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Integrating Culture in European Spatial Analysis: Methods and Results

Explore methodological challenges and outcomes of ESPON project 1.3.3 focusing on cultural data analysis in European regions, highlighting indicators, regional categories, and policy implications.

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Integrating Culture in European Spatial Analysis: Methods and Results

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  1. ESPON project 1.3.3Integrating culture in European spatial analysis: methods, issues, results ANTONIO PAOLO RUSSO EURICURRotterdam Universitat Rovira i Virgili, Tarragona

  2. Methodological problems and limitations • In some cases, data difficult to obtain • Database collection started from scratch • Inconsistent databases across countries • example: map A.0 • Nature of data • “subjective judgements” on what is culture • Lack of time series: static analysis • Spatial effects not always evident – further elaboration needed • Cross-effects with other ESPON dimensions not always evident / causal relations not always clear AP Russo - ESPON seminar

  3. Output of 1.3.3: base indicators • 20 indicators of CHI – complete EU cover NUTS II or III • Commodity focus. presence, density, potential use pressure of: • Heritage assets – intangible immovable heritage • Heritage “landscapes” – heritage conjuncts with spatial extension • Museums – movable heritage reunited in a place • Productive focus • Cultural professions (% “creative” jobs) • Capacity focus • Cultural diversity (diversity index according to nationalities) • Attainment level (% highly educed residents) • Other incomplete datasets used to do analysis / case studies • Events, ethnic diversity, university output, etc. AP Russo - ESPON seminar

  4. Output of 1.3.3: regional categories • Classification # 1 based on demand-supply analysis • Define a “market” for cultural assets (main focus on tourism) • Objectives: classify regions by match between (potential) demands and supply of heritage assets • Classification # 2 based on functional specialisations of culture • Rank regions according to their relative and combined specialisation with respect to three main “functional aspects of culture” • Conservation: how likely is a region to “protect” its cultural resources • Production: how likely is a region to produce new cultural assets • Valorisation: how likely is a region to “sell” its cultural resources • Build indices of C, P, and V from ESPON 1.3.3 indicators: “rule of thumb” method! • Maps based on C, P, V rankings and on combined specialisations • Classification # 3 based on cross-thematic analysis of ESPON 1.3.3 and other ESPON projects • Objectives: classify regions by outstanding relations between cultural features and other ESPON measures AP Russo - ESPON seminar

  5. Resulting map • Pale yellow areas: “balance”, unexceptional value of D and S • A few “green” areas (Vienna, Inner London): there’s a lot to see, and also a lot of users. • Pink areas (Brussels, Prague, Berlin): a lot to see but fewer potential users. • Light blue areas: low D, low S • Ochre areas (most of Italy, Cyprus, Manchester, Bratislava): a very high pressure compared to resources • Policies are needed to “upgrade” • All regions would want to be green, red, or pink AP Russo - ESPON seminar

  6. CPV: large urban areas + Highlands, Estonia, Aragon • CP: secondary cities • CV: rural areas • PV: (post)-industrial cities • C: secondary urban centres, rural areas • P: smaller production clusters • V: mostly coastal tourism destinations • POLICY RULE: develop unfocused cultural functions! AP Russo - ESPON seminar

  7. Cross-thematic analysis: main results • Interesting relation between urban structure and cultural attributes • Culture as a socio-economic determinant • Cultural excellence vs. competitiveness (Lisbon Strategy) • Other territorial features analysed vs. culture: • Vulnerability • Accessibility • Diversity AP Russo - ESPON seminar

  8. Key policy implications • LOCAL LEVEL: • Improve regional positioning with respect to regional categories through targeted strategies (e.g. “matrix of tourism development goals”) • REGIONAL / NATIONAL LEVEL: • Development policies based on cultural potentials (see cross-thematic maps) • EU LEVEL: • Standardised inventoring of cultural data and integration of cultural data in EU databases AP Russo - ESPON seminar

  9. Low P, high S Under-exploitation of heritage High P, high S Potential for valorisation of heritage Increase demand (higher gear in cultural marketing) POTENTIAL DEMAND FOR HERITAGE RESOURCES “Balance” Create “alternative” cultural products to satisfy existing demand Capacity building: increase “new” cultural assets and use them in regional promotion strategies Reduce pressure levels (e.g. extreme protection) Low P, low S Cultural capacity deficit High P, low S Heritage at risk (excess demand pressure) SUPPLY OF HERITAGE RESOURCES

  10. Open issues for ESPON 2013 • Database homogenisation • Data formats and methods: a template for EU data accounting? • Culture monitor as a structural ESPON activity • Extension in time/space/content • Obtain time series • Analyse eastern/southern borders of Europe • Social “embedding” of culture • Causal relations / dynamic modelling • From spatial analysis to (transversal and sectoral) policy directives e.g. tourism AP Russo - ESPON seminar

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