Computational science is a relatively new multidisciplinary paradigm for doing
science in the late 20th century. As yet there is no general consensus as to a
precise definition of what computational science actually is. In broad terms,
computational science involves using computers to study scientific problems
and it seeks to complement the use of theory and experimentation in scientific
investigation. It seeks to gain understanding principally through the use and
analysis of mathematical models and computer simulation of processes
performed using, and often totally dependent upon, the availability of high
performance computers. It is a largely or wholly computational approach to
scientific investigation in which computer power is used to supplement and
perhaps in some areas supplant more traditional scientific tools. Indeed once
computer hardware became fast enough and big enough and numerical
methodologies clever or flexible enough, then a computational paradigm
provided a substitute for physical experimentation. It allows the visualization of
hitherto unseen scientific processes, and it offers a basis for the simulation of
complex systems which are too difficult for economical study by any other
route. Computation permits the investigator to test theory by simulation, to
create new theory by experimentation, to obtain a view of the previously
invisible, to explore the previously unexplorable, and to model the previously
unmodellable. There is clearly considerable potential here that will be released
in the new millennium as computer speeds increase and a computational
paradigm becomes a more common paradigm for doing science in many more read more

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