NOTES 1. PLACE, DATE AND EVENT NAME 1.1. Access the slide-set place, date and event name text box beneath the JRC logo from the Slide Master. 1.2. Do not change the size nor the position of that text box. 1.3. Replace the mock-up texts for the place (“Place”), the date (“dd Month YYYY”) and the event name (“Event Name”) with your own texts. 1.4. Set it in MetaPlus Book Roman, if you own the typeface. Otherwise, keep the original typeface – Arial. 1.5. Keep the original flush-left justification. 1.6. Keep the original font colour (white). 1.7. Keep the original font body size (7 pt) and the text on one single line. 2. SLIDE NUMBER 2.1. The slide number on the banner’s lower right-hand side is automatically generated. 3. SLIDES 3.1. Duplicate the first slide as needed. 3.2. Do not change the size nor the position of the slide’s text box. 3.3. Try not to place more text on each slide than will fit in the given text box. 3.4. Replace the mock-up heading text (“Joint Research Centre (JRC)”) with your own text heading. 3.5. Set it in Eurostile Bold Extended Two or in Helvetica Rounded Bold Condensed, if you own one of these typefaces. Otherwise, keep the original typeface – Arial. 3.6. Keep the original flush-left justification. 3.7. Keep the original font colour (100c 80m 0y 0k). 3.8. Keep the original font body size (28 pt) and the heading on one single line whenever possible. Reduce the font body size if needed. 3.9. Replace the mock-up text (“The European Commission’s Research-Based Policy Support Organisation)”) with your own text. 3.10. Set it in MetaPlus Book Roman, if you own the typeface. Otherwise, keep the original typeface – Arial. 3.11. Keep the original flush-left justification. 3.12. Keep the original font colour (100c 80m 0y 0k). Use black if you need a second colour. 3.13. Keep the original font body size (22 pt) or reduce it if unavoidable. 3.14. Replace the EU-27 map mock-up illustration with your own illustration(s). 3.13. Try to keep your illustration(s) right- and top- or bottom-aligned with the main text box whenever possible. A Downscaled Population Density Map of the EU from Commune Data and Land Cover Information Javier.gallego@jrc.it NOTES 1. PLACE, DATE AND EVENT NAME 1.1. Access the slide-set place, date and event name text box beneath the JRC logo from the Slide Master. 1.2. Do not change the size nor the position of that text box. 1.3. Replace the mock-up texts for the place (“Place”), the date (“dd Month YYYY”) and the event name (“Event Name”) with your own texts. 1.4. Set it in MetaPlus Book Roman, if you own the typeface. Otherwise, keep the original typeface – Arial. 1.5. Keep the original flush-left justification. 1.6. Keep the original font colour (white). 1.7. Keep the original font body size (7 pt) and the text on one single line. 2. SLIDE NUMBER 2.1. The slide number on the banner’s lower right-hand side is automatically generated. 3. SLIDES 3.1. Duplicate the first slide as needed. 3.2. Do not change the size nor the position of the slide’s text box. 3.3. Try not to place more text on each slide than will fit in the given text box. 3.4. Replace the mock-up heading text (“Joint Research Centre (JRC)”) with your own text heading. 3.5. Set it in Eurostile Bold Extended Two or in Helvetica Rounded Bold Condensed, if you own one of these typefaces. Otherwise, keep the original typeface – Arial. 3.6. Keep the original flush-left justification. 3.7. Keep the original font colour (100c 80m 0y 0k). 3.8. Keep the original font body size (28 pt) and the heading on one single line whenever possible. Reduce the font body size if needed. 3.9. Replace the mock-up text (“The European Commission’s Research-Based Policy Support Organisation)”) with your own text. 3.10. Set it in MetaPlus Book Roman, if you own the typeface. Otherwise, keep the original typeface – Arial. 3.11. Keep the original flush-left justification. 3.12. Keep the original font colour (100c 80m 0y 0k). Use black if you need a second colour. 3.13. Keep the original font body size (22 pt) or reduce it if unavoidable. 3.14. Replace the EU-27 map mock-up illustration with your own illustration(s). 3.13. Try to keep your illustration(s) right- and top- or bottom-aligned with the main text box whenever possible.

The problem we tackle Suppose you want to study the link between population and geo-referenced data: Population hit by a flood Population in the 65 decibel contour of airports Population at a distance > 2 km of the closest primary school. Population living at <300 m of a (projected) road Population pressure on “Natura 2000” sites

Data in Member States European Forum for Geostatistics (EFGS) In some countries, population data exist for 1 km grids European Forum for Geostatistics (EFGS) Bottom-up approach (accurate) In most countries, National Administrations have population data per census section/district (<1000 inh/district). Representation as a grid (UK) In which countries are census sections geo-referenced? As polygons As points (centroids) Is it possible/suitable/necessary to send a form to National Statistical Institutes to clarify: Type of data available Restrictions to public use

EU-wide data What about making EU-wide studies? Only total population per commune is available at the moment. In the meantime we have downscaled population per commune. Resulting grid can be downloaded from the EEA dataservice: http://dataservice.eea.europa.eu/dataservice/

Table 2: Heterogeneity of commune sizes in the EU Size of communes Table 2: Heterogeneity of commune sizes in the EU Commune area (km2) % Number communes % area % population 0-10 36.6 5.4 14.6 10-100 57.2 45.3 52.8 100-500 5.7 28.3 27.3 >500 0.5 21.1 5.3

Population density downscaling LUCAS Reference data

A simple model for downscaling Xm : population in commune m Scm : area of land cover type c in commune m. Ycm : density of population for land cover type c in commune m. Inside each commune Ycm is assumed to be proportional to given coefficients Uc for each land cover type: If we know Uc , Wm are computed to respect the total population of the commune Problem: estimating reasonable coefficients Uc

Downscaling approaches tested Estimating Uc through: Iterative algorithm (combining NUTS2 aggregation and commune-level data) Straight estimates with LUCAS data % of points with residential use (for non-urban CLC classes) Using LUCAS data in a logit model The density in a CLC class is higher in communes with higher average density. But the function grows slowly (non-linearly) EM Algorithm (Expectation-Maximum Likelihood, Dempster, 1977)

% of LUCAS residential points for different CLC2000 classes

Validation in 5 countries A reliable reference grid available for 5 countries with 1 km2 cells To be extended to other countries Disagreement index for map m: Reference map Disaggregated map cell Austria Denmark Finland Sweden Netherlands Communes (non disaggregated) 8.96 6.08 6.79 12.48 18.3 CLC-iterative 4.55 4.07 5.44 8.05 7.13 CLC-LUCAS simple 4.39 3.97 5.06 8.09 9.03 CLC-LUCAS logit 4.35 3.95 5.03 8.07 7.08 CLC EM 4.50 3.98 5.12 8.08 9.29 disagreement of different disaggregated maps with reference data

Bias in some classes CLC Urban Infra-struct. Agricult. Heterog Forest & Nat.veg Open sp. & water Number of cells 1037 245 14875 4092 1980 644 Reference data 5331 340 75 104 27 2 Communes (non disagg.) 1640 1194 282 332 365 145 CLC-iterative 4614 268 90 154 30 CLC-LUCAS simple 4125 1081 139 218 55 CLC-LUCAS logit 4725 600 101 166 38 CLC EM 3775 2495 87 129 28 1 Netherlands: Average population density for cells with one dominant CLC class (>80%).

Some conclusions Disaggregated population density maps with the help of CORINE Land Cover reduces the disagreement with a reference map Improvement between 20% and 60% But still far from perfect The logit model seems to give the best results among the approaches tested, but the differences are very small (except for NL) In communes that contain large urban and non-urban areas, all the disaggregated maps tested seem to over-estimate the density in non-urban areas.

Next steps Additional countries in the validation (Northern Ireland and Slovenia) Additional countries in the downscaled map (Norway, Switzerland). CLC not yet validated by ETC/LC (???) Using EFGS reference data to better tune coefficients with a “limiting variable” algorithm. Hopefully finished this month. 2006 version: Population data: still some problems to match commune boundaries with tables. CLC: not yet validated.

Further developments Look at specific categories of population Sex, age, job…. If data are available New layers of geographic data should be tried, e.g.: Sealed soil (EEA project ongoing???????) night time light Urban Atlas Layer of population density changes