Figure 10.
Travel time accessibility for heavy trucks
Explanatory Note:
Heavy truck travel time from Rotterdam to each European cities respecting the prescribed
speed in France on the different networks - Road, motorway and ferry - and the European
regulations of driving times and obligatory rest. The corridors used are very obvious and
different from "Euclidian distance". The determination of travel time and minimal ways
require a real origin and destination as cities or network connexions. The use of regions or
zones does not allow this type of computation.
Figure 11. Generalised accessibility of large basins of activities
Explanatory Note:
This map shows accessibilities for many cities (unipolar accessibility). Actual minimal distances
determine corridors, which thus do not represent Euclidian distance. The travel space is not
homogeneous but depends on the physical geographical characteristics of the European territory. These
corridors show that it is possible, with a model, to anticipate some spatial consequences of heavy truck
traffic, such as traffic growth, saturation, air and noise pollution, and modification of the rural and
urban landscapes.
3. CRITERIA FOR SPATIAL DIFFERENTIATION
Europe. Those group members following the
second direction adopted a nodal approach,
stressing intra-regional information (e.g.
towns, nodal points of transport, physical constraints, corridors, border effects) which was
complemented by simulations related to possible changes in networks (like the closure of
Alpine tunnels or the construction of new
links).
Surveyed after-the-fact, the two approaches
appear rather complementary. The first approach is appropriate for showing large-scale
differences in global accessibility and may illustrate specific aspects of inter-regional imbalances in relation to European cohesion policy. The second approach provides operational
support for influential decisions in the field of
transport policy related to impacts of network
improvements, changes in service frequency,
regulations with respect to truck transport, etc.
Presentation of geographical position indicators
An interpretation of five of the eight reference
indicators elaborated for geographical position
is presented in Figure 6. Orthodromic distances
were calculated between centroids of the
NUTS 3 regions, i.e. idealised locations representing the spatial distribution of population
and economic activities in the regions. In the
example shown, the centroids are the central
points of the most important cities in the respective regions. Using orthodromic distance
to the centre of gravity of population, weighted
by population, is the simplest way to show peripherality. Using this method locates the
population centre of gravity of the EU near the
city of Reims in eastern France.
Figure 6. Orthodromic distance to the centre of gravity
of population in Europe
The following figures show accessibility indicators by road (Figure 7), rail (Figure 8) and
air (Figure 9), and travel-time accessibility
(Figures 10 and 11).
Figure 7. Accessibility by road to population in 1996
Figure 8. Accessibility by rail to population in 1996
Figure 9. Accessibility by air to GDP in 1996
Figure 10. Travel time accessibility for heavy trucks
Figure 11. Generalised accessibility of large basins of
activities
SPESP
3.2.2 Spatial integration
As already discussed in the preceding chapter,
the concept of spatial integration is complex
and has been defined in a variety of ways.
Here, spatial integration is treated as a system
of links between territories and the result of
concrete social, economic and cultural relationships.
An attempt was made to identify measures of
these linkages, which were then used as guidelines for evaluating spatial integration. Five
basic procedural principles were identified:
!" In a relational approach, relations between
territories can be described through a set of
specific attributes. The choice of territorial
units is crucial, since the structure of the
links between locations can vary greatly
according to scale.
!" Following a multi-dimensional approach,
different types of links between locations
can be analysed in order to describe various dimensions of spatial integration.
!" A dynamic approach is based on analysis
of links/flows over time.
!" In a multi-scalar approach, spatial integration at one scale of territorial organisation has consequences at higher and
lower levels of territorial organisation. Developing a multi-scalar approach facilitates
understanding of the conflicts or contradictions between the evolution observed
at each geographical scale (European, national, regional, local).
!" A systemic approach combines analysis of
spatial structures (integration opportunities), spatial relations (the level of interaction) and spatial processes (the consequences of realised or unrealised
interactions). Spatial integration has clear
links to the concepts of spatial systems and
functional regions.
Spatial systems can be conceptualised as territories where a form of integration is present;
they may belong to different types of domains
(e.g. economic, social, cultural, ecological) and
may take various forms according to the issue
in question (e.g. river basins, urban networks,
Euro-corridors). Figure 12 illustrates some selected fields for a systemic approach to spatial
integration.
Figure 12. Selected fields for a systematic approach of
74
Figure 12.
Selected fields for a systematic approach of spatial integration in cross-border regions
1. Non-integration
2. Integration
1-2. Integration dynamics
Density
+
Relative growth of density
in the border a rea
Transport
netw ork
Fields of integration
Built of n ew lin ks to connect
the two na tional networks
and to im prove th eir connexity
Urban
netw ork
Connection of the two territorial
urban networks and increase
of cities influences
+
Flow s
-
-
+
Relative growth of transborder flows
+
+
+
Territorial
hom oge neity
+
+
+
+
+
+
+
+
+
+ +
+
+
+ +
+ +
+
+ +
+
+
+ +
+
+
+
+
+ + + +
+ +
+
+ +
+ + + +
+
+
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+
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Homogenization of chara cteristics
Administrative
and policy grid
Adop tion of a sim ilar political
and adm inistrative sp atial division
Figure 13. Geographical modelling of flows
Hypothesis 1. Exchanges between two locations are in
proportion with the magnitude of their
1000
imports/immigration imimports/immigrations
imports/immigration and exports/emigrations
100
10
0
Magnitude of imports/immigrations
and exports/emigrations
(sum of flows)
Flows
Hypothesis 2. The greater the distance between two territories, the
smaller their exchanges
km
Distance
km
Hypothesis 3. The need to overcome a territorial limit
reduces the exchanges
Frontier
3. CRITERIA FOR SPATIAL DIFFERENTIATION
spatial integration in cross-border regions
SPESP
comprehensive methodology, most of the potential indicators have not been mapped out for
the whole European territory. Those indicators
presented concentrate on the results obtained at
the European level.
Three sets of indicators are explored, illustrating the methodology presented above (Table
3). These potential indicators identified are not
considered capable of giving a complete or
satisfactory picture of the subject. Due to lack
of data, limited time and the need for a more
Table 3. Potential spatial integration indicators
Main aspects
Potential indicators explored
Spatial interaction measured using flows and
barriers
Goods transport flows
Inter-regional migration
Barriers to trade and migration
Wealth differences between neighbouring regions
Multi-scalar profile and dynamics of regions
National funding of INTERREG IIA programmes
Town and city twinning activities
Spatial homogeneity and discontinuities
Spatial co-operation
Flows and barriers
As a general point of departure, we expect the
exchanges between two places to be determined by their size, the distance between them
and the presence of barriers, as illustrated in
Figure 13.
Figure 13. Geographical modelling of flows
Examples of indicators for transport flows and
interegional migration have been investigated
for the Netherlands, Portugal and the UK. The
studies illustrate some peripheral regions to be
less integrated than might be expected from
their economic strength and population size,
while others appear to be more integrated than
expected. More fundamentally, the exercise
reveals the number and variety of factors that
have to be taken into account in order to interpret flows in terms of spatial integration.
At a national level, trade flows show that
Europe is becoming more economically integrated over time. The barrier effects posed by
national borders still exist, however. A gravity
model tested for freight transports between
regions in France and Belgium - a rare example of comparable data - shows that in 1990
flows between two regions within the same
country are, on average, about seven times as
great as flows between regions in different
countries, despite the fact that the countries in
question have been involved in the same integration process since 1957.
Spatial homogeneity and discontinuities
The relationship between the concept of spatial
integration and homogeneity or discontinuity is
a complex one. Homogeneity does not necessarily imply integration - and in some cases it
is heterogeneity that generates interaction and
flows. Conversely, spatial integration may
generate more homogeneity in some cases, but
also more heterogeneity in other cases. However, one can consider that a trend towards
homogeneity in the longer term may generate
increasing flows and hence reflect a process of
spatial integration.
Figures 14 and 15 illustrate the development of
wealth differentials between neighbouring regions in 1981 and 1996. The colours show
GNP per capita at NUTS 2 level, while the
lines indicates where there are discontinuities
of GNP per capita between contiguous areas.
Figure 14. Wealth differentials between neighbouring
regions in 1989
Figure 15. Wealth differentials between neighbouring
regions in 1996
The principal inter-regional discontinuities
would appear to derive from four general factors,
!" discontinuities between metropolitan areas
and neighbouring regions,
!" borders between states,
!" central-peripheral discontinuities, both at
EU level and inside Member States, and
!" specific local situations where regions
have specific advantages or disadvantages.
75
Figure 14. Wealth differentials between neighbouring regions in 1981
Explanatory Note:
The map illustrates discontinuities of GNP per capita between European regions at NUTS. 2 level ( =
2*| xj – xj | / (xj + xj), where xj, xj = GNP per capita in contiguous regions i,j).
Figure 15. Wealth differentials between neighbouring regions in 1996
Explanatory Note:
The map illustrates discontinuities of GNP per capita between European regions at NUTS 2 level ( =
2*| xj – xj | / (xj + xj) where xj, xj = GNP per capita in contiguous regions i,j).
Figure 16. National financing of Interreg IIA / GDP
Explanatory Note:
The index relates the amount of national financing (computed on basis of entire programme areas) to
the population of the border NUTS 3 region of the NUTS 2 area concerned, and to the national GDP,
thus indicating the level of relative investment in co-operative actions.
Figure 17. Ratio of host municipalities
Explanatory Note:
The variable represented is the ratio between the number of host municipalities that have received
European financial aid in order to organise twinning activities over the period 1990-1998 and the total
number of municipalities. Municipalities are considered to be NUTS 5 areas, except in one case
(Portugal – NUTS 4 areas).
NB: Austria, Finland and Sweden joined the European Union in 1995.