Which diversity in the hierarchical organisation of urban systems in Europe?

Transcription

1 Which diversity in the hierarchical organisation of urban systems in Europe? Denise Pumain Université Paris I, UMR Géographie-cités Céline Rozenblat Université de Lausanne 1

2 A geographical ontology of urban systems Two levels: Cities Systems of cities Pumain D. Hierarchy in natural and social sciences, Springer, 2006

3 Urban hierarchy: universal structural feature Zipf s law: Continuum of city sizes over more than 4 orders of magnitude inhab. Pumain et al. 2015, Cybergeo, 706

4 Cities sizes are relative to the size of the system they belong to

5 City sizes are relative to territories City Name Population 2011 (000s) Rank in Eastern & Central Europe Varsovie Budapest Bucarest Katovice (FUA) Prague Sofia Zagreb Bratislava Ljubljana Source: Bretagnolle et al. Tradeve data base 5

6 Decentralization trends since 1991 in Eastern and Central Europe? CLASSES TCAM TCAM TCAM TCAM façade «Ouest» 2. façade «Centre» 3. façade «Est» 1,57 0,71 0,02 0,05 1,82 0,99-0,01 0,12 2,19 1,26-0,23-0,11 Source: Zdanevska,

7 Analysis of urban hierarchies Evolutionary theory of urban systems (Pumain, 1997) connecting four theoretical lines: Distribution of city population sizes and urban growth models (Zipf, Gibrat) Central place theory: number and diversity of urban functions (Christaller, Berry, Pred) Spatial diffusion of innovations (Hägerstrand) Scaling laws 7

8 Scaling laws in complex systems Scaling laws: Non-linear relationship between size of entities and some of their functional attributes reveal physical constraints on the structure and evolution of complex systems (spatial distribution of energy through fractal networks, theory in biology: West, Brown & Enquist, Science, 1997 & 99) Application to urban systems: D. Lane, D. Pumain, S. van der Leeuw, G. West: Complexity perspectives in Innovation and Social change, Springer, 2009 (FET EU programme: ISCOM (Information Society as a Complex System)

9 Two interpretations of scaling laws x t = y t β where x is an attribute y is the size of a city measured in a system of cities at date t Physicists: linking urban attributes to city size reveals scaling laws that are expressing universal constraints on the dynamics of complex systems Geographers: as urban systems are not ergodic (crosssectional data cannot receive the same interpretation as longitudinal) scaling laws are revealing constraints on urban development that are relative to its geohistorical context 9

10 Scaling parameters according to urban attributes β <1: gasoline stations, gasoline sales, length of electrical cables, road surface (= scale economies) β = 1: total establishments, total employment, household power and water consumptions β >1 : wages, GDP, patents, inventors, R&D employment, housing costs, walking speed Luís M. A. Bettencourt, José Lobo, and Geoffrey B. West,

11 Scaling parameters and growth trajectories dn R R 1 (linear) => 1 0 N exponential dtt E0 1 (sublinear) => sigmoidal: ( ) t R Nt R 1 (superlinear) 1 1 : N () t R N1 (0) R R R e R E 0 0 ( 1) t Source: Bettencourt, Lobo, West,

12 Growth trajectories according to scaling exponent <1 =1 >1 Source: Bettencourt et al.,

13 Urban trajectory (Bettencourt et al., 2009) Pb: model does not fit with observations 13

14 A «static», «universal physical» interpretation of scaling exponents (Bettencourt et al. 2009) Scaling Exponent Driving Force Organization Growth <1 Optimization, Efficiency Biological Sigmoidal Long term stagnation >1 Creation of Information, Wealth and Resources Sociological Boom / Collapse Finite time singularity Increasing acceleration/discontinuities =1 Individual Maintenance Individual Exponential 14

15 A «physicalist» interpretation of urban scaling laws Values of scaling parameters >1 are a novelty (when comparing urban systems to biological): Bettencourt, Lobo, Helbing, Kühnert, West, P.N.A.S., 2007, 104 From theoretical considerations linking resource consomption and growth, supralinear scaling laws imply superexponential growth (infinite growth in finite time) and a succession of crisis at shorter and shorter time intervals accelerating pace of social life as cities grow larger 15

16 The theory crazes the medias! 16

17 Scaling laws in social systems Physical interpretation : in terms of growth process in principle very appealing and challenging BUT: A fundamental (hidden?) hypothesis for deducing the shape of growth curves is that the system is ergodic (any individual particle (=a city) can reach any state any time) Urban systems are not ergodic!!! 17

18 A geographical interpretation: scaling laws and innovation waves in urban systems evolution Stage in innovation cycles and scaling parameter of urban activities: Leading, innovative β > 1 Diffusing β 1 Mature β <1 Scaling exponents as tools for analyzing adaptive diffusion processes in urban systems 18

19 Variations in scaling parameters confirms evolutionary interpretation Stages in innovation cycle Innovative sectors β > 1 France USA South Africa - Financial activities, Insurance, Real Estate - Research and development - Manufacturing - Business services, Consultancy Common sectors β 1 Mature sectors β <1 - Hotels and Restaurants - Community, social, personal services - Manufacturing - Retail Trade - Utilities - Retail Trade - Community, social and personal services - Utilities - Private Households Paulus et al. in Lane et al., 2009 Pumain, Paulus, Vacchiani-Marcuzzo, Cybergeo, 2006

20 Number of employed in Manufacturing, Research and Education Scaling laws according to innovation waves ß Manufacturing = 1.3 ß Research = 1.2 ß Education = 0.8 Chinese cities Elfie Swerts 2013 Number of employed in cities in 2000

21 Methodological steps for analyzing globalization processes in European cities Cities defined as 356 functional urban areas > inhab. UE+ (29 countries : ESPON, 2010; BBSR, 2011; Halbert et al., 2012) Selection of 25 urban indicators according to their scaling exponent as revealing traces of the recent adaptive process (globalisation inducing metropolization) Construction of a composite metropolization index by PCA Estimation of scaling exponents linking composite index and urban size 21

22 Types of metropolization indicators Productive capacity Accessibility Attractiveness Centrality in investment networks Centrality in European research space Cultural influence Access to European institutions 22

23 Contrasted patterns of urban hierarchy according to indicators N es Nb of cultural places Investment in FP6 23

24 PCA summary of metropolization PCA 26 indicators 356 FUAS 24

25 Position of FUAS on composite metropolization index (PCA first 2 axes) PCA 26 indicators 356 FUAS 25

26 Two metropolization gradients in Europe x = y β (x= composite index; y = city size) Western Europe: β = 0.6 = metropolitan features are reaching the smaller cities New member states: β = 1.2 = higher concentration of metropolitan features in the largest cities Two stages of globalisation processes diffusion in European Western and Eastern urban systems 26

27 Two scaling laws for the PCA first factor Red line= W. Europe β = 0.6 Yellow line E. Europe β =

28 Urban advances and delays in adaptation process within each urban system (=residuals to scaling laws) 28

29 Thank you for your attention! 29