The use of geostatistics for the analysis of europe s regions
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The use of geostatistics for the analysis of Europe’s regions. Hugo Poelman European Commission – DG Regional Policy EFGS workshop, Den Haag, 6 October 2009. The geographical framework. Policy-supporting analysis of the European regions

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The use of geostatistics for the analysis of europe s regions

The use of geostatistics for the analysis of Europe’s regions

Hugo Poelman

European Commission – DG Regional Policy

EFGS workshop, Den Haag, 6 October 2009

The geographical framework
The geographical framework regions

  • Policy-supporting analysis of the European regions

  • NUTS regions: the backbone of the analytical framework

    • Role in implementing cohesion policy interventions

    • Legal background (NUTS Regulation)

    • NUTS2 and NUTS3 levels allowing for different levels of detail

    • Statistical system providing extensive datasets

Issues with nuts regions
Issues with NUTS regions regions

  • Spatially heterogeneous

  • Changes over time

  • Most regions are more administrative than functional

  • Thematic data availability varies

  • Regional breakdown is more appropriate for some themes, less for others

  • Border effects between countries and regions

Extended thematic needs
Extended thematic needs regions

  • Challenges with regional / territorial dimension, e.g.

    • Climate change effects

    • Infrastructure and (public) services

    • Accessibility and connectivity

    • Environment and quality of life

    • Energy

  • Statistical systems often have difficulties to tackle the regional dimension of these areas

Use cases of geostatistics
Use cases of geostatistics regions

  • Exploration of the use of geostatistics

    • Helping to overcome some of the issues related to (administrative) regions

    • Allowing for better analysis of various georeferenced data, e.g.

      • Remote sensing

      • Network related data

    • Improvement of the development of regional typologies

Key data source in geostatistics
Key data source in geostatistics regions

  • Many analysis cases rely upon the use of a regular and sufficiently detailed population distribution

  • 1 km² registered population data for available countries

  • Population disaggregation layer (JRC – Javier Gallego) for the other countries, aggregated at 1 km² cell size

Overcome issues related to irregular regions
Overcome issues related to irregular regions regions

  • A few examples:

    • 1) Availability and accessibility of passenger flights

    • 2) Estimate of potential market size

1 accessibility to passenger flights
1) Accessibility to passenger flights regions

  • Various statistical data can be (almost directly) exploited at regional level

    • Departures per airport

    • Air traffic data at NUTS2 level

  • Results are hardly meaningful when only considering the region where the airport is located

  • Accessibility analysis tries to overcome the border effects of the regions

1 accessibility to passenger flights1
1) Accessibility to passenger flights regions

  • Basic data

    • Airport locations + data on departing passenger flights

    • Road transport network

    • Population distribution

  • Results

    • Areas where a certain number of flights is easily accessible

    • Population-weighted regional average figures on available and accessible flights

2 potential market size
2) Potential market size regions

  • Estimate the amount of GDP or population available within a pre-defined neighbourhood

  • Within the neighbourhood, distance is taken into account

  • Analysis is carried out using rasters with 1 km² and 10 x 10 km cells

  • NUTS2 regions used as reporting units

2 potential market size1
2) Potential market size regions

  • Basic data

    • Regional GDP/head figures in PPS

    • Population distribution grid

    • NUTS polygons and derived NUTS grid

  • Results

    • Focal sum of GDP (or population)

    • Regional averages of the obtained focal sums

    • Results expressed as index of EU average for easier interpretation

Enhanced analysis of various georeferenced sources
Enhanced analysis of various georeferenced sources regions

  • Geostatistics help in establishing links between data from remote sensing and regional or territorial reporting units

  • Especially relevant in the area of the environment, climate change effects, hazards, etc.

Concentrations of pm10
Concentrations of PM10 regions

  • Basic data

    • Grid layers from GMES PROMOTE project with yearly summary data on concentrations of PM10 (similar data also for ozone)

    • Population distribution

Concentrations of pm101
Concentrations of PM10 regions

  • Results

    • Population-weighted regional average concentrations of PM10

    • Same approach can also be applied to other territories (e.g. major agglomerations)

Development of typologies
Development of typologies regions

  • Regional and territorial typologies often need to refer to data / variables which make sense at lower levels than the level at which the typology is to be applied

  • Choice between regular grids and local administrative units ??

  • Regular grids often have an advantage when using data on geophysical or natural phenomena and help to overcome the MAUP

Typologies using a regular population distribution
Typologies using a regular population distribution regions

  • Mountain regions, based a comparison of the population grid and a geophysical definition of mountain areas

  • Typology of rural areas according to their remoteness

    • Evaluation of the accessibility of city centres via the road network

    • Share of regional population living at more than 45 minutes from city centres

Findings on use cases
Findings on use cases regions

  • Use of geostatistics for regional policy started in rather experimental way

  • But resulted in various indicator sets, used in further analysis and reports

    • Green paper on territorial cohesion

    • Regions2020 report

    • Cohesion reports

  • More use and more “visibility” of the results also means more requirements…

Further developments 1
Further developments (1) km² resolution

  • Topics related to a common European definition of rasters

    • Rules and methods for conversion of national grids into European ones

    • Issue of cell size for European-wide analysis of regions and territories

      • Trade-off between precision, analysis effort and confidentiality issues

    • De-facto standard used at EU level (JRC / EEA)

Further developments 2
Further developments (2) km² resolution

  • Timeliness and frequency of essential geostatistical datasets

    • Weakness of current analysis: 2000-2001 time stamp of major population grid

    • New thematic datasets with emerging time series require the use of corresponding population distribution

    • Timely land cover datasets

    • Disaggregation may help to overcome incompleteness of data

Further developments 3
Further developments (3) km² resolution

  • Enlarge the thematic scope

    • Various analyses would benefit from the use of other raster datasets than merely total population

      • Key demographic breakdowns (age classes)

      • Employment (day/night time population)

  • Location of services?

    • Issues of harmonisation and definition

    • Confidentiality?

Outlook km² resolution

  • Continued and enhanced use of currently available geostatistical sources

  • Help awareness raising by demonstrating and documenting use cases

  • Promote (via Eurostat) further development of European-wide geostatistical datasets and methodologies

References km² resolution

  • Green Paper on Territorial Cohesion

  • Regions2020 report

  • Regional Focus

    • 01/2008: Remote rural regions

    • 01/2009: Metropolitan regions in the EU

  • 5th Cohesion Report (due in Autumn 2010)