O Final definition and delineation of rural areas in Central

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3CE335P4 EURUFU

O 3.2.2 Final definition and delineation of rural areas in central Europe

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3CE335P4 – EURUFU

O 3.2.2 Final definition and delineation of rural areas in Central Europe

Work package

3 – Identifying Rural Potentials

Action

3.2 – Evaluation and exchange of experience

Author

PP12 – Office for National Economic Planning (ONEP)

Version

Final, June 2012

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

3CE335P4 EURUFU

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Index 1 EXISTING DEFINITIONS ..................................................................................................... 3 1.1 International definitions ................................................................................................................ 3 1.1.1 OECD Regional Typology .............................................................................................................. 3 1.1.2 OECD Extended Regional Typology ............................................................................................ 4 1.1.3 A revised urban-rural typology by Eurostat.................................................................................. 5 1.1.4 EDORA Cube ................................................................................................................................... 7 1.1.5 ESPON Typology Compilation...................................................................................................... 9

1.2 National definitions ...................................................................................................................... 10 1.2.1 Austria ...............................................................................................................................................10 1.2.2 Czech Republic ................................................................................................................................11 1.2.3 Germany ...........................................................................................................................................12 1.2.4 Hungary – National Spatial Development Concept ..................................................................13 1.2.5 Hungary – New Hungary Rural Development Programme ....................................................14 1.2.6 Italy ....................................................................................................................................................15 1.2.7 Poland ...............................................................................................................................................15 1.2.8 Slovakia .............................................................................................................................................16 1.2.9 Slovenia .............................................................................................................................................17

2 EURUFU DEFINITION OF RURAL ................................................................................... 19 2.1 The principles and approach ...................................................................................................... 19 2.1.1 The issue of territorial levels .........................................................................................................19

2.2 The proposed methodology in details ....................................................................................... 22 2.2.1 The schematic model of the proposed EURUFU methodology ............................................23

2.3 The preliminary results of the methodology ............................................................................ 24 2.3.1 The fulfilment of the criteria .........................................................................................................24 2.3.1.1 Land Use.............................................................................................................................................. 24 2.3.1.2 Accessibility ......................................................................................................................................... 26 2.3.1.3 Importance of Primary sector .......................................................................................................... 27

2.3.2 The EURUFU definition of Central European rural areas ......................................................29

3 CATEGORISATION – SUBTYPES OF CENTRAL EUROPEAN RURAL REGIONS ...................... 30 3.1 Simple categorisations by single indicators ............................................................................... 30 3.1.1 Indicators of ageing ........................................................................................................................30 3.1.2 Migration balance ............................................................................................................................32 3.1.3 Land use characteristics..................................................................................................................33 3.1.4 Economic differences.....................................................................................................................35 This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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3.1.5 Settlement structure ........................................................................................................................36 3.1.6 Ethnic minorities .............................................................................................................................37

3.2 Complex categorisations by combining different indicators.................................................. 38 3.2.1 Two dimensional typology ............................................................................................................38 3.2.2 Three dimensional typology ..........................................................................................................39 3.2.3 Dimension reduction – factor analyses .......................................................................................40 3.2.3.1 About the method in short .............................................................................................................. 40 3.2.3.2 Ageing factor ...................................................................................................................................... 40 3.2.3.3 Land use factor ................................................................................................................................... 41

3.2.4 K-means clustering .........................................................................................................................42 3.2.4.1 About the method in short .............................................................................................................. 42 3.2.4.2 Input indicators .................................................................................................................................. 42 3.2.4.3 Results according to different number of clusters ....................................................................... 43 3.2.4.4 EURUFU typology of rural regions ............................................................................................... 47

4 REFERENCES .............................................................................................................. 49 5 ANNEXES ..................................................................................................................... 51

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Final definition and delineation of rural areas in central Europe Elaborated by Office for National Economic Planning (ONEP), Hungary Department of Strategic and Spatial Planning and Evaluation, Unit for International Territorial Cooperation and Urban Strategy

Budapest, 29 June 2012 Contributed by Dr. Márton Péti (chief planner), Gábor Kígyóssy (deputy head of department), Bence Mészáros (planner-analyst)

1 EXISTING DEFINITIONS 1.1 International definitions 1.1.1 OECD Regional Typology What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) 

Regions at Territorial Level 3 (TL3) and Non-Official Grids (NOGs) ≈ equivalent to NUTS3 in Europe;



Local unites ≈ equivalent to LAU2 in Europe

What basic data or information is/are needed to distinguish rural from non-rural areas? 

Number of permanent residents in local unites (≈LAU2) (capita);



The size of the local unites (≈LAU2) (km2);



List of local unites of the TL3 regions (classification of territorial levels)

What is the threshold value that classifies an area as rural? A region is classified as „Predominantly rural‟ if the share of population living in rural local units* (≈LAU2) is higher than 50% and the region does not contain an urban centre of more than 200 000 inhabitants representing at least 25% of the regional population. *A local unites is classified as rural if its population density is below 150 inhabitants per square kilometre.

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1.1.1 OECD Regional Typology Why is this definition important or interesting? It is used by the OECD in its analytical work (see, for example, the series OECD Regions at a Glance), as well as in analysis carried out by other institutions, such as National Statistical Offices and the European Commission. Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?) There are no subdivisions of „Predominantly rural‟ areas, however, in the OECD regional typology there is another category, called „Intermediate‟, which may be considered as rural. “Researchers with a rural focus sometimes combine predominantly rural and intermediate and call them rural regions, in part because the OECD used the term „significantly rural‟ before they replaced it with „intermediate‟ in 1997” (Eurostat 2010, p. 245.). By definition, a region is classified as „Intermediate‟, if the share of population living in rural local units is between 15% and 50%, and the region does not contain an urban centre of more than 500 000 inhabitants representing at least 25% of the regional population. (A region is also classified as „Intermediate‟, if although the share of population living in rural local units is higher than 50%, but the region contains an urban centre of more than 200 000 inhabitants representing at least 25% of the regional population.) In any other cases the region is classified as „Predominantly Urban‟. What basic data or information is/are needed to distinguish subdivisions of rural areas? No additional data or information needed. What is/are the source(s) of information (with link(s) if it is available)? OECD (2010): „REGIONAL TYPOLOGY‟. Directorate for Public Governance and Territorial Development. 22 February 2010 (http://www.oecd.org/dataoecd/35/62/42392595.pdf)

1.1.2 OECD Extended Regional Typology The Extended Typology is based on the original OECD Regional Typology. Hence, the information given there is valid for this extended typology as well, which only further classifies intermediate and predominantly rural regions into „remote‟ or „close to a populated centre‟. What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) See „OECD Regional Typology‟. What basic data or information is/are needed to distinguish rural from non-rural areas? See „OECD Regional Typology‟.

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1.1.2 OECD Extended Regional Typology What is the threshold value that classifies an area as rural? See „OECD Regional Typology‟. Why is this definition important or interesting? The extended typology is used to compare the dynamics of population and labour markets. Remote rural regions show a stronger decline in population and a faster ageing process than rural regions close to a city. The remoteness of rural regions is in fact a significant factor explaining regional outflows of working age population, confirming that this extended typology captures the economic distance from market and services. Remote rural regions appear economically more fragile. Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?) 

„Predominantly Rural Remote‟ (PRR): at least 50% of the regional population needs at least 45 minutes of driving time to reach a populated centre with at least 50 000 inhabitants;



„Predominantly Rural Close to a city‟ (PRC): less than 50% of the regional population needs at least 45 minutes of driving time to reach a populated centre with at least 50 000 inhabitants

What basic data or information is/are needed to distinguish subdivisions of rural areas?    

A map containing the distribution of the population; A road network; A map containing populated centres with at least 50 000 inhabitants; The analysis can be further refined by considering some additional factors that affect the driving time. This implies the use of a Digital Elevation Model (DEM) and an Urban Areas map.

What is/are the source(s) of information (with link(s) if it is available)? 

Brezzi, M. – Dijkstra, L. – Ruiz, V. (2011): „OECD Extended Regional Typology: The Economic Performance of Remote Rural Regions‟, OECD Regional Development Working Papers, 2011/06, OECD Publishing.

(http://dx.doi.org/10.1787/5kg6z83tw7f4-enOECD)



Dijkstra, L. – Poelman, H. (2008): “Remote Rural Regions – How proximity to a city influences the performance of rural regions”. Regional Focus – A series of short papers on regional research and indicators produced by the Directorate-General for Regional Policy. n° 01/2008. (http://ec.europa.eu/regional_policy/sources/docgener/focus/2008_01_rural.pdf)

1.1.3 A revised urban-rural typology by Eurostat The revised typology introduced by Eurostat in 2010 is based on the OECD Regional Typology. What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) NUTS 3 regions

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1.1.3 A revised urban-rural typology by Eurostat What basic data or information is/are needed to distinguish rural from non-rural areas? Population disaggregation (1 km²) grid based on LAU2 population and Corine land cover (detailed methodology can be found on the website of the European Environment Agency: http://www.eea.europa.eu/data-and-maps/data/population-density-disaggregated-with-corine-land-cover-2000-1) What is the threshold value that classifies an area as rural? A NUTS 3 region is classified as „Predominantly rural‟ if the share of population living in „rural areas‟(*) is higher than 50% and the region does not contain an urban centre of more than 200 000 inhabitants representing at least 25% of the regional population.  The methodology combines NUTS 3 regions smaller than 500 km2 with their neighbouring NUTS 3 regions. These groupings are not used for any other purpose and are dissolved as soon as the classification has been done. As a result, the outcome is a classification for each individual NUTS 3 region. (*)The population living in „rural areas‟ is the population living outside the „urban areas‟. The urban areas identified through the method described below:  a population density threshold (300 inhabitants per km²) applied to grid cells of 1 km²;  a minimum size threshold (5 000 inhabitants) applied to grouped grid cells above the density threshold. To determine the population size, the grid cells are grouped based on contiguity (including the diagonals). For instance, if the central square is above the density threshold, it will be grouped with each of the other surrounding eight cells that exceed the density threshold. Why is this definition important or interesting? The new typology remedy two shortcomings of the OECD classification:  The first distortion is due to the large variation in the area of local administrative units level 2 (LAU2).  The second distortion is due to the large variation in the surface area of NUTS 3 regions and the practice in some countries to separate a (small) city centre from the surrounding region (e.g. in Germany). The aim of this new typology is to provide a consistent basis for the description of predominantly rural, intermediate and predominantly urban regions in all Commission communications, reports and publications. Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?) The two other categories besides „predominantly rural‟ are the same as in the OECD Regional Typology: „intermediate‟ and „predominantly urban‟. The only difference is that the threshold distinguishing predominantly urban from intermediate has been adjusted from 15 % to 20 %, in order to not differ too much from the original OECD classification applied to NUTS 3 regions. What basic data or information is/are needed to distinguish subdivisions of rural areas? No additional data is needed.

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1.1.3 A revised urban-rural typology by Eurostat What is/are the source(s) of information (with link(s) if it is available)? 

Eurostat (2010): „A revised urban-rural typology‟. IN: „Eurostat regional yearbook 2010‟. pp. 240-259.

(http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-HA-10-001-15/EN/KS-HA-10-001-15-EN.PDF)



European Environment Agency (http://www.eea.europa.eu/data-and-maps/data/population-density-disaggregated-with-corine-land-cover-2000-1)

1.1.4 EDORA Cube The EDORA typologies are implemented at NUTS 3, and (in terms of the OECD classification) cover all Intermediate and Predominantly Rural regions. What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) See „OECD Regional Typology‟. What basic data or information is/are needed to distinguish rural from non-rural areas? See „OECD Regional Typology‟. What is the threshold value that classifies an area as rural? 

See „OECD Regional Typology‟.

Why is this definition important or interesting? Instead of a single typology the EDORA researchers propose an “analysis framework” in the form of three typologies reflecting three important dimensions of differentiation among non-urban regions. Unlike most rural typologies the EDORA cube takes us beyond the issue of rurality, and into the realms of rural economic structure and performance. Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?) Typology (dimension) 1: „D-P Typology‟ (Rurality/accessibility) For methodological details see “OECD Extended Regional Typology”  Intermediate Accessible  Intermediate Remote  Predominantly Rural Accessible  Predominantly Rural Remote

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1.1.4 EDORA Cube Typology (dimension) 2: „Structural Types‟ (Degree of economic restructuring)  Agrarian  all three indicators of the relative importance of agriculture (% employment in the primary sector, % of GVA from primary sector, and AWU as a percentage of total employment) exceeded the EU27 non-urban region mean  Consumption Countryside  at least one indicator in two out of three thematic groups exceeded the EU27 average. The three groups of indicators relate to capacity for and intensity of tourism activity, access to natural areas, and the importance of peri-productivist farming styles.  Diversified (Strong Secondary Sector)  identified (from the residual after the first two were defined) as those in which GVA from secondary sector activities exceeded that from private services.  Diversified (Strong Market Services)  the residual after the first three had been defined. In other words they do not have a strong dependence upon agriculture, little evidence of strong “Consumption Countryside” activities, and a larger share of GVA from market services than from the secondary sector. Typology (dimension) 3: „Socio-economic performance‟ (accumulation or depletion) The first step in the classification is to create a synthetic performance indicator, an unweighted average of normalised “Z” scores of five indicators. These are net migration rate, GDP per capita, annual percentage changes in GDP and employment, and unemployment rate. This continuous variable is then presented in four categories, defined by the EU27 average, and +/- 0.5 Standard Deviations.  Depleting  Below Average  Above Average  Accumulating What basic data or information is/are needed to distinguish subdivisions of rural areas? 27 raw data variables (predominantly from the Eurostat REGIO database) which were combined in various way to generate 17 ratio indicators. All the indicators were converted to normalised (Z) scores, using the non-urban (NUTS 3) mean and standard deviation. All the raw data variables and the derived ratio indicators are available in the EDORA Core Database. 13 indicators were used to define the four Structural types. and 5 to generate a synthetic regional performance indicator. What is/are the source(s) of information (with link(s) if it is available)? ESPON (2011): „European Development Opportunities for Rural Areas‟. Applied Research 2013/1/2. Final Report, Parts A, B and C. August 2011. pp. 15-21. Funded by the ESPON 2013 Programme (http://www.espon.eu/export/sites/default/Documents/Projects/AppliedResearch/EDORA/EDORA_Final_Report_Parts_A_and_B.pdf)

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1.1.5 ESPON Typology Compilation The final report of ESPON Typology Compilation project was not available at the time of this study was being written, thus the definition and typology below is just a preliminary version. What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) NUTS 3 (in a very limited number of cases, NUTS 2 due to lack of data) What basic data or information is/are needed to distinguish rural from non-rural areas?  

Definition of urban areas at LAU 2 based on Urban Audit and GISCO STEU and checked against the EEA Degree of Urbanisation. Population number of the selected cities and NUTS 3 regions.

What is the threshold value that classifies an area as rural? As a starting point it is envisage to include as rural areas primarily only such regions that are not classified as urban. If the population of the selected large cities is less than one third or a quarter of the population of their surrounding NUTS 3 region, they should be considered as rural region. Regions containing more than one of these cities would be excluded from this comparison and automatically considered being urban areas. Why is this definition important or interesting? The purpose of the ESPON Typology Compilation project is to provide a compilation of existing territorial typologies and to propose a set of eight territorial typologies (amongst them one for rural areas) which can be used throughout the ESPON 2013 Programme. The proposals for the typologies bring together elements form the various typologies reviewed in the frame of the project and compose a coherent set of eight homogenous ESPON typologies. Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?) 1. 2. 3. 4.

rural areas close to urban centre without agrarian profile rural areas close to urban centres with agrarian profile remote rural area without agrarian profile remote rural area with agrarian profile

What basic data or information is/are needed to distinguish subdivisions of rural areas? For the differentiation of rural regions two dimensions will be used: 1) the relative position of the rural region vis-à-vis larger urban centres (e.g. areas within 45 minutes reach from urban centres), and 2) the importance of primary production to the overall regional economy (GVA branches A-B as a share of total GVA), combined with the importance of primary production as a source of livelihood (employment in branches A-B as a share of total employment).

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1.1.5 ESPON Typology Compilation What is/are the source(s) of information (with link(s) if it is available)? ESPON (2011): „ESPON Typology Compilation‟. Scientific Platform and Tools 2013/3/022. Interim Report. Version 15/06/2009. pp. 9-19. Funded by the ESPON 2013 Programme (http://www.espon.eu/export/sites/default/Documents/Projects/ScientificPlatform/TypologyCompilation/fir-090615.pdf)

1.2 National definitions 1.2.1 Austria In general Austria applies the OECD rural-urban regional typology for the classification of regions. However, as the international OECD typology hardly addresses the problems and context of Austrian functional regions, some analyses provided more targeted typologies to the national spatial structure. What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) Municipalities (LAU 2) What basic data or information is/are needed to distinguish rural from non-rural areas? Population number of municipalities What is the threshold value that classifies an area as rural? 



Urban: Population of communes (Gemeinden) or groups of communes encompassing at least one settlement (means zusammenhängend verbautes Gebiet where houses are at most 200 metres from each other) with 2,000 inhabitants or more. Rural: All remaining communes or groups of communes.

Why is this definition important or interesting? This is the official definition of Statistic Austria. Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?)   

Rural regions with higher than average agricultural rates; Production-oriented rural regions; Rural regions of high regional significance for tourism;

What basic data or information is/are needed to distinguish subdivisions of rural areas? Detailed methodology is not available in English.

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1.2.1 Austria What is/are the source(s) of information (with link(s) if it is available)? 

Wiesinger, G. – Dax, T. (2008): „Country profiles on rural characteristics: Austria‟. BABF (Federal Institute for Less Favoured and Mountainous areas, Vienna, Austria). IN: Assessing the Impact of Rural Development Policies (RuDI) project (Work package 1: Priorities in rural development policies; Deliverable D 1.1.); Funded by the 7th Framework Programme for Research and Technology Development of the European Commission. (http://www.rudi-europe.net/uploads/media/Austria_WP1_Report.pdf)



ESPON (2003): „Urban-rural relations in Europe‟. Coordinator: Centre for Urban and Regional Studies, Helsinki University of Technology. Second interim report March 2003. p. 37. Funded by the ESPON 2006 Programme (http://www.espon.eu/export/sites/default/Documents/Projects/ESPON2006Projects/ThematicProjects/UrbanRural/2.ir_1.1.2.pdf)

1.2.2 Czech Republic What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) Municipalities (LAU 2) What basic data or information is/are needed to distinguish rural from non-rural areas? Number of permanent residents in the municipality (population level) What is the threshold value that classifies an area as rural? Less than 2 000 residents in the municipality Why is this definition important or interesting? This definition is used by Czech Statistical Office and represents the most accepted national definition in the Czech Republic. Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?) Rural areas in the Czech Republic are to be distinguished as suburban, intermediate, and remote ones. At present, an unambiguously adopted definition of the above types does not exist. The urban agglomerations and peripheral lands were defined in the past; at present, work relating to the up-dating thereof is going on. What basic data or information is/are needed to distinguish subdivisions of rural areas? It is not known.

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1.2.2 Czech Republic What is/are the source(s) of information (with link(s) if it is available)? 

Bednarikova, Z. – Maur, P (2008).: „Country profile on rural characteristics, Czech Republic‟. Research Institute of Agricultural Economics (VUZE). Prague, Czech Republic. p. 8. IN: Assessing the Impact of Rural Development Policies (RuDI) project (Work package 1: Priorities in rural development policies; Deliverable D 1.1.); Funded by the 7th Framework Programme for Research and Technology Development of the European Commission. (http://www.rudi-europe.net/uploads/media/Czech_WP1_Report_01.pdf)



RURAL DEVELOPMENT PROGRAMME OF THE CZECH REPUBLIC FOR 2007 – 2013, Working document. Prague, November 2008. Ministry of Agriculture, VÚZE Prague. p. 17. (http://eagri.cz/public/web/file/10574/RDP_November_2008.pdf)

1.2.3 Germany There is not „one‟ definition of rural areas strictly applied in Germany but there are different definitions and approaches used depending on the purpose of the categorization. Moreover, besides the national used typology, each of the federal states uses their own categorisation for rural areas for the purpose of land use planning. What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?)  

Administrative regions (Regierungsbezirke - NUTS 2) District/county (Landkreis NUTS 3)

What basic data or information is/are needed to distinguish rural from non-rural areas?   

Population number of the region (NUTS 2); Size of the region (NUTS 2) (km2); List of high level centres with more than 100 000 inhabitants

What is the threshold value that classifies an area as rural? Rural areas are defined as areas with a population density of above 150 p/km2 without a high level centre with more than 100 000 inhabitants; or a region with a population density of below 100 p/km2 with a high level centre of more than 100 000 inhabitants. Why is this definition important or interesting? This definition is one of the most commonly used rural definition in Germany created by the „Federal Office for Building and Regional Planning‟ (BRR)

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1.2.3 Germany Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?) The rural areas defined on NUTS 2 level are classified further on NUTS 3 level into two categories: „Rural districts with higher density‟ and „Rural districts with lower density‟. However, each of the three types of region („agglomeration‟, „urbanised‟ and „rural areas‟) described on NUTS2 level can contain rural districts on NUTS 3 level. The thresholds and a detailed methodology are not mentioned in the information source. What basic data or information is/are needed to distinguish subdivisions of rural areas? It is not known. What is/are the source(s) of information (with link(s) if it is available)? Schiller, S. R. (2008): „Country profiles on rural characteristics: Germany‟. IFLS (The Institute for Rural Development Research at the Johann Wolfgang Goethe University, Frankfurt/Main, Germany). IN: Assessing the Impact of Rural Development Policies (RuDI) project (Work package 1: Priorities in rural development policies; Deliverable D 1.1.); Funded by the 7th Framework Programme for Research and Technology Development of the European Commission. (http://www.rudi-europe.net/uploads/media/Germany_WP1_Report.pdf)

1.2.4 Hungary – National Spatial Development Concept What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) Micro regions (LAU 1) What basic data or information is/are needed to distinguish rural from non-rural areas? Population density of micro regions (LAU 1) What is the threshold value that classifies an area as rural? The population density of a micro-region is below 120 inhabitants/km2 Why is this definition important or interesting? This is the official definition of the Hungarian National Spatial Development Concept, 2005. Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?)  

„Rural micro-region‟: The population density of the micro-region is under 120 inhabitants/km2, and there is no urban centre in the region with a minimum 20 000 inhabitants. „Rural micro-region with an urban centre‟: The population density of the micro-region is under 120 inhabitants/km2, and there is at least one urban centre with a minimum 20 000 inhabitants

What basic data or information is/are needed to distinguish subdivisions of rural areas? Population number of municipalities (LAU 2)

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1.2.4 Hungary – National Spatial Development Concept What is/are the source(s) of information (with link(s) if it is available)? Hungarian Regional Development Office (2005): „National Spatial Development Concept of Hungary‟ Edited and abridged supplementary version of the National Spatial Development Concept, 2005. (http://www.vati.hu/static/otk/eng/nsdc2005eng.pdf)

1.2.5 Hungary – New Hungary Rural Development Programme What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) Settlements (LAU 2) What basic data or information is/are needed to distinguish rural from non-rural areas? 

Population density of settlements (LAU 2)



Number of permanent population of settlements (LAU 2)



Population number of outskirts areas of settlements



List of settlements of the Budapest agglomeration

What is the threshold value that classifies an area as rural? Settlements with population number of less than 5000 or density of population less than 100 persons/km2. The outskirt areas of non-eligible settlements – with an outskirt population above 2% of the inhabitants of the settlement – are eligible for support. Settlements of the Budapest agglomeration are not geographical target areas of measure. Why is this definition important or interesting? In the New Hungary Rural Development Programme (2007-2013) this definition is used to identify the eligible geographical areas in case of the following measures of Axis III: “Quality of life in rural areas and diversification of the rural economy”: 

“Encouragement of tourism activities”;



“Basic services for the economy and rural population”;



“Conservation and sustainable development of the rural heritage”

Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?) There are no subdivisions are known What basic data or information is/are needed to distinguish subdivisions of rural areas? There are no subdivisions are known What is/are the source(s) of information (with link(s) if it is available)? „New Hungarian Rural Development Programme (2007-2013)‟. Budapest. 19 February 2007. (http://www.fvm.gov.hu/doc/upload/200702/nhrdp_070220.pdf)

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1.2.6 Italy What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) Municipalities (LAU 2) What basic data or information is/are needed to distinguish rural from non-rural areas? Detailed methodology is not available in English. What is the threshold value that classifies an area as rural? Detailed methodology is not available in English. Why is this definition important or interesting? This is an official methodology of the National Strategic Plan of Italy for the classification of rural/urban areas, used for operational purposes related to policy, but currently being discussed with the academic world, the world of research and the Central Institute of Statistics (ISTAT) in order to consolidate it. Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?) There are 3 subtype of rural areas, which are the followings:  Intensive agriculture rural areas;  Intermediate rural areas;  Rural areas with comprehensive development problems. Detailed methodology is not available in English. What basic data or information is/are needed to distinguish subdivisions of rural areas? Detailed methodology is not available in English. What is/are the source(s) of information (with link(s) if it is available)? Bolli, M. – Tarangioli, S. – Mantino, F. (2008): „Country profiles on rural characteristics: Italy‟. INEA (National Institute of Agricultural Economics, Rome, Italy). IN: Assessing the Impact of Rural Development Policies (RuDI) project (Work package 1: Priorities in rural development policies; Deliverable D 1.1.); Funded by the 7th Framework Programme for Research and Technology Development of the European Commission. (http://www.rudi-europe.net/uploads/media/Italy_WP1_Report.pdf)

1.2.7 Poland What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) Municipalities (LAU 2)

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1.2.7 Poland What basic data or information is/are needed to distinguish rural from non-rural areas? Legal status of settlements What is the threshold value that classifies an area as rural? Rural areas are defined as those located outside the administrative boundaries of towns and cities. In justified cases, the definition of rural areas may be extended to include small urban settlements closely related to rural areas in terms of function. Why is this definition important or interesting? This is the official definition of the polish Central Statistical Office – GUS. Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?) There are no subdivisions are known What basic data or information is/are needed to distinguish subdivisions of rural areas? There are no subdivisions are known What is/are the source(s) of information (with link(s) if it is available)? Chmielewska, B. (2008): „Country profiles on rural characteristics: Poland‟. UL (Chair of Agricultural Economics, Policy and Law, Ljubljana University, Ljubljana, Slovenia). IN: Assessing the Impact of Rural Development Policies (RuDI) project (Work package 1: Priorities in rural development policies; Deliverable D 1.1.); Funded by the 7th Framework Programme for Research and Technology Development of the European Commission. (http://www.rudi-europe.net/uploads/media/Poland_WP1_Report_01.pdf)

1.2.8 Slovakia What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) Municipalities (LAU 2) What basic data or information is/are needed to distinguish rural from non-rural areas? Legal status of settlements What is the threshold value that classifies an area as rural?  

Urban: Population of a municipality declared to be a town by government decision according to its function as a centre, its urban character in building and its size of at least 5,000 inhabitants. Rural: All remaining municipalities.

Why is this definition important or interesting? This is the definition of Statistical Office of the Slovak Republic. This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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1.2.8 Slovakia Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?) There are no subdivisions are known. What basic data or information is/are needed to distinguish subdivisions of rural areas? There are no subdivisions are known. What is/are the source(s) of information (with link(s) if it is available)? ESPON (2003): „Urban-rural relations in Europe‟. Coordinator: Centre for Urban and Regional Studies, Helsinki University of Technology. Second interim report March 2003. p. 40. Funded by the ESPON 2006 Programme (http://www.espon.eu/export/sites/default/Documents/Projects/ESPON2006Projects/ThematicProjects/UrbanRural/2.ir_1.1.2.pdf)

1.2.9 Slovenia In Slovenia, there is no official typology distinguishing between urban and rural areas. Nevertheless, there have been various attempts to elaborate one. What is the territorial unit/area on which the definition of rural is based (i.e. postcode areas, community districts, communities, districts or regions)? (What is the NUTS level code of it?) Municipalities (LAU 2) What basic data or information is/are needed to distinguish rural from non-rural areas?  Population density of municipalities  Population number of municipalities  Territorial agglomeration of local units (municipalities) What is the threshold value that classifies an area as rural? The typology distinguishes three types of areas: 1. Densely populated area: a contiguous set of local areas, each of which has a density over 500 inhabitants per km2, and where the total population for the set is at least 50 000 inhabitants; 2. Intermediate area: a contiguous set of local areas, not belonging to the densely populated area, each of which has a density more than 100 inhabitants per km2, and either with a total population for the set of at least 50 000 inhabitants or adjacent to a densely populated area; 3. Thinly populated area: a contiguous set of local areas, neither belonging to a densely populated area nor to an intermediate area. „Thinly populated areas‟ are definitely considered rural. Intermediate area may be considered either rural or urban depending on the analyst‟s point of view. Why is this definition important or interesting? The Statistical Office of the Republic of Slovenia (SORS) has recently carried out this designation of rural areas This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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1.2.9 Slovenia Are there any subdivisions of rural areas relating to the degree of rurality? (What are those?) There are no subdivisions are known What basic data or information is/are needed to distinguish subdivisions of rural areas? There are no subdivisions are known What is/are the source(s) of information (with link(s) if it is available)? Juvančič, L. (2008): „Country profiles on rural characteristics: Slovenia‟. UL (Chair of Agricultural Economics, Policy and Law, Ljubljana University, Ljubljana, Slovenia). IN: Assessing the Impact of Rural Development Policies (RuDI) project (Work package 1: Priorities in rural development policies; Deliverable D 1.1.); Funded by the 7th Framework Programme for Research and Technology Development of the European Commission. (http://www.rudi-europe.net/uploads/media/Slovenia_WP1_Report_01.pdf)

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2 EURUFU DEFINITION OF RURAL 2.1 The principles and approach The overview of the existing methodologies proved that an omnipotent, official definition of rural areas does not exist. According to different points of view, different purposes, different territorial scope, various definitions can be used. Even in Central Europe, in such a small region, different definitions are used by the member countries. The economical-demographical-cultural situation differs from country to country, however, common characteristics of rural areas can be defined within the territorial scope of Central Europe. There are two main principles which have been set at the beginning of the elaboration of the methodology: 1) We would like to give a definition in the context of Central Europe. We are not interested in the national relations. (E.g. a given region could be defined as rural within the borders of its own country, while it may be defined as an urbanized region within Central Europe). Therefore we will always try to compare the regional data to the average values of whole Central Europe. 2) We do not want to define rural areas as „areas which are not urban‟. We would like to concentrate on a more focused rural definition instead giving a huge residual „matrix‟. The OECD rural definition is the most commonly used methodology in international context. Therefore we corporate it into our model as a starting point. However, to find the most suitable definition for Central Europe we need to make further adjustments. This should be done along two dimensions: 1) Incorporate some important criteria into the model: (a) Land Cover and Land Use characteristics; (b) Accessibility; (c) The importance of primary sector. 2) Apply the definition in different territorial levels (NUTS 3 and LAU 1) country to country.

2.1.1 The issue of territorial levels The table below gives an overview of the differences between the average sizes of territorial levels in each Central European country. It can be seen quite clearly that there are two groups which are different according to the average size of their NUTS 3 regions. 1) NUTS 3 level is appropriate in: Germany, Slovenia, Austria and Italy 2) NUTS 3 level is too large in: Slovakia, Czech Republic, Poland and Hungary In the latter case LAU 1 level is proposed to be used.

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1. Table: The average sizes of territorial levels in the Central European countries

NUTS 3

LAU 1

Average Average Number of Average Number of Average population population regions size (km2) regions size (km2) (person) (person)

CENTRAL EUROPE

444

2 192

319 349

3 667

265

38 667

243

884

163 109

2 899*

74

13 672

Slovenia

12

1 689

170 849

58

350

35 348

Austria

35

2 410

239 294

LAU 1 level is not existed

Italy (CEU)

46

2 614

599 708

LAU 1 level is not existed

Hungary

20

4 651

499 286

175

532

57 061

Poland

66

4 738

578 788

379

825

100 792

Czech Republic

14

5 633

752 341

77

1 024

136 789

8

6 130

678 116

79

621

68 670

MEMBER COUNTRIES

Germany (CEU)

Slovakia

* The number of LAU 1 unites in the Central European part of Germany would be just 940 if LAU 1 unites representing only one city were not counted In case only NUTS 3 level is used the difference between the highest and the lowest value is more than sevenfold, whereas the proposed combination of different territorial levels would reduce this gap to less than fivefold. Therefore, in case of Hungary, Poland, Czech Republic and Slovakia LAU 1 level will be used instead of NUTS 3. (km2)

Average size of territorial unites

NUTS 3

6000

NUTS 3

5000

NUTS 3

NUTS 3

4000

3000

NUTS 3 NUTS 3

2000

1000

NUTS 3

LAU 1

NUTS 3

LAU 1 LAU 1

LAU 1 LAU 1 LAU 1 0

DE

SI

AT

IT

HU

PL

CZ

SK

1. Figure: The differences between the average sizes of territorial levels in the Central European countries

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The following maps also emphasize the role and importance of territorial levels in the definition of rural areas. It shows that most of the NUTS 3 regions are likely to consist of various types LAU 1 regions.

2. Map: Adjusted OECD typology

1. Map: OECD original typology

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2.2 The proposed methodology in details As a first step the original OECD definition was revised and threshold values for urban centres were reduced and adapted to the characteristics of the Central European settlement system. According to the modified thresholds a region is classified as 





„Predominantly rural‟ if the share of population living in rural local units (≈LAU2) is higher than 50% and the region does not contain an urban centre of more than 200 000 100 000 inhabitants representing at least 25% of the regional population; „Intermediate‟ if the share of population living in rural local units (≈LAU2) is between 15-50% and the region does not contain an urban centre of more than 500 000 200 000 inhabitants representing at least 25% of the regional population. „Predominantly Urban‟ if the share of population living in rural local units (≈LAU2) is below 15% or the share of population living in rural local units (≈LAU2) is between 15-50% and the region contains an urban centre of more than 500 000 200 000 inhabitants representing at least 25% of the regional population.

The second step was to define the Predominantly Urban regions which were excluded from the further examination. In the last phase of the definition the fulfilment of the predefined criteria was examined. At least two criteria were needed to be fulfilled in order to consider a region as rural. The criteria are as follows: 1) Land use characteristics (For more information on the creation of Land Use categories see Annex) o The share of “Built-up” and “Industrial/commercial” Land Use coverage of the region is below the CEU average OR o The share of “Agricultural” Land Use coverage of the region is above the CEU average (At least one of these two „sub-criterions‟ must be fulfilled) 2) Accessibility is measured with the length of motorways and primary roads per km2. If the value were below the CEU average regions are considered as remote. 3) The role of primary sector o The share of employed people in Primary Sector in the region is above the CEU average OR o The share of Gross Value Added in Primary Sector in the region is above the CEU average (At least one of these two „sub-criterions‟ must be fulfilled)

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2.2.1 The schematic model of the proposed EURUFU methodology

REVISED OECD METHODOLOGY

How much is the population density of Local Rural Areas (LAU 2)?

below 150 persons/km2

above 150 persons/km2

RURAL LAU 2

URBAN LAU 2

How many percent of the population of the region* are living in Rural LAU 2? (* Territorial levels are different by countries: NUTS 3: AT, DE, IT, SI; LAU 1: CZ, HU, PL, SK) > 50 %

15 – 50 %

Is there an urban centre in the region with more than 100 000 inhabitants, which is representing more than 25 % of the regional population? NO

< 15 %

YES

YES

NO

Predominantly Urban

Intermediate

Is the share of “Built-up” and “Industrial/commercial” Land Use coverage of the region below the CEU average?

Above

Is the share of “Agricultural” Land Use coverage of the region above the CEU average?

Below

Above

Below

Is the region „remote”?

Is the region „remote”?

(Is the length of motorways and primary roads per km2 below the CEU average?)

(Is the length of motorways and primary roads per km2 below the CEU average?)

Remote

STEP 2

Is there an urban centre in the region with more than 200 000 inhabitants, which is representing more than 25 % of the regional population?

Predominantly Rural

EURUFU EXTENSION

STEP 1

Accessible

Remote

STEP 3

Accessible

URBAN

Is the share of employed people in Primary Sector in the NUTS3 regions above the CEU average?

Below

Above

Above

Is the share of Gross Value Added in Primary Sector in the NUTS3 regions above the CEU average?

RURAL REGIONS

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Below

URBAN

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2.3 The preliminary results of the methodology 2.3.1 The fulfilment of the criteria 2.3.1.1

Land Use

3. Map: Regions according to the proportion of “Built-up” and “Industrial/commercial” Land Use categories This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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4. Map: Regions according to the proportion of “Agricultural” Land Use category

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Accessibility

5. Map: Regions according to the density of main roads This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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Importance of Primary sector

6. Map: Regions according to the share of agricultural employment This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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7. Map: Regions according to the share of agricultural GVA

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2.3.2 The EURUFU definition of Central European rural areas

8. Map: The delineation of rural areas in Central Europe This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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3 CATEGORISATION – SUBTYPES OF CENTRAL EUROPEAN RURAL REGIONS 3.1 Simple categorisations by single indicators 3.1.1 Indicators of ageing

9. Map: Change in the proportion of elderly population (> 65 year old) between 2006 and 2010

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10. Map: Proportion of young generation (0-14 years) compared to elderly population (> 65 year old), 2010

(CEU average: 80%; Rural CEU average: 94%)

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3.1.2 Migration balance

11. Map: Net migration balance between 2006 and 2010

(CEU average: +1,2%; Rural CEU average: +0,3%)

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3.1.3 Land use characteristics

12. Map: Proportion of natural vegetation land cover (%), based on Corin Land cover 2006

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13. Map: Proportion of agricultural land use (%), based on Corin Land cover 2006

(CEU average: 55,6%; Rural CEU average: 57,8%)

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3.1.4 Economic differences

14. Map: GDP (PPS/inhabitant), 2009 (only available on NUTS3)

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3.1.5 Settlement structure

15. Map: Proportion of small villages (LAU2 with less than 500 inhabitant) in the settlement structure

(CEU average: 26%; Rural CEU average: 32%) This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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3.1.6 Ethnic minorities

16. Map: Proportion of Roma population (%), 2001

(CEU average: 1,2%; Rural CEU average: 1,5%)

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3.2 Complex categorisations by combining different indicators 3.2.1 Two dimensional typology Demographic typology

change

- Net migration: Net migration balance between 2006 and 2010 is below the rural CEU average + Net migration: Net migration balance between 2006 and 2010 is above the rural CEU average - Age structure: proportion of young generation (0-14 years) compared to elderly population ( > 65 year old) is below the rural CEU average + Age structure: proportion of young generation (0-14 years) compared to elderly population ( > 65 year old) is above the rural CEU average

17. Map: Typology of demographic change in Central European rural regions

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3.2.2 Three dimensional typology 3 dimensional typology: 1.) L / H GDP: GDP (PPS/inhabitant) below (L) or above (H) the rural CEU average 2.) Ag / Nt: Dominant land use type is more agricultural (Ag) or more natural vegetation (Nt) 3.) Dc / n Dc: Based on the migration and ageing indicators, the given region is highly threatened by demographic change (Dc) or not (n Dc)

18. Map: Typology of demographic change in Central European rural regions

The Dominant land use type was defined by examining the deviation of the regions from the CEU rural average of the following two variables:  

Proportion of agricultural land use (%), based on Corin Land cover 2006 Proportion of natural vegetation land cover (%), based on Corin Land cover 2006

If the deviation was higher in case of agricultural land use than in case of natural vegetation land cover, the relevant region defined as “more agricultural (Ag) and vice versa. The level of demographic change was defined by examining the deviation of the regions from the CEU rural average of the following two variables:   

Change in the proportion of elderly population ( > 65 year old) between 2006 and 2010 Proportion of young generation (0-14 years) compared to elderly population ( > 65 year old), 2010 Net migration balance between 2006 and 2010

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The relevant region is needed to exceed the Central European rural average in case of at least two variables to be considered as a region which is highly threatened by demographic change.

3.2.3 Dimension reduction – factor analyses 3.2.3.1

About the method in short

How can we combine two variables – which show strong correlation – into a single factor? You can summarize the correlation between two variables in a scatterplot. A regression line can then be fitted that represents the "best" summary of the linear relationship between the variables. If we could define a variable that would approximate the regression line in such a plot, then that variable would capture most of the "essence" of the two items. Subjects' single scores on that new factor, represented by the regression line, could then be used in future data analyses to represent that essence of the two items. In a sense we have reduced the two variables to one factor. Note that the new factor is actually a linear combination of the two variables.

3.2.3.2

Ageing factor The following two variables were combined into a single “ageing factor”: 



Change in the proportion of elderly population ( > 65 year old) between 2006 and 2010 Proportion of young generation (0-14 years) compared to elderly population ( > 65 year old), 2010

19. Map: Ageing factor in Central European rural regions This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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Land use factor

The following two variables were combined into a single “Land use factor”:  

Proportion of agricultural land use (%), based on Corin Land cover 2006 Proportion of natural vegetation land cover (%), based on Corin Land cover 2006

20. Map: Land use factor in Central European rural regions

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3.2.4 K-means clustering 3.2.4.1

About the method in short

We deal with clustering in almost every aspect of daily life. For example, a group of diners sharing the same table in a restaurant may be regarded as a cluster of people. In food stores items of similar nature, such as different types of meat or vegetables are displayed in the same or nearby locations. There is a countless number of examples in which clustering plays an important role. Note how in this classification, the higher the level of aggregation the less similar are the members in the respective class. The term cluster analysis (first used by Tryon, 1939) encompasses a number of different algorithms and methods for grouping objects of similar kind into respective categories. A general question facing researchers in many areas of inquiry is how to organize observed data into meaningful structures, that is, to develop taxonomies. In other words cluster analysis is an exploratory data analysis tool which aims at sorting different objects into groups in a way that the degree of association between two objects is maximal if they belong to the same group and minimal otherwise. Given the above, cluster analysis can be used to discover structures in data without providing an explanation/interpretation. In other words, cluster analysis simply discovers structures in data without explaining why they exist. Suppose that you already have hypotheses concerning the number of clusters in your cases or variables. You may want to "tell" the computer to form exactly 3 clusters that are to be as distinct as possible. This is the type of research question that can be addressed by the k-means clustering algorithm. In general, the k-means method will produce exactly k different clusters of greatest possible distinction. It should be mentioned that the best number of clusters k leading to the greatest separation (distance) is not known as a priori and must be computed from the data. The program will start with k random clusters, and then move objects between those clusters with the goal to 1) minimize variability within clusters and 2) maximize variability between clusters. In other words, the similarity rules will apply maximally to the members of one cluster and minimally to members belonging to the rest of the clusters. Usually, as the result of a kmeans clustering analysis, we would examine the means for each cluster on each dimension to assess how distinct our k clusters are. Ideally, we would obtain very different means for most, if not all dimensions, used in the analysis.

3.2.4.2 

 

  

Input indicators

Ageing factor, composed from the following variables: o Change in the proportion of elderly population ( > 65 year old) between 2006 and 2010 o Ageing indicator: proportion of young generation (0-14 years) compared to elderly population ( > 65 year old), 2010 Net migration balance between 2006 and 2010 Land use factor, composed from the following variables: o Proportion of agricultural land use (%), based on Corin Land cover 2006 o Proportion of natural vegetation land cover (%), based on Corin Land cover 2006 GDP (PPS/inhabitant), 2009 (only available on NUTS3) Proportion of small villages (LAU2 with less than 500 inhabitant) in the settlement structure Proportion of Roma population (%), 2001

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Results according to different number of clusters 1) Ageing population, high GDP, small villages, more natural vegetation 2) Younger population, low GDP, significant Roma population, more agricultural land use

21. Map: Results of K=2 cluster analysis

1) Ageing population, high GDP, small villages, more natural vegetation 2) Younger population, low GDP, significant Roma population, migration loss, small villages 3) Younger population, low GDP, dominantly agricultural land use

22. Map: Results of K=3 cluster analysis This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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1) Significant migration surplus, high GDP, agricultural land use, small villages 2) Significant Roma population, younger population, low GDP, migration loss, small villages 3) Younger population, low GDP, dominantly agricultural land use 4) Ageing population, high GDP, small villages, more natural vegetation

23. Map: Results of K=4 cluster analysis

1) Significant small villages, ageing population 2) Significant Roma population, younger population, low GDP, migration loss, small villages 3) Significant migration surplus, high GDP, agricultural land use, small villages 4) Younger population, low GDP, dominantly agricultural land use 5) Ageing population, high GDP, small villages, more natural vegetation

24. Map: Results of K=5 cluster analysis This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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1) Significant migration surplus (+23 %), young age structure, high GDP, agricultural land use 2) Significant Roma population, young age structure, low GDP, migration loss, small villages 3) Significant migration surplus, high GDP, agricultural land use, small villages 4) Younger population, low GDP, dominantly agricultural land use 5) Small villages, ageing population, low GDP, Roma population, migration loss 6) Ageing population, high GDP, small villages, migration loss

25. Map: Results of K=6 cluster analysis

1) Younger population, low GDP, dominantly agricultural land use 2) Extremely high Roma population, very young age structure, strong migration loss, very low GDP, lot of small villages 3) Ageing population, high GDP, dominantly natural vegetation 4) Significant migration surplus, high GDP, agricultural land use, small villages 5) Significant Roma population, young age structure, low GDP, migration loss, small villages 6) Rapidly ageing population, small villages, migration loss , agricultural land use 7) Significant migration surplus (+23 %), young age structure, high GDP, agricultural land use

26. Map: Results of K=7 cluster analysis This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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1) Extremely high Roma population, very young age structure, strong migration loss, very low GDP, lot of small villages 2) Significant Roma population, young age structure, low GDP, migration loss, small villages 3) Rapidly ageing population, migration loss, higher GDP, agricultural land use 4) Significant migration surplus, high GDP, agricultural land use 5) Ageing population, high proportion of small villages 6) Significant migration surplus (+23 %), young age structure, high GDP, agricultural land use 7) Ageing population, high GDP, dominantly natural vegetation, migration surplus 8) Younger population, low GDP, dominantly agricultural land use 27. Map: Results of K=8 cluster analysis

1) Younger population, low GDP, dominantly agricultural land use 2) Very significant Roma population, young age structure, low GDP, migration loss, agricultural land use 3) Significant Roma population, young age structure, low GDP, migration loss, small villages 4) Significant migration surplus, high GDP, agricultural land use 5) Extremely high Roma population, very young age structure, strong migration loss, very low GDP, lot of small villages 6) Rapidly ageing population, migration loss, dominantly agricultural land use 7) Ageing population, high GDP, dominantly natural vegetation, migration surplus 8) Significant migration surplus (+23 %), young age structure, high GDP, agricultural land use 28. Map: Results of K=9 cluster analysis

9) Ageing population, high proportion of small villages

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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EURUFU typology of rural regions Legend on map

29. Map: EURUFU typology of Central European rural areas

Name

Features

1

Deprived Roma villages

Negative net migration; Natural vegetation land cover; Low GDP; High proportion of small settlements; High proportion of Roma population

2

Deprived Roma children

Young age structure; Negative net migration; Low GDP; High proportion of Roma population

3

Crisis regions

Decreasing proportion of old population; Young age structure; Negative net migration; Low GDP; High proportion of small settlements; Extremely high proportion of Roma population

4

Poor polish youth

Young age structure; Low GDP; Lack of small settlements

5

Ageing small villages

Growing proportion of old population; High proportion of small settlements

6

Poor farmers

Dominant agricultural land use; low GDP; Lack of small settlements

7

Migration magnet

Decreasing proportion of old population; Young age structure; Extremely positive net migration; Agricultural land use

8

Wealthy elderly green Alpine

Old age structure; Positive net migration; Dominant natural vegetation land cover; High GDP; Low proportion of small settlements

9

Unattractive serious ageing

Growing proportion of old population; Old age structure; Negative net migration; High GDP; Low proportion of small settlements

10

Wealthy suburban

Positive net migration; Agricultural land use; High GDP

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF

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O 3.2.2 Final definition and delineation of rural areas in central Europe

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2. Table: Average values of the defined clusters

Legend on map Type 1 Type 2 Type 3 Type 4 Type 5 Type 6 Type 7 Type 8 Type 9 Type 10 CEU rural average

Change of old (65-x) population proportion (%), 2006-2010

Proportion Age structure (%) Net migration Agricultural Natural vegetation GDP of small (0-14 yo./65-x yo.), (% of 2006), land use (%), land cover (%), (pps/inh.) (

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