Geoscience Reference
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and Belgium. In Spain and Italy the growth areas are in the north,
again reaching towards the centre, just as in Norway and Sweden
they are in the south. On the other hand, the relatively under-
developed areas of Europe are stretched all along the periphery:
Greece, southern Italy, Corsica, Sardinia, most of Spain and
Portugal, south-west France, Brittany, Ireland, Scotland, Jutland
and eastern Bavaria. One may suspect a link between this striking
pattern of economic development and accessibility, which is a
result partly of geography and partly of transport (Thomson 1976,
p.274).
Whether or not this implies that the core-periphery structure is caused
directly or indirectly by the transport system, it is important to bear in
mind that a higher density of transport infrastructure will partly be a con-
sequence of higher levels of economic activity, as well as being a causal
factor which tends to facilitate that level of activity. However, in tests of
association between HDI and GDP per capita (PPP) data and transport data
compiled for this investigation, significant correlations were only found
with cars per capita ( Table 14 below), which indicates wealth rather than
the personal mobility of the population. Although data for the usage of
other forms of transport are not included in these tests, it would still be
possible to see if any association between transport and development is
present in the relationship between transport statistics and the Accessibility
and Transport class (and its subclasses) of symbols.
Table 14: Results of Pearson's product moment correlation coefficient tests between HDI
and GDP per capita (PPP) data and transport data (source data compiled from Maher
2006)
Significant positive correlations are indeed present between the proportion
of symbols dedicated to Accessibility and Transport and the number of
cars in use, which provides a more accurate measure of the personal mobil-
ity of the whole population than cars per capita ( Table 8 ). Stronger positive
correlations, however, were found between cars in use and the number of
symbols in the Canals class (e.g., Table 9 ) and a strong negative correla-
tion between cars in use and the proportion of symbols allocated to the
 
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