the self-conscious formation of national iden-
tities through maps, and in particular through
‘logo maps’ that sketch in outline a simple and
homogenousspaceimbued with nationalistic
sentiments: more generally, Helgerson (1992)
convincingly argued that a modern nation re-
quires a spatial self-conception and that such
self-conceptions are constructed cartographic-
ally. From these studies, it seems appropriate to
limit the use of ‘geo-body’ to the spatial em-
bodiment of the nation and its self-imaginings,
leaving each state to construct and define its
territorial and political limits through markedly
different cartographic practices, technologies
anddiscourses. mhe
Suggested reading
Winichakul (1994).
geocoding Geocoding is the act of convert-
ing papermapsinto computer-readable form
by scanning or digitizing (Clarke, 2002,
p. 313) or, alternatively, the act of assigning a
location to information (Longley, Goodchild,
Maguire and Rhind, 2005, p. 110). Despite
revealing that there is no standardized nomen-
clature forgeographic information systems
(gis), these two meanings cover common
ground. To convert or to encode geographical
information digitally in a GIS requires that
both the characteristics and the locations of
the features of interest be stored in a database,
usually invectororrasterformat. Recording
what is found and where gives GIS its map-
ping and spatial analytical capabilities. rh
Suggested reading
Longley, Goodchild, Maguire and Rhind (2005).
geocomputation The technique of geo-
computation applies the processing power of
computers to enable advanced geographical
analysis and modelling. However, this broad
definition conceals a diversity of methods
and philosophies, leading Couclelis (1998,
p. 18) to ask ‘whether geocomputation is to
be understood as a new perspective or para-
digm in geography ... or as a grab-bag of
useful computer-based tools’.
Tosome,thespiritofgeocomputationiscon-
veyed by Openshaw, Charlton, Wymer and
Craft’s (1987) geographical analysis ma-
chine(gam), designed to look for spatial clus-
ters within child leukaemia data for northern
England. As a method of spatial analysis and
local pattern detection, it is characterized by
iterative repeat testing, subdividing the study
region into overlapping regions, within each of
which a significance test of the rate of incidence
(of leukaemia) is undertaken. Such a technique
is often portrayed as inductive (cf.induction):
drawing out ideas, inferences and working
hypotheses from what is found in the data,
and suggesting that the process of geographical
knowledge construction is data-driven or
‘avowedly empiricist’ (Longley, Brooks,
McDonnell and Macmillan, 1998). However,
that portrayal is not entirely satisfactory given
anya prioripostulate or theorization that radi-
ation causes leukaemia and therefore an exp-
ectation that a cluster of cases be found in
proximity to a nuclear power station. Finding
the cluster does not prove the theory, but it may
add circumstantial evidence. In this manner,
geocomputational practices are abductive (cf.
abduction): interesting cases (or spatial ‘hot
spots’) are used to support a plausible although
not logically necessary conclusion, not a purely
(inductive) empirical generalization.
Others pursue a more deductive tradition of
scientific practice (cf.deduction), with the
foundations of geocomputation established
firmly in the analytical traditions ofspatial
science and geography’s quantitative
revolution(see, for example, the history of
geocomputation outlined at http://www.geocompu-
tation.org). Here, the focus is on modelling,
analysing and theorizing dynamic socio-
economic or physical systems (cf. model);
on modelling spatial distributions, flows,
networks, hierarchies and diffusions.In
particular, there is an interest in methods of
simulation – from a human geography
perspective, of simulating the spatial pattern-
ing, causes and consequences of population
change, urbanmorphology, economic cycles,
transport congestion and so forth. These
methods build on the idea of Monte Carlo
simulation outlined by Haggett (1965). It
means that the rules of the system (assumed
from, say, economic theory) are played out in
virtual spaces, where what came before affects
what follows, but the geographical outcomes
are not entirely fixed or predetermined.
Instead, there is randomness in the system –
the ability to generate particular chance
events – albeit that the consequences of those
events are often constrained by the context in
which they are generated; for example, their
locations and the ‘state’ of the system around
them. Such methods include the use ofcel-
lular automataandagent-based modelling
(Flake, 2001) to model complexsystemssuch
as cities (Batty, 2005).
If this vision of geocomputation isnomo-
theticand law-seeking, does it then risk theGregory / The Dictionary of Human Geography 9781405132879_4_G Final Proof page 275 2.4.2009 6:30pmGEOCOMPUTATION