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Regional and urban Policy Combining geography and statistics for an improved analysis of urban phenomena Recent experiences in European Regional and Urban.

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Presentation on theme: "Regional and urban Policy Combining geography and statistics for an improved analysis of urban phenomena Recent experiences in European Regional and Urban."— Presentation transcript:

1 Regional and urban Policy Combining geography and statistics for an improved analysis of urban phenomena Recent experiences in European Regional and Urban Policy Hugo Poelman DG Regional and Urban Policy B1 - Analysis Unit – GIS team EFGS Conference Wien 10-12 Nov 2015

2 Overview Cohesion Policy and urban development Towards spatially relevant urban indicators A framework for urban analysis Enhancing small urban area estimates Future opportunities

3 Cohesion Policy 2014-2020 Investment policy covering about 1/3 of the EU budget Supports 11 thematic objectives of smart, sustainable and inclusive growth Research and Innovation Combating climate change Information and Commu- nication technologies Competitiveness of SMEs Low-carbon economy Environment and resource efficiency Sustainable transport Better public administration Better education, training Social inclusion Employment and Mobility 5 6 7 1 2 3 4 8 9 10 11

4 Cohesion Policy and urban development 2014-2020: a stronger focus on urban areas  Minimum 5% of ERDF support dedicated to integrated sustainable urban development  Investment themes with urban relevance 12.3 bn for clean urban transport infrastructure and promotion housing infrastructure, co-generation and district heating, etc.  Innovative actions for sustainable urban development  Urban development network  URBACT cooperation programme

5 Towards spatially relevant urban indicators Rich collection of European city statistics Need for more comparable indicators on aspects of sustainability and quality of life Indicators should grasp the diversity of urban areas Spatial framework for data and analysis High-resolution grids Point-based or polygon-based frameworks

6 A framework for urban analysis Copernicus Urban Atlas as framework for Europe- wide cross-thematic analysis inside urban areas  Detailed and harmonised spatial resolution  Tight integration with complete transport networks, especially road networks  Opportunities for linking Urban Atlas data with statistics collected at infra-urban scale (e.g. point based data, census tracts, etc.)  Opportunities for combination with other datasets to go beyond the land use theme

7 Land use indicators for a variety of spatial concepts Cities, greater cities, FUAs Grid-based urban centres Concentric circles around city centroids

8 Spatial distribution of population Population estimates per Urban Atlas polygon  Method first applied to Urban Atlas 2006 data  Updated and improved for Urban Atlas 2012 Higher resolution of the input data on population Use of GHSL layer (modelled building footprints at 10x10 meter resolution) Input for proximity and accessibility analysis

9 Proximity and accessibility analysis Using the power of the combination of  Urban Atlas land use data  Population distribution at the same spatial level  Urban road networks  Location of facilities to produce indicators by city, reflecting the spatial structure of land use and population distribution

10 Proximity of green urban areas Total surface of green urban areas (and forests) that can be reached within 10 minutes walking time

11 Measuring access to public transport Which level of public transport at walking distance? Analysis of frequency and speed of services

12 Speed and frequency profile by transport mode (Berlin) Cumulative population Distribution and frequency of departures (Praha, Brussels, Berlin) Typology of departure frequencies and employment density (Manchester)

13 Rail accessibility of cities / greater cities O/D calculation between stations in cities / greater cities Based on complete EU timetables

14 Enhancing small urban area estimates High-resolution urban population data  Ad-hoc point-based aggregation ?  High-resolution grids  Polygons (building blocks; Urban Atlas)  Use adequate ancillary data when downscaling is required Going beyond total population counts  Population by age class,…  Workplace-based employment, day-time population

15 Downscaling total population Alternative ancillary data: Madrid test case Urban Atlas and GHSLUrban Atlas and buildings floor space Buildings (use typology) Test data on buildings provided by Dirección General del Catastro

16 Downscaling total population Alternative ancillary data: Ghent test case Urban AtlasGHSL (10 m) Urban Atlas and buildings (height) Test data on buildings provided by AGIV (GRB-3D data)

17 Test results Madrid: Population Ghent: Population * TAE = total absolute error (of estimates compared to measured data at census tract level)

18 Going beyond residential population Madrid: Workplace-based employment Scarce high-resolution input data (infra – LAU2) Requires more information on land use and building characteristics More tests forthcoming (NL and UK)

19 Forthcoming publications Urban Atlas based land use indicators in Eurostat city statistics Urban Atlas population estimates on Copernicus Land website Methodological note and results of proximity of green urban areas analysis Extended and updated urban public transport indicators (Inforegio website) Results in European Cities Report (2016)

20 Outlook to future opportunities Currently available data combinations allow for the production of interesting indicators Challenges concerning the spatial resolution of data, timeliness, thematic detail and availability Opportunities for enhanced analysis:  INSPIRE data themes, e.g. building units  Open data or less restrictive access policy (NMAs, public transport operators, cities and regions)  Flexible point-based aggregations (disclosure policy)

21 Acknowledgments Filipe Batista (JRC): population by Urban Atlas polygon Matina Halkia and the whole GHSL team (JRC) Amalia Velasco (Spanish Cadastre) Jo Van Valckenborgh (AGIV Flanders – Belgium) Linde Ackermans, Olivier Draily and Emile Robe (REGIO): sensitivity tests for population and employment disaggregation; rail timetables analysis; accessibility modelling

22 References Copernicus Urban Atlas 2012: http://land.copernicus.eu/local/urban-atlas/http://land.copernicus.eu/local/urban-atlas/ Population estimations for the Urban Atlas polygons: JRC Technical Report: http://publications.jrc.ec.europa.eu/repository/bitstream/111111111/30408/1/qms_h08_int esa_deliverable_2_2_eur_26437.pdf (will be updated with the Urban Atlas 2012 methodology) http://publications.jrc.ec.europa.eu/repository/bitstream/111111111/30408/1/qms_h08_int esa_deliverable_2_2_eur_26437.pdf Measuring access to public transport in European cities: Working Paper 01/2015 http://ec.europa.eu/regional_policy/en/information/publications/working- papers/2015/measuring-access-to-public-transport-in-european-cities http://ec.europa.eu/regional_policy/en/information/publications/working- papers/2015/measuring-access-to-public-transport-in-european-cities Cities in Europe - The new OECD-EC definition: Regional Focus 01/2012 http://ec.europa.eu/regional_policy/sources/docgener/focus/2012_01_city.pdf http://ec.europa.eu/regional_policy/sources/docgener/focus/2012_01_city.pdf Global Human Settlement Layer: http://ghslsys.jrc.ec.europa.eu/ and http://land.copernicus.eu/pan-european/GHSLhttp://ghslsys.jrc.ec.europa.eu/ http://land.copernicus.eu/pan-european/GHSL Cohesion Policy and urban development: http://ec.europa.eu/regional_policy/en/policy/themes/urban-development/ http://ec.europa.eu/regional_policy/en/policy/themes/urban-development/


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