GIS, Environmental Modeling and Engineering

Second Edition
Allan Brimicombe

CRC Press
© 2010 by Taylor and Francis Group, LLC
CRC Press is an imprint of Taylor & Francis Group, an Informa business

International Standard Book Number: 978-1-4398-0870-2 (Hardback)

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Integrating models and geographical information systems

Roger Bivand and Anne Lucas

Since geographic information systems (GIS) currently dominate our perception
of how computing and geography should interface, and since GeoComputation
(GC) is providing analysts of spatial phenomena with ever more powerful
computing tools, it may be helpful to examine the experience that has accrued
concerning links between them. Our examination is both empirical and
normative, and the reader may find it useful to repeat at least some of our
literature surveys, since new papers and articles are accumulating rapidly.
Searching on the key words ‘GIS’ and ‘model*’ or ‘integral*’, where ‘*’ is the
wild card, led to a wide range of hits both in ISI Science and Social Science
Citations Indices, and in OCLC-FirstSearch. These sources primarily contain
journal articles, while conference proceedings may be searched at the Ohio State
University GIS Master Bibliography Project, and more recently through the
web-sites of conference organizers, such as NCGIA and GISDATA in Europe.
Adding these resources to what we already knew about the issues involved, we
were able to scan the field for interesting regularities, trends, and citation
clustering. read more

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Geospatial expert systems

Tony Moore

The division of computational science that has come to be known as expert
systems (ES) has its origins in the broader discipline of artificial intelligence
(AI), where it still resides. Put very simply, the broad aim of artificial
intelligence is to simulate human reasoning (Laurini and Thompson, 1992).
Expert systems are the most mature products to emerge from this field (Raggad,
1996), dating back to the mid-1960s. Since that time, when researchers at
Stanford University developed a program that used chemical expert knowledge
to automatically deduce molecular structure (Durkin, 1996), a plethora of
definitions for the emergent technology have been put forward. The following
gives an indication of how the use of expert systems has expanded to encompass
nearly every scientific discipline in that time (Cress and Diesler, 1990).
‘Expert systems are computer systems that advise on or help solve
realworld problems requiring an expert’s interpretation and solve realworld
problems using a computer model of expert human reasoning
reaching the same conclusion the human expert would reach if faced
with a comparable problem.’
(Weiss and Kulikowski, 1984)
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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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Parallel processing in geography

Ian Turton

This chapter is about parallel processing, or parallel computing; the terms are
used synonymously. It will focus on ways to produce real applications not
computer science abstractions. It will start out by describing what parallel
computing is and why as a geographer you should even care. It will then give a
brief historical overview of supercomputing and the rise of parallel computers. It
will then attempt to set out what parallel computing is good for and what it is not
good for and then finish up by showing you how you might get started with
parallel computing.

What is parallel computing?
Parallel processing at its simplest is making use of more than one central
processing unit at the same time to allow you to complete a long computational
task more quickly. This should not be confused with so called multitasking
where a single processor gives the appearance of working on more than one task
by splitting its time between programs; if both the programs are computationally
intensive then it will take more than twice the time for them to complete, nor are
we concerned here with specialized processors (e.g. graphics controllers or disk
managers) that work in parallel with a processor. read more

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