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Alexandru Bănică, Researcher, Ph.D, Romanian Academy - Iași Branch,
Romania [email protected]
ROMANIAN FUNCTIONAL URBAN AREAS: BETWEEN POLARIZATION AND SPATIAL RESILIENCE
Prof. Ionel Muntele, Researcher, Ph.D, Romanian Academy - Iași Branch,
“Al. I. Cuza” University Iași, Romania [email protected].
4th Global Forum on Urban Resilience & Adaptation Bonn, Germany 31 May – 2 June 2013
The urban chore and the surrounding territory (rural and urban) that is directly influenced by it.
I. GENERAL CONSIDERATIONS
Partially synonyms Metropolitan districts
Bassin d’emploi
Chore based statistical areas Metropolitan statistical areas
Larger Urban Zones Functional urban areas
Urban and peri-urban areas
I.1. MAIN CONCEPTS
Resilience
sometimes seen as a metaphor (Pendall et al., 2008) or a general framework (Folke, 2006; Ahern, 2011), it should also be a tool for integrated planning of complex spatial systems such as cities and their polarized areas
Spatial resilience
refers to the relation between spatial variation of certain relevant variables inside and outside the system of interest and the resilience of that system across multiple spatial and temporal scales (Cumming, 2011)
Spatial resilience capacity
Theoretical functional urban areas
(metropolitan areas – in broad sense)
the differentiated and discriminatory competence of territories to respond, recover, cope, adapt and even develop when facing an unexpected, sudden perturbation or stressor.
Metropolitan regions
Resilience capacity
not focused on a certain disaster, but on the general ability to resist shocks as “some (…) [units] are structurally more prepared than others, and have greater capacity to bounce back in the wake of a stress” (Kathryn Foster, Dir., UB Regional Institute).
Hypothesis
RESILIENCE CAPACITY OF (ROMANIAN) FUNCTIONAL URBAN AREAS
OF WHOM?
TO WHAT?
HOW?
I.2. FRAMEWORK
A harmonious relation between the city and the polarized territory reduces spatial disparities and increases resilience capacity.
O1 – To test an integrated spatial resilience capacity index (SRCI) applicable to Romanian realities by adapting the existing methodologies
II. OBJECTIVES AND METHODOLOGY II.1. OBJECTIVES
O2 – To assess the spatial similarities and the disparities at different scales in order to better understand both the capacity of studied units to adapt and their ability to become poles of regional stability and development
(Source: Google Earth, 2013) Bucharest city functional area Iași city functional area
II. OBJECTIVES AND METHODOLOGY
II.2. METHODOLOGY
A. Delimitation of study areas:
>50000 inhabitants (at least once in their recent history) + spatial equity principle;
a road distance of max. 20 km (from the edge of the chore-city) allowing close socio-economic relations (commuting, daily services, ex-urban activities of the city).
B. Index construction
12 indicators (aggregated from local level to “metropolitan” level) normalized by using Min-Max rescaling scheme to create a homogenous dataset;
Principal component analysis for weighting the indicators and grouping them in three categories; some initial indicators (environmental) eliminated (no relevance for the model as hardly correlated to any other indicator);
Final Z Scores of the three aggregated indicators (for each category) and of the final index -spatial resilience capacity index (SRCI). A correlation matrix was obtained in order to study their relation;
Mapping the SRCI in order to compare:
• functional urban areas (metropolitan areas);
• metropolitan areas and non-metropolitan areas;
• urban metropolitan areas/rural metropolitan areas/urban non-metropolitan areas/rural non-metropolitan areas.
• (official) voluntary associations/partnerships • (theoretical) cities’ functional area
METROPOLITAN AREAS
II. OBJECTIVES AND METHODOLOGY
II.2. METHODOLOGY
A. Delimitation of study areas:
>50000 inhabitants (at least once in their recent history) + spatial equity principle;
a road distance of max. 20 km (from the edge of the chore-city) allowing close socio-economic relations (commuting, daily services, ex-urban activities of the city).
B. Index construction
12 indicators (aggregated from local level to “metropolitan” level) normalized by using Min-Max rescaling scheme to create a homogenous dataset;
Principal component analysis for weighting the indicators and grouping them in three categories; some initial indicators (environmental) eliminated (no relevance for the model as hardly correlated to any other indicator);
Final Z Scores of the three aggregated indicators (for each category) and of the final index -spatial resilience capacity index (SRCI). A correlation matrix was obtained in order to study their relation;
Mapping the SRCI in order to compare:
• functional urban areas (metropolitan areas);
• metropolitan areas and non-metropolitan areas;
• urban metropolitan areas/rural metropolitan areas/urban non-metropolitan areas/rural non-metropolitan areas.
MEASURING RESILIENCE. FROM INDICATORS TO INDEX II.2.B. Index construction
(Bănică, Muntele, 2013)
II. OBJECTIVES AND METHODOLOGY
II.2. METHODOLOGY
A. Delimitation of study areas:
>50000 inhabitants (at least once in their recent history) + spatial equity principle;
a road distance of max. 20 km (from the edge of the chore-city) allowing close socio-economic relations (commuting, daily services, ex-urban activities of the city).
B. Index construction
12 indicators (aggregated from local level to “metropolitan” level) normalized by using Min-Max rescaling scheme to create a homogenous dataset;
Principal component analysis for weighting the indicators and grouping them in three categories; some initial indicators (environmental) eliminated (no relevance for the model as hardly correlated to any other indicator);
Final Z Scores of the three aggregated indicators (for each category) and of the final index - spatial resilience capacity index (SRCI). A correlation matrix was obtained in order to study their relation;
Mapping the SRCI in order to compare:
• functional urban areas (metropolitan areas);
• metropolitan areas and non-metropolitan areas;
• urban metropolitan areas/rural metropolitan areas/urban non-metropolitan areas/rural non-metropolitan areas.
II.2.B. Index construction SPATIAL RESILIENCE CAPACITY INDEX
(Bănică, Muntele, 2013)
II. OBJECTIVES AND METHODOLOGY
II.2. METHODOLOGY
A. Delimitation of study areas:
>50000 inhabitants (at least once in their recent history) + spatial equity principle;
a road distance of max. 20 km (from the edge of the chore-city) allowing close socio-economic relations (commuting, daily services, ex-urban activities of the city).
B. Index construction
12 indicators (aggregated from local level to “metropolitan” level) normalized by using Min-Max rescaling scheme to create a homogenous dataset;
Principal component analysis for weighting the indicators and grouping them in three categories; some initial indicators (environmental) eliminated (no relevance for the model as hardly correlated to any other indicator);
Final Z Scores of the three aggregated indicators (for each category) and of the final index - spatial resilience capacity index (SRCI). A correlation matrix was obtained in order to study their relation;
Mapping the SRCI in order to compare:
• functional urban areas (metropolitan areas);
• metropolitan areas and non-metropolitan areas;
• urban metropolitan areas/rural metropolitan areas/urban non-metropolitan areas/rural non-metropolitan areas.
II. OBJECTIVES AND METHODOLOGY
II.2. METHODOLOGY
A. Delimitation of study areas:
>50000 inhabitants (at least once in their recent history) + spatial equity principle;
a road distance of max. 20 km (from the edge of the chore-city) allowing close socio-economic relations (commuting, daily services, ex-urban activities of the city).
B. Index construction
12 indicators (aggregated from local level to “metropolitan” level) normalized by using Min-Max rescaling scheme to create a homogenous dataset;
Principal component analysis for weighting the indicators and grouping them in three categories; some initial indicators (environmental) eliminated (no relevance for the model as hardly correlated to any other indicator);
Final Z Scores of the three aggregated indicators (for each category) and of the final index - spatial resilience capacity index (SRCI). A correlation matrix was obtained in order to study their relation;
Mapping the SRCI in order to compare:
• functional urban areas (metropolitan areas);
• metropolitan areas and non-metropolitan areas;
• urban metropolitan areas/rural metropolitan areas/urban non-metropolitan areas/rural non-metropolitan areas.
III. RESULTS SPATIAL RESILIENCE CAPACITY INDEX (SRCI). URBAN FUNCTIONAL AREAS
SPATIAL RESILIENCE CAPACITY INDEX (SRCI). METROPOLITAN AND NON-METROPOLITAN AREAS
III. RESULTS
III. RESULTS SRCI. METROPOLITAN - NON-METROPOLITAN, URBAN – RURAL AREAS
IV. CONCLUSIONS
SRCI - an adaptation of RCI to Romanian realities - spatially integrates the main urban poles to the surrounding area (hinterland) by taking into account the local, regional and national processes and outcomes that enforce or diminish resilience;
a peripheral country whose segregated territory shows a clear western orientation, but also the lack of coherent regional strategies which decreases the overall resilience capacity;
needed integration of resilience within spatial planning policies taking into account the context at local (urban-rural systems) and regional scale (relations between cities, fractures or complementarily between metropolitan and non-metropolitan areas);
metropolitan areas that became regional development poles benefit from investments, innovation, diversified economy, finances, high skilled human resources, infrastructure etc. and adapt easier to present globalized challenges;
the direct influence of a city is not a guarantee for a clean environment, a sound community, a healthy economic development or a high resilience capacity;
a high resilience capacity does not mean that an urban region/metropolitan area will successfully manage any crises it faces, but it is a premise that it might. Future developments the reiteration of SRCI: revising the 12 indicators, introducing others:
a better integration of indicators capturing environmental or geographic factors and governance is needed in order to better cover these dimensions of spatial resilience;
the assessment of long term regional trends in resilience capacity of urban functional areas.
IV. CONCLUSIONS
the direct influence of a city is not a guarantee for a clean environment, a sound community, a healthy economic development or a high resilience capacity;
a high resilience capacity does not mean that an urban region/metropolitan area will successfully manage any crises it faces, but it is a premise that it might. Future developments the reiteration of SRCI: revising the 12 indicators, introducing others:
a better integration of indicators capturing environmental or geographic factors and governance is needed in order to better cover these dimensions of spatial resilience;
the assessment of long term regional trends in resilience capacity of urban functional areas.
IV. CONCLUSIONS