Potentials for Polycentric Development in Europe

(1)

1

ESPON 111

Potentials for polycentric development

in Europe

(2)

This report represents the final results of a research project conducted within the framework of the ESPON 2000-2006 programme, partly financed through the INTERREG programme.

The partnership behind the ESPON programme consists of the EU

Commission and the Member States of the EU25, plus Norway and Switzerland. Each partner is represented in the ESPON Monitoring Committee.

This report does not necessarily reflect the opinion of the members of the Monitoring Committee.

Information on the ESPON programme and projects can be found on

www.espon.lu

The web side provides the possibility to download and examine the most recent document produced by finalised and ongoing ESPON projects.

ISBN number: 91-89332-37-7 This basic report exists only in an electronic version.

Printing, reproduction or quotation is authorized provided the source is acknowledged and a copy is forwarded to the ESPON Coordination Unit in

Luxembourg.

(3)

ESPON 1.1.1

Potentials for polycentric development in Europe

Project report

Separate volumes

Annex report A

Critical dictionary of polycentricity European urban networking

ISBN 91-89332-38-5

Annex report B

The application of polycentricity in European countries

ISBN 91-89332-39-3

Annex report C Governing polycentrism

ISBN 91-89332-40-7

Annex report D

Morphological analysis of urban areas based on 45-minutes isochrones

ISBN 91-89332-41-5

August 2004

revised version - March 2005

Contact information:

Nordregio Box 1658

SE-111 86 Stockholm SWEDEN

Tel: +44 (0)8 463 54 00 Fax: +46 (0)8 463 54 01

E-mail: nordregio@nordregio.se or erik.gloersen@nordregio.se

Web:http://www.nordregio.se

(4)

ESPON 1.1.1 Project Partners

Nordregio (Stockholm, Sweden) (Lead partner)

Danish Centre for Forest, Landscape and Planning (Copenhagen, Denmark)

OTB - Research Institute for Housing, Urban and Mobility Studies, Delft University of Technology (Delft, the Netherlands)

CNRS-UMR Géographie-cités (Paris, France)

Centre for Urban Development and Environmental Management CUDEM, Leeds Metropolitan University (Leeds, UK)

Austrian Institute for Regional Studies and Spatial Planning, ÖIR (Vienna, Austria)

Spiekermann & Wegener, S&W (Dortmund, Germany)

Dipartimento Interateneo Territorio, Politecnico e Università di Torino (Turin, Italy)

Quarternaire (Porto, Portugal)

Department of Urban and Regional Planning, National Technical University of Athens, NTUA (Athens, Greece)

Norwegian Institute for Urban and Regional Research, NIBR (Oslo, Norway),

Institute for Territorial Development and Landscape (IRL), Swiss Federal Institute of Technology (Zurich, Switzerland)

Hungarian Institute for Regional and Urban Development and Planning, VÁTI, (Budapest, Hungary)

Nataša Pichler-Milanović, Urban Planning Institute of the Republic of Slovenia, UPIRS, Ljubljana, Slovenia

(5)

Foreword

The present report presents the results from the ESPON project entitled “The role, specific situation and potentials of urban areas as nodes in a polycentric development”. The objective of the study has been to provide the background for a more informed discussion of polycentric development in Europe. This, on the one hand, has implied providing an overview of the European urban system with regards to functional specialisations and current degrees of polycentricity, as well as a prospective analysis of possible effects of regional polycentric integration in different parts of Europe. On the other hand, existing partnerships at the inter-municipal, inter-regional and transnational scales have been analysed, and the differents applications of polycentricity in national policies have been reviewed.

This report is divided into the following parts:

Part 1 consists of an executive summary and an overview of concepts, models and networking.

Part 2 is the full report.

Annex A presents relevant additional lists of data, maps and other information.

Three separate annex reports A, B and C include the full reports from work package 1, 2 and 5.

The team originally consisted of members from 10 research organisations, with an additional four members being included at a later date as more countries joined the ESPON programme. The work was organised into working packages:

The critical dictionary of polycentricity (Work Package 1) was developed by CNRS-UMR with Nadine Cattan as co-ordinator and the following contributors: Sophie Baudet- Michel, Sandrine Berroir, Anne Bretagnolle, Cécile Buxeda, Eugénie Dumas, Marianne Guérois, Lena Sanders, Thérèse Saint-Julien (UMR Géographie-cités) and Remy Allain, Guy Baudelle, Danielle Charles Le Bihan, Juliette Cristescu, Emmanuèle Cunningham- Sabot (UMR RESO).

Work on the application of polycentricity (Work package 2) was carried out by Wil Zonneveld (co-ordinator), Bas Waterhout and Evert Meijers, at OTB.

Analyses of the urban system (Work Packages 3 and 4) were developed by Janne Antikainen. Karin Bradley acted as the main co-ordinator in data gathering/mining, assisted by Jörg Neubauer, Ton van Gestel and several Nordregio assistants.

Analyses of the proximity of urban centres and of the potentials for regional polycentricity (WP 3-4) were developed by Erik Gløersen at Nordregio together with Carsten Schürmann (RRG), with assistance from Alexandre Dubois (Nordregio).

(6)

Klaus Spiekermann and Michael Wegener from S&W contributed to the accessibility analysis and developed a method to measure polycentricity (WP 3-4).

The work on European Urban Networking (WP 3-4) was conducted by Nadine Cattan (co- ordinator), Cécile Buxeda, Juliette Cristescu, Grégory Hamez and Guillaume Lesecq at CNRS-UMR Géographie-cités.

Governing polycentricity (Work package 5) was developed by Simin Davoudi (co- ordinator), Ian Strange and Michelle Wishardt at CUDEM.

The policy recommendations (Work package 6) were developed by Niels Boje Groth at DCFLP and Hallgeir Aalbu at Nordregio, who also conducted the final editing of the report with assistance from Jakob Grande, Lisbeth Harbo and Søren Smidt-Jensen at DCFLP and Erik Gløersen and Chris Smith at Nordregio.

Apart from the project partners, many others have also contributed with useful comments, material and data during the course of the research process. Kai Enkama provided data for population development trend analysis. We are also indebted to Julia Spiridonova, Jitka Cenková, Rivo Noorkôiv, Erzsébet Visy, Ieva Verzemniece, Jolants Austrups, Armands Vilcins, Rita Bagdzeviciene, Algimantas Venckus, Tomasz Komornicki, Serban Nadejde, Dorottya Pantea, Christian Steriade, Miloslava Paskova, Margarita Jancic, Janja Kreitmayer, Tatjana Kerčmar, Marco Kellenberger and others who have contributed with information, data and comments.

Janne Antikainen and subsequently Erik Gløersen at Nordregio were responsible for the co-ordination of the project. Financial management was provided by Anja Porseby and Anita Kullén.

Three interim reports have been produced prior to this final report. After the Third Interim report, the European commission, DG Regio requested an alternative classification of the Metropolitan European Growth Areas (MEGAs), as well as an assessment of levels of polycentricity in NUTS 2 regions. These analyses were financed through an extension to the original contract, and the results have been presented in a separate report. The alternative MEGA typology has been used in the present report; the analysis of polycentricity at NUTS 2 level has been judged non-conclusive, and is therefore not included.

The project report and the four annex reports are available at www.espon.lu

Stockholm, August 2004

The content of this report does not necessarily reflect the opinion of the ESPON Monitoring Committee

(7)

ERRATA

A certain number of errors and omission have been notified to us by the ESPON

Coordination Unit and the ESPON European Contact Points. Whenever possible, these errors and omissions have been corrected in the present version of the report. This was however not possible in some cases:

- Because the Novo Mesto FUA in Slovenia was not positioned correctly, it appeared to share less than one third of its PUSH area. The Ljubljana and Novo Mesto PUSH should normally have been considered as a Polycentric Integration Area (PIA).

- In the case of Switzerland, the results are based on population data from 1990. This may have had an influence on the classification of certain Swiss FUAs, e.g. Zürich.

- The Hungarian ECP informs us that the city of Pécs has probably been classified incorrectly in the FUA classification (map 1.3), as it should have been ranked as a FUA of National or Transnational importance.

- The French Outermost Regions (Départements d’Outre-Mer) have not been included in any of the analyses of the present report, as the French statistical office (INSEE) has not produced any delimitation of FUAs in these areas.

(8)

-

Figures

Figure 3.1 Functional urban areas with over 20 000 inhabitants in France and in the Nordic

countries 58

Figure 3.2 Functional urban areas with over 20 000 inhabitants in France and in the Nordic

countries - population density 59

Figure 3.3 Rank-size distributions of population (top) and GDP (bottom) of FUAs in Europe 63

Figure 3.4 Service areas of FUAs in Europe 64

Figure 3.5 Population and accessibility of FUAs 65

Figure 3.6 Rank-size distributions of population of FUAs in selected countries 66 Figure 3.7 Rank-size distributions of the GDP of FUAs in selected countries 67

Figure 3.8 Service areas of FUAs of selected countries 68

Figure 3.9 Population and accessibility of FUAs in selected countries 69 Figure 3.10 Polycentricity indicators of North-Rhine Westphalia 71

Figure 5.1 Examples of Isochrone delimitations 122

Figure 5.2 Approximation to municipal boundaries 124

Figure 5.3 Comparison between the geographical extent of PUSH areas and Isochrones 125 Figure 5.4 Different types of settlement structures (schematic representation). 151 Figure 6.1 European urban network models of integration and air traffic 167 Figure 6.2 The weight of the capitals* in the national university system 169 Figure 6.3 The weight of major cities in the national university system 170 Figure 6.4 The 20 most attractive cities for Erasmus students 171

Figure 6.5 Models of cross-border urban cooperation 174

Figure 7.1 The continuum of partnership 185

Figure 8.1 Swiss city network (Bundesrat, 1996) 219

Figure 8.2 Existing and new centres in the desired polycentric spatial structure for Ireland 219 Figure 8.3 Elements for structuring a polycentric urban network in Portugal 222 Figure 9.1 Challenges in the implementation of polycentricity at all spatial scales 240

Maps

Map 1.1 Functional urban areas in EU 27+2 6

Map 1.2 The degree of polycentricity in national urban systems 7

Map 1.3 Typology of Functional Urban Areas (FUAs) 10

Map 1.4 MEGA typology 12

Map 1.5 Area assigned to PUSH area (in red) 14

Map 1.6 Potential Polycentric Integration Areas in EU 27+2 16

Map 3.1 Size Index of polycentricity 74

Map 3.2 Location Index of polycentricity 75

Map 3.3 Connectivity Index of polycericity 76

Map 3.4 Polycentricity Index 77

Map 3.5 Polycentricity Index of NUTS-1 regions 79

Map 4.1 FUA Population (Mass function) 89

Map 4.2 Transport function 92

Map 4.3 Tourism function 95

Map 4.4 Industrial function 98

Map 4.5 Knowledge function 101

Map 4.6 Business decision-making function 105

Map 4.7 Administrative function 108

Map 5.1 Typology of Functional Urban Areas (FUAs) 114

Map 5.2 MEGA typology 118

Map 5.3 MEGAs situated outside the Pentagon 119

(12)

Map 5.5 Area assigned to Potential Urban Strategic Horizons (PUSH) 126 Map 5.6 Comparison of population figures for nationally defined FUAs and PUSH areas 128 Map 5.7 Number of PUSH areas overlapping in each municipality 130 Map 5.8 Overlay of NUTS 2 boundaries and PUSH areas of cities with over 250 000 inhabitants 132 Map 5.9 Overlay of NUTS 2 boundaries and PUSH areas of cities with between 100 000 and

250 000 inhabitants 133

Map 5.10 Transnational PUSH areas (considering internal study area boundaries only) 134 Map 5.11 Multiple tiers of integration in PIA: the example of Amsterdam 136 Map 5.12 Geographical spread and multi-scalar complexity of Europe’s Polycentric Integration

Areas 137

Map 5.13 PIA overlaid by NUTS 2 boundaries 138

Map 5.14 A major PIA not dominated by any single city: the example of Bielefeld 140 Map 5.15 Difference in population between the PUSH area of individual cities, and that of the PIA

of which they are the main node 142

Map 5.16 Incentive to develop polycentric integration policies, seen from the perspective of individual cities: Change of rank in the European urban hierarchy for each city that is

the main node of a PIA 145

Map 5.17 Uniform polycentric scenario: Change of rank in the European urban hierarchy if all Cities integrate with the PIA defined around them 149 Map 5.18 Classification of PIAs according to their total population 150

Map 5.19 Settlement areas in Europe 153

Map 5.20 Proportion of settlement areas in each PUSH area 154 Map 5.21 Standardised maximum concentration index (average value within each PUSH

area =100) 156

Map 5.22 Representative cases for each class in the typology 158

Map 5.23 Settlement areas within the Paris PUSH area 159

Map 5.24 Settlement areas within the Münster PUSH area 160

Map 5.25 Classification of PUSH areas according to their settlement structure 161

Map 6.1 Evolution of main airflows 165

Map 6.2 Most important international-European air routes in 2000 166

Map 6.3 The main Erasmus networks 170

Map 6.4 Attractiveness of cities for Erasmus students 171

Map 6.5 Main French-Belgian instances of cooperation in Interreg IIa (1994-1999) 173 Map 6.6 Main French-German instances of cooperation in Interreg IIa (1994-1999) 173 Map 6.7 Participation in Interreg IIc, NWMA (North-west Metropolitan area) by city 176 Map 6.8 Interreg IIc CADSES cooperation. The localisation of lead partners by project objective 176

Tables

Table 1.1 Aspects of polycentricity investigated 26

Table 3.1 The key spatial concepts of urban areas 54

Table 3.2 Polycentricity indicators of countries 70

Table 3.3 Value functions of sub-indicators 72

Table 3.4 Component indices and Polycentricity Index of countries 73

Table 4.1 Features and functions of FUAs 85

Table 4.2 Data gathered in making the list of FUAs 86

Table 4.3 Population (mass function) – country reports 87

Table 4.4 Transport function – country reports 90

Table 4.5 Tourism function – country reports 93

Table 4.6 Industrial function – country reports 96

Table 4.7 Knowledge function – country reports 99

(13)

Table 4.8 Business decision-making centre – country reports 103

Table 4.9 Administrative function – country reports 106

Table 4.10 Functional and morphological polycentricity compared 110 Table 5.1 Typology of Functional Urban Areas (FUAs) – country reports 112 Table 5.2 Average MEGA population and number of inhabitants (national population) per MEGA

for each country 113

Table 5.3 MEGA analysis variables 116

Table 5.4 Result of the iterative identification of PIA 135 Table 5.5 Highest and lowest proportions of total population in FUAs living in the main node,

for each Potential Polycentric Integration area (PIA) 139 Table 5.6 Main Potential Polycentric Integration Areas (PIA) in Europe 141

Table 7.1 The Benefits of Partnership 183

Table 7.2 A Typology of Partnerships 184

Table 7.3 Objectives of the Partnership 191

Table 7.4 Achievements of the Partnership 192

Table 7.5 Strengths of Partnerships 193

Table 7.6 Weaknesses of Partnerships 193

Table 8.1 Main objectives of current polycentric policies in ESPON countries 208 Table 8.2 Type of gaps in national urban systems and privileged groups of cities 208

Table 8.3 Categories of instruments 212

Table 8.4 The use of strategic planning instruments 216

Table 8.5 Polycentric development policies in Europe according to priority, status and scale 217

Table 9.1 Policy recommendations of the ESDP 227

Table 9.2 Concepts and policies on polycentricity at different spatial levels 228

(14)

(15)

Part 1 Summary

(16)

(17)

1 Summary

1.1 Executive summary

1.1.1 The concept of polycentricity

Polycentricity has two complementary aspects. The first relates to morphology, i.e. the distribution of urban areas in a given territory (number of cities, hierarchy, distribution).

The second concerns the relations between urban areas, i.e. the networks of flows and co- operation. These flows are generally related to proximity, though networks can also be independent of distance.

We can speak about polycentricity in two different situations. Looking at an urban system from a continental or national perspective, polycentricity occurs when the system is characterised by several cities at different levels rather than just being dominated by one city. At this level, polycentric policies stimulate the growth of centres and regions outside the core. At the regional or local scale, polycentricity occurs when two or more cities have functions that complement each other and even more so, if the cities co-operate with each other in order to be able to act jointly as a larger city. At this level, policies for polycentricity stimulate the functional division of labour, as well as the flows and the level of co-operation between neighbouring cities. The two situations are interlinked when e.g. polycentric integration at the regional level contributes to counterbalance the dominance of the national centre.

Polycentricity originated as an empirical concept in the 1930s, with the development of central-place theory. The concept of polycentricity first appeared at the European level with the adoption of the Leipzig principles in 1994 in relation to the ESDP process. Polycentricity is a key policy aim of the ESDP. It is hoped that a more polycentric urban structure will contribute to a more balanced regional development, to reducing regional disparities, to increasing European competitiveness, to the fuller integration of European regions into the global economy, and to sustainable development.

Polycentricity is opposed to monocentricity, in which service provision and territorial management competence is increasingly concentrated to a single centre. Polycentricity is also opposed to urban sprawl, in which the structure of secondary centres is diluted in a spatially unstructured continuum. Rather, polycentricity is about promoting the balanced and multiscalar types of urban networks that are most beneficial from a social and economic point of view, both for the core areas and for the peripheries.

At the European level (macro), polycentricity is seen as a useful alternative model to enhance regional development more evenly across the European territory. A polycentric Europe is thus seen as an attractive alternative to a European space dominated by the Pentagon, the area delimitated by London, Hamburg, Munich, Milan and Paris, i.e. the European core with approximately 14% of the EU27 area, 32% of its population and 43% of

(18)

global integration zones. A European wide application of polycentricity is designed to promote several larger zones of global economic integration in the EU in addition to the Pentagon.

At the interregional or meso level, urban complementarities are important. Two or more cities can complement each other functionally by offering the citizens and companies in their conjoined hinterlands access to urban functions that would usually only be offered by higher-ranking cities. Rather than competing to build up the same urban functions, the ESDP recommends that cities should co-operate by joining existing assets, in particular assets that are complementary.

In the context of intra-regional development (micro), urban functional and economic complementarities are emphasised. An urban region can improve its economic performance through better co-operation and improved links within the region. An intra-regional application of polycentricity thus promotes integrated spatial development strategies for city clusters.

The idea of polycentric development thus runs parallel to the shift in regional policies towards an emphasis on the development of specialised regional competencies, where synergy and strength are sought and developed through regional networks of specialists, suppliers, specialised education and labour markets, much of which is nested in tacit abilities and competencies that are difficult to codify and hence, difficult to reproduce elsewhere.

Previous research on this general topic has focused predominantly on the intra-urban scale and on the organisation of cities at the local level. For the ESDP, as well as for this project however, the point of departure is that of the European scale, as little research has as yet been done in respect of the European level (macro) or the inter-regional level (meso) in this regard. As such, this project, as with the other projects in the ESPON programme, is rather unique, both because it has a top-down perspective and because it covers all 29 countries of the ESPON space.

1.1.2 The morphology of the urban system in Europe

The building blocks of polycentricity are the functional urban areas (FUAs). A FUA consists of an urban core and the area around it that is economically integrated with the centre, e.g.

the local labour market. Our first task then was to map the urban structure of the EU27+2 as comparatively as possible. In countries that have definitions of travel-to-work areas, commuter catchment areas, urban poles etc., these are used for the identification of FUAs.

In countries lacking official definitions, the identification of FUAs was based on insights provided by our national experts. The use of national definitions means, however, that the choice of FUAs is not totally comparable across Europe.

In countries with more than 10 million inhabitants, a FUA is defined as having an urban core of at least 15,000 inhabitants and over 50,000 in total population. For smaller countries, a FUA should have an urban core of at least 15,000 inhabitants and more than 0.5% of the national population, as well as having functions of national or regional importance. Based on

(19)

this definition, a total of 1,595 FUAs with more than 20,000 inhabitants have been identified in EU27+2 (map 1.1), of which London, Paris and Madrid have more than 5 million inhabitants, and 44 FUAs have 1-5 million inhabitants.

A dense urban structure covers the central parts of Europe, stretching from the UK in the north via the Netherlands, Belgium, western Germany and northern France, and continuing both east and west of the Alps in the south; in the west to Italy, and to the east through the Czech Republic, southern Poland and Slovakia, into Hungary.

The countries to the north and to the south of this area are less populated and have less dense urban systems. This is particularly true of Ireland, the northern areas of the UK, Norway, Sweden, Finland, Estonia, Latvia and Lithuania, but also for parts of Spain, Portugal, Greece, Bulgaria and Romania.

1.1.3 The degree of polycentricity in national urban systems

The countries are the best-integrated territorial level in Europe, and are therefore best suited for a discussion of the degree of polycentrism. With the FUAs as building blocks, we have analysed the national urban systems on the basis of the following three dimensions of polycentricity:

Size. A flat rank-size distribution is more polycentric that a steep one, and a polycentric urban system should not be dominated by one large city.

Location. A uniform distribution of cities across a territory is more appropriate for a polycentric urban system than a highly polarised one where all major cities are clustered in one part of the territory.

Connectivity. In a polycentric system, both small and large FUAs have good accessibility.

The more accessible lower-level centres are compared to the primary city, the less monocentric is the urban system.

Based on indicators for each of these three dimensions, a comprehensive index of polycentricity was constructed for 26 countries, excluding Luxembourg, Cyprus and Malta where the number of FUAs is insufficient (map 1.2). The most polycentric countries are Slovenia, Ireland, Poland, Denmark and the Netherlands, though they are so for rather different reasons. Slovenia and the Netherlands have a high score for all three dimensions, Poland has a balanced size distribution and Ireland and Denmark have a good distribution of FUAs over their territory.

Other countries generally thought to be polycentric score less well because they are deficient in one of the dimensions, e.g. Italy, Germany and the UK where cities are concentrated in one part of the country. The most monocentric countries are Norway, Finland, Spain, Hungary, Portugal and Sweden.

(20)

Map 1.1 Functional urban areas in EU 27+2

(21)

Map 1.2 The degree of polycentricity in national urban systems

As polycentricity is not a goal in itself but one of the means to achieving policy objectives

(22)

polycentricity index was confronted with indicators for these three factors. Here we find a correlation between polycentricity and GDP per capita, confirming that countries with a more polycentric structure are economically more successful. There is also a correlation between energy consumption (used as an indicator for sustainability) and polycentricity, showing that polycentric countries use less energy. However, these relationships are not particularly strong. Moreover it is difficult to deduce any causal links from them, as both better economic performance and lower energy consumption in polycentric countries may be linked to other factors. Among the new EU member states, more polycentric countries have smaller differences in income levels between central and peripheral regions than do monocentric ones. This correlation is however not found in the old member states.

1.1.4 The functional specialisation of urban nodes

Functional specialisation is an important dimension of polycentricity as it is these functions that make cities different from each other and produce the flows necessary for economic and political integration. We have therefore mapped the functional specialisation of the FUAs and made a classification of the urban areas in EU 27+2.

All FUAs are obviously not of the same importance in the national or European urban system. Some are larger than others, and do therefore display a greater variety of functions and services. Some are of national and/or European significance based on the strengths of their manufacturing or service industries; others are the sites of regional, national and/or European administrations.

Only limited access is available to statistics on the level of FUAs. We have identified seven functions of urban areas that, taken together, provide us with an initial indication of their role in Europe, and we have further identified indicators that it is possible to measure in a comparable fashion. Each FUA has been ranked according to its importance for each variable. The analysis reveals the following pattern:

Population: For both private and public-sector investments the demographic weight naturally constitutes the most favoured indicator for choosing the location of certain services and facilities. Population is concentrated in the Pentagon, though there are extensions reaching down to Southern Italy and to central and Eastern Europe, where there is a strong concentration of large urban agglomerations. In peripheral Europe most of the large urban agglomerations are more insular.

Transport: The connectivity of the FUAs constitutes one of the central factors of polycentrism. Any sharing of economic functions cannot be really effective unless accompanied by an efficient transport infrastructure and by accessibility. Transport is measured by means of the main airports and major container traffic harbours, in order to explicitly identify transport-oriented cities. As a result, the general picture is rather monocentric, particularly in the geographically small countries. The busiest transport nodes are found in the Pentagon. Not one acceding country has a transport node of European significance.

(23)

Tourism: Tourism is an indicator for attractiveness. Most of the FUAs strong in tourism are different from those that score highly in other functions, and they are mainly located in the Mediterranean area and the Alps. Only a few highly tourist-oriented FUAs of European-level significance exist beyond these two zones. Globally significant urban destinations are to be found in London, Paris and Rome. Capital cities are in general also important nodes as regards tourism.

Manufacturing: The urban systems are in many countries the result of industrialisation.

Manufacturing industries are in decline in most regions, though they remain however the backbone of the economy in many others. Many industrial FUAs are trading globally, even the smaller ones. As such, industrial strength was measured by calculating the gross value added in manufacturing. The strongest FUAs are to be found in the Pentagon. Gross value added is often low in the acceding countries, except in capital regions and in Poland.

Knowledge: This function is measured by calculating the number of students attending higher education institutes. In all countries, the capitals are the strongest nodes in knowledge terms, though many other FUAs are also important. The general picture is therefore rather balanced, as higher education is distributed across all parts of Europe, and within most of the countries as well.

Decision-making in the private sector: Any urban system’s ‘capacity to influence’ is not solely dependent upon its level of competitiveness and demographic weight, but also on its actual economic attractiveness to private investors. The distribution of the headquarters of top European firms is an indicator of economic attractiveness. Business headquarters locate in places with good accessibility and where they are close to business services. Decision-making however remains highly concentrated to the Pentagon, as Stockholm is the only FUA outside the Pentagon that makes the top list.

Decision-making in the public sector: Strong hierarchies within urban systems are often due to the development of administrative functions. The current picture of Europe is thus the result of the growth and development of individual national systems with the capitals being the main nodes of the European administrative system.

Most crucial economic functions such as the location of European decision centres are concentrated within the Pentagon. The knowledge function is more balanced due to the location of universities in national educational systems all over Europe. The tourism and transport indicators are different, showing a pattern of the functional division of labour at the EU level. Thus, tourism is concentrated in the Alps and the Mediterranean coastal regions and transport within the northern-most parts of central Europe.

In Map 1.3, all variables except Tourism and Administration have been combined to give an overall ranking of the FUAs into three groups. The 76 FUAs with the highest average score have been labelled Metropolitan European Growth Areas (MEGAs).

(24)

Map 1.3 Typology of Functional Urban Areas (FUAs)

(25)

1.1.5 Possible counterweights to the Pentagon

The strengths of the strongest FUAs, the 76 MEGAs, are analysed further in a discussion of where the most likely counterweights to the Pentagon are to be found. The analysis here is based on indicators for each of the following four qualities:

Mass. The denser a regions’ economic environment is, the more likely it is to present favourable conditions for its development. Mass is measured by the population size and the size of the economy.

Competitiveness. The degree of attractiveness for private companies is measured by the GDP per capita and the location of head offices for the top 500 European companies.

Connectivity. Attractive regions have good connectivity to other regions. Indicators used here are the number of airport passengers and the regions’ multimodal accessibility.

Knowledge basis. The percentage of the population with higher education and the share of the employed working with R&D measure the attractiveness of a FUA.

The MEGAs are compared with each other for each quality, ranked and divided into five groups (map 1.4):

Two global nodes are identified, London and Paris. These are the largest, most competitive and have the best connectivity.

There are 17 Category 1 MEGAs, large city regions with a good score on all indicators:

Munich, Frankfurt, Madrid, Milan, Rome, Hamburg, Brussels, Copenhagen, Zurich, Amsterdam, Berlin, Barcelona, Stuttgart, Stockholm, Düsseldorf, Vienna and Cologne.

Ten of these are located within the Pentagon.

At the next level comes the 8 Category 2 MEGAs, cities that are relatively large, competitive and often with a strong knowledge basis. Most MEGAs in this category have one or two qualities that are notably weaker than the others, usually relating to either mass or accessibility. These are Athens, Dublin, Geneva, Gothenburg, Helsinki, Manchester, Oslo and Torino.

26 MEGAs are labelled Category 3 MEGAs. These are usually smaller, with lower competitiveness and accessibility levels. They often have one quality that is stronger than the others. The four strongest city regions in the new member states are in this category: Prague, Warsaw, Budapest and Bratislava together with the three other capitals Bern, Luxembourg and Lisbon. The rest are non-capital cities in their countries:

Lyon, Antwerp, Rotterdam, Aarhus, Malmö, Marseille, Nice, Bremen, Toulouse, Lille, Bergen, Edinburgh, Glasgow, Birmingham, Palma de Mallorca, Bologna, Bilbao, Valencia and Naples.

(26)

Map 1.4 MEGA typology

(27)

The remaining 23 regions are the Category 4 MEGAs. Most of these have a low score on all four qualities. 15 of them are located in the new member states or accession countries (Bucharest, Tallinn, Sofia, Ljubljana, Katowice, Vilnius, Krakow, Riga, Lodz, Poznan, Szczecin, Gdansk-Gdynia, Wroklaw, Timisoara and Valetta), four are cities of north-western Europe situated outside the main transport corridors (Cork, Le Havre, Southampton and Turku) while the remaining four are non-capital cities in the southern part of EU15 (Bordeaux, Seville, Porto and Genoa).

This analysis has identified the strongest urban regions in Europe. Many of them are located within the Pentagon, while others such as Rome, Vienna, Berlin, Manchester and Copenhagen are located in relatively close proximity to the Pentagon. There are only a few top category MEGAs in the peripheral parts of Europe: Madrid, Barcelona and Athens in south, Dublin in west and Stockholm, Helsinki, Oslo and Gothenburg in north. MEGAs with high scores in the new member states are also located close to Pentagon, with Warsaw being the only exception.

1.1.6 The potential for polycentricity based on morphological proximity

Thus far, the analysis has been descriptive. The next question then is where can we find the most promising potential for development towards a more polycentric urban system for Europe? The preconditions for polycentricity are best where cities are located in proximity to each other. The question is therefore where new functional entities, created trough increased integration and co-operation, may change the European urban hierarchy: where can new nodes emerge, strong enough to counterbalance the Pentagon?

Morphological proximity is of course no guarantee of co-operation, but proximity does nevertheless provide cities with a better opportunity for functional integration. Our hypothesis is that cities with overlapping travel-to-work-areas have the best potential for developing synergies. For each of the FUAs, we have calculated the area that can be reached within 45 minutes by car from the FUA centre. These areas are then approximated to municipal boundaries, as municipalities are potential building blocks in polycentric development strategies. This approximation also makes it possible to use population data at the NUTS 5 level, i.e. for municipalities. The resulting areas are labelled Potential Urban Strategic Horizons (PUSH).

Several countries are almost entirely covered by PUSH areas (map 1.5), while large parts of the most peripheral countries are located far away from any FUA centre. On average, 66%

of the EU27+2 area is covered within 45 minutes travel time of a FUA centre. The values range from 98-93% in Luxembourg, Belgium, Denmark, the Netherlands and Germany, to 36-33% in Cyprus, Sweden, Malta and Finland, down to only 25% in Norway.

(28)

Map 1.5 Area assigned to PUSH area (in red) – municipalities of which at least 10% of the

area is within 45 minutes from the nearest FUA centres

(29)

The population in these PUSH areas is different from the FUA population, as the PUSH areas are defined according to 45-minute isochrones and can overlap each other. The largest differences here are to be found in the smaller cities located within the vicinity of major metropolitan areas. In the most urbanised zone stretching from the Midlands in the UK down to southern Italy, more than 10 and up to 43 PUSH centres can be reached within 45 minutes.

In the next step, Potential Polycentric Integration Areas (PIAs) were identified, based on the hypothesis that neighbouring cities with overlapping travel-to-work-areas can be functionally integrated and can gain from co-operation. A total of 249 areas were found where at least two PUSH areas shared more than 1/3 of their area with each other. These areas concern 1,139 PUSHs, while the remaining 456 PUSHs are more isolated. The 249 areas are well distributed across Europe, with the exception of Ireland and the northern parts of the UK, Norway, Sweden and Finland.

Map 1.6 illustrates the potential mass each PIA can aim for in absolute terms. It shows the population of PIAs, using the same threshold values as for the FUAs in Map 1.1. These population levels can of course not be obtained simultaneously by all PIAs, as their delimitations overlap. Here again, the concentration of PIAs with an exceptionally high population potential from the UK Midlands to Northern Italy and over most of Germany is apparent. Outside this extended Pentagon area, Naples and Barcelona are the only new centres with more than 5 million inhabitants as compared to Map 1.1.

A wide range of cities could significantly increase their demographic mass, and thus also their position in the European urban hierarchy though polycentric integration. The majority of these cities are situated inside this extended Pentagon area. The larger peripheral PIAs that would improve their position most through integration are Montpellier, Decin, Rimini, Palermo, Messina, Copenhagen, Bari, Alicante, Oslo, Belfast, Porto, Glasgow and Valencia.

One conclusion here is that the definition of the European core as ‘the Pentagon’ is too narrow. In terms of population and dense city networks, Manchester, Berlin, Venice, Genoa and Paris define the corners of the European core.

A second conclusion is that polycentricity at the European level must build upon functional specialisation, i.e. stimulate cities outside the core area to develop functions for the whole of Europe. Increasing the demographic mass of cities through regional polycentric integration is, if it is done everywhere across Europe, likely to further enhance the contrasts between the European core area and the rest of the European territory. We cannot currently identify any region in the European periphery where the polycentric integration of neighbouring cities could increase the population mass sufficiently to the extent that the potential for a new global integration zone was created.

(30)

Map 1.6 Potential Polycentric Integration Areas in EU 27+2

(31)

1.1.7 Transnational networks and co-operation

Thus far, we have mapped the urban system and investigated its functional specialisation.

The discussion of the potential of polycentricity is based on morphological proximity. A third important precondition for polycentricity is that of functional integration and co-operation.

However, data on flows and networks is difficult to obtain. It is therefore not possible to study the degree of integration at the pan-European level. We can however provide some examples of specialised and thematic networks and co-operation between cities at the European level. Networks are monocentric if they are oriented towards a limited number of strong centres, and more polycentric if connections are more evenly distributed between partners.

The network of air traffic reflects the actual market for travel services as well as the organisational structure of the air traffic business, where some cities act as hubs and consequently have the best accessibility. Over the last decade a noticeable trend has emerged towards the increasing polarisation of flows through London and Paris. The highest growth in passenger numbers are thus to be observed between the peripheral capitals and the centrally located capitals, with the largest traffic growth in cities such as Lisbon, Madrid, Barcelona, Prague, Munich, Berlin and Warsaw. The most significant flows between Europe and the rest of the world go through London. Paris and Frankfurt are also important gateways, as is Madrid, which acts as a gateway to South America.

A second example is the network of student exchanges between universities, supported by the EASMUS programme. The dynamic of student exchange flows primarily reflects the location of national capitals. Secondly, there is a significant concentration at the European level towards Paris, Madrid, Barcelona, London and Berlin. With regard to the new member states and to the accession countries the numbers here are rather small, with the concentration to one city region being quite high. Thus, while we can see that a rather balanced network exists in this regard between universities across Europe, in the smaller countries only a limited number of cities are actually involved.

A third example of transnational networks is that of the Interreg programme, where authorities are encouraged to co-operate across national borders. We have analysed programme participation in two Interreg IIIB regions, NWMA and CADSES. In the NWMA programme, there are interesting differences between France and Belgium on the one hand, where the participants are located in a very limited number of cities, and the UK and the Netherlands on the other, where networks are much denser. Other types of contrasts can be found in the CADSES area, where Austrian participants are concentrated to Vienna while German participants are more widespread. These two countries are the most active, while the other participating countries, namely, Bulgaria, the Czech Republic, Greece Italy, Hungary, Poland, Romania, Slovakia, Slovenia and the nine additional non-ESPON countries have been less active. This illustrates the multiple scales involved when trying to assess the degree of poly- or Monocentricity of a network: The organisation of cities at the national scale influences the spread of partners in each country, while contrasts between Member states can create an imbalance in the number of partners on each side of the border.

(32)

These examples illustrate the fact that size should not be considered as a comprehensive indicator when identifying nodes of polycentric development. Transnational networks between universities, private companies and other urban functions are particularly important for the development of polycentricity if networking is established between 2^nd order cities and are thus able contribute to stabilising the position of these cities in the national urban hierarchies. The transnational networking within meso-regions such as e.g.

the Interreg regions, contributes to the development of polycentricity if regional integration and competitiveness results from such co-operation.

1.1.8 The experience of co-operation and partnership in spatial policies

The benefits of partnership are described as synergy creation, transformation and consensus construction, budget enlargement, place promotion, co-ordination, and the legitimisation of pro-growth policies. In the literature, the rise of partnerships is mainly described as an approach to tackling urban problems, i.e. below the spatial focus of this study.

Polycentricity at the micro, meso and macro levels is about functional integration and co- operation between urban areas. Two questionnaire surveys of existing partnerships were undertaken to provide an overview of institutional networking and partnership arrangements around spatial strategic issues.

The first survey concerned inter-municipal co-operation at the level of FUAs, with 21 countries responding. While functional urban regions in many cases are the level of socio- economic analysis, there are very few examples to be found of polices actually being implemented at that level. Public administration is not organised on the basis of functional regions, and there is no formal structure of governance at this level.

The late 1980s and early 1990s marked the beginning of a growing number of inter- municipal partnerships across Europe. Some are small, single-sector networks (such as the National Centre Mid-Vest in Denmark and the Association of Municipalities of Lima Valley in Portugal); others are large multi-sector networks (such as Patto Territoriale del Sangone in Italy with 108 partners). Their objectives can be divided into four categories: Strategic development, project implementation (often time-limited), networking and advocacy. Most partnerships do not have executive powers. They do however influence policy-making processes by making recommendations, lobbying or through undertaking studies and programmes. Their strengths are in the co-ordination of resources, goals and objectives;

building access to knowledge and expertise, and the promotion of mutual dependence and shared understandings of common challenges. Their main weaknesses are often their lack of resources and political commitment.

The second survey concerned inter-regional and trans-national co-operation at the European level. Seven potentially polycentric cross-border areas responded, and information from another five was also utilised in the analysis. Economic and commercial development was the most common field of co-operation here. The rationale for preparing joint strategies focussed on the need to develop complementarities and the need to exploit

(33)

the broader marketing potential of two or more centres. Improving functional complementarity and enhancing economic co-operation was the stated aim of e.g. the Gorizia/Nova Gorica (Italy and Slovenia) and Øresund (Denmark and Sweden). There are few examples of joint strategic planning however, though this is perhaps somewhat surprising, as we would expect transport to be a significant issue for trans-national co- operation. In some cases tendencies towards competition remain (e.g. Edinburgh-Glasgow and the "Alpine Diamond" with Lyon, Geneva and Torino), and in some cases dependence rather than partnership prevails (e.g. the larger Bologna). The potential for polycentric development is mentioned as a key factor in partnership establishment only in Silesia/Moravia-Silesia (Poland and the Czech Republic) and Gorizia/Nova Gorica.

Apart from the above-mentioned examples, polycentric integration of the urban network was rarely mentioned as an instrument or an objective by the partnerships covered by the surveys. Current debates over polycentricity at the European level have however contributed to placing this issue on the table in terms of the future of partnerships at the local, regional and trans-national levels.

1.1.9 Polycentricity in national spatial planning and regional policies

The application of the concept of polycentricity has been encouraged by the ESDP. We have, through a questionnaire, collected information on the use of polycentricity in plans and strategies at the national level throughout the ESPON space. As the word polycentric is only rarely used, the information covers spatial policies in a wider sense. Of the 29 countries covered, 18 claim to pursue polycentric development in one way or another.

Two different clusters of objectives can be identified here. The most important goal is to enhance urban competitiveness, while the second is to reduce disparities between urban areas. These objectives do not necessarily exclude each other.

Polycentric policies for competitiveness link the size and importance of cities, and classify the national urban system in a hierarchy often based on a desired future rather than current realities. Several countries have developed appealing metaphors for internationally competing centres, such as European Metropolitan Regions (Germany), Gateways (Greece, Ireland), Centres de Développement et d’attraction (Luxembourg), Europols (Poland) and Anchor cities (Portugal). In many cases, urban competitiveness is promoted by inter- municipal co-operation (i.e. France, Germany, Italy, the Netherlands) or by administrative reform (i.e. France, Greece, Latvia, Spain).

The types of urban disparities addressed are different from country to country. In countries such as Denmark, Estonia, France, Ireland and Latvia the focus is on the gap between the capital regions and the rest of the cities. In Germany, Italy, Norway and Poland there are north/south or east/west disparities, while countries such as Finland, Greece and Portugal focus on the need to strengthen the medium-sized cities in their urban hierarchies.