Geography Reference
In-Depth Information
scaling and aggregation with respect to the
precision with which characteristics can be
ascribed to points and places on the Earth's surface
(Openshaw 1984). Even if data were
geographically precise, this does not necessarily
mean that they accurately portray relevant aspects
of socio-economic reality in a model, since in
practice many facets of the urban system are
measured and represented using surrogate
information—an often-used example is the
absence of income data from most censuses, which
makes it necessary to represent spending power
using surrogate
indicators,
such as car ownership
rates (Bracken 1981:281-5).
Nevertheless, urban models can be used in a
static
sense, to depict the state of the system, or in a
dynamic
sense to illustrate how system
characteristics change over time. A static
application of an urban model might be to
represent the size and shape of an urban system.
Dynamic urban models use representations of
static states along with information about the
nature and rate of change in order to develop
simulations
(or scenarios) of what might happen in
a future stage of the system's development. These
scenarios can be used to answer the types of
question posed at the start of this chapter.
Dynamic urban modelling presumes some
understanding of the ways in which an urban
system
functions,
and such understanding is often
predicated upon what we know about the spatial
forms
of urban settlements. If a model abstracts all
that is important and discards what is unimportant,
then there is a good chance that we can use it to
summarise, recreate and forecast the salient
characteristics of an urban area.
Each of the questions posed at the start of this
section requires us to investigate some aspect of
the urban system by modelling selective aspects of
urban development. There is a vast range of ways
in which urban models and simulations may be
developed, and in a chapter of this length it is not
possible to classify, let alone summarise, all of
applied urban modelling. Instead, therefore, we
will focus upon the foundations to urban
modelling—that is, we will describe the computer
environment in which urban modelling and
simulation takes place, and describe how urban
models may be used to abstract the essential
characteristics of urban systems and develop
simulations in applied analysis.
THE CHANGING NATURE AND REMIT
OF URBAN MODELLING AND
SIMULATION
Most students are introduced to urban geography
through the classic models of urban structure that
were developed by Burgess, Hoyt and the other
'Chicago human ecologists' during the 1920s
and 1930s. There can be few of today's geography
students who are not familiar with the classic
concentric ring diagram of 1920s Chicago, and
one of its central characteristics, residential
zoning, has been borrowed in generations of
school projects to describe the mosaic of urban
land uses of hundreds of urban areas. Other
models often encountered by students at the
beginnings of their undergraduate careers
include those of Lösch and Weber in the realm
of industrial location, Christaller's central place
theory, the agricultural bid rent theory of von
Thünen, and the 'bid rent' micro-economic
theories of urban land use (developed in the
work of Alonso 1964; Muth 1969). Of these, the
micro-economic formulations of bid rents for
different land uses, and 'density gradients' of
different land-use categories, will be most
relevant to our discussion of urban structure here.
Such models are enduring because of the
powerful yet simple way that they abstract
(model)
essential characteristics of real-world urban
systems—the spirit of the very best applied
geography. (Just because a model is simple does
not mean that it cannot be misused, however. For
example, the Burgess model is too of ten
portrayed as a static representation of urban
form
rather than a dynamic representation of the
changing
function
of residential areas—in which
the inflow of successive waves of immigrants fuels
waves of outward movement of established
communities, in the same way that a pebble
dropped into a pool of water generates ripples.)
