Figure 10. Travel time accessibility for heavy trucks

Transcription

1 Figure 10. Travel time accessibility for heavy trucks 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.

2 Figure 11. Generalised accessibility of large basins of activities 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 3. CRITERIA FOR SPATIAL DIFFERENTIATION SPESP 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 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

4 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 area Transport network Built of new links to connect the two national networks and to improve their connexity Fields of integration Urban network Connection of the two territorial urban networks and increase of cities influences Flows - - Relative growth of transborder flows Territorial homogeneity Homogenization of characteristics Administrative and policy grid Adoption of a similar political and administrative spatial division

5 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 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

6 3. CRITERIA FOR SPATIAL DIFFERENTIATION SPESP spatial integration in cross-border regions 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 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. Table 3. Potential spatial integration indicators Main aspects Potential indicators explored Spatial interaction measured using flows and barriers Spatial homogeneity and discontinuities Spatial co-operation 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 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 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 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

7 Figure 14. Wealth differentials between neighbouring regions in 1981 The map illustrates discontinuities of GNP per capita between European regions at NUTS. 2 level ( = 2* x j x j / (x j x j ), where x j, x j = GNP per capita in contiguous regions i,j).

8 Figure 15. Wealth differentials between neighbouring regions in 1996 The map illustrates discontinuities of GNP per capita between European regions at NUTS 2 level ( = 2* x j x j / (x j x j ) where x j, x j = GNP per capita in contiguous regions i,j).

9 Figure 16. National financing of Interreg IIA / GDP 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.

10 Figure 17. Ratio of host municipalities 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 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.