Geography Reference
In-Depth Information
visualisation has helped the epistemic break in cartography by fostering the under-
standing that maps construct and do not reproduce the world, and that there is not
necessarily a direct relationship between a map and the territory it represents. Yet
others, including Pickles (1995) and Veregin (1995), have pointed out that new
technologies such as GIS and the increasing use of remote sensing/satellite data
appear to strengthen the belief in an unbiased and scientific cartography. However,
the notion that technology is value-free is inherently misleading, and it has been
demonstrated many times that neither cartography nor the new technologies of
remote sensing and GIS are the impartial and unbiased tools that many seem to
think they are (Robbins, 2001). For example, satellite images have to be inter-
preted, and in this interpretation categorisation and colour-coding play an import-
ant role. For the area of GIS, Pickles (1995: 12) has pointed out that 'the
epistemology
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and method that underpins GIS emerged in the 1960s under the
auspices of positivist and empiricist versions of science and re-emerged as a result
of the collaboration between, and a revitalization of, spatial analysis, cybernetics,
and computer development of the 1970s'. Veregin (1995: 99) has emphasised
that already the encoding of geographic and thematic data in a GIS database is
rooted in a specific cultural context and scientific paradigm, and:
filtered and modified as a function of technological feasibility and necessity. For
example this data model necessarily assumes that the features contained in a
database represent unambiguous real-world entities, [i.e.] the three basic
cartographic feature types - point, line and area - are viewed as representative
of real-world entities even though they are abstractions of a world more
complex than this simple categorization would allow.
Yet a GIS does not cater for the representation of the uncertainty which is associ-
ated with most geographical phenomena, given that most types of data, including
soil, vegetation and land-cover classes, 'exhibit neither recognizable areal bound-
aries nor strong spatial homogeneity within a given areal unit. Rather, these types
of data are characterized by spatial heterogeneity and gradual transitions from one
zone to an adjacent one' (Veregin, 1995: 99). Arguably, thus, the technology avail-
able to a certain extent prescribes the questions that can be asked and the set of
policies that might be considered as viable alternatives.
In summary, since the 1970s, many perception and cognition studies have
been undertaken in cartographic science, and the effects of visual variables have
been investigated systematically. There is now growing recognition amongst car-
tographers world-wide that there will never be an all-embracing theory of map
reading, or of cartographic communication in general. This is due to the fact that
there are certain variables which are difficult to control or even to identify in the
