1. 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
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.

2. 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

3. 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

4. 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:

5. 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
5.7
28.3
27.3
>500
0.5
21.1
5.3

6. Population density downscaling
LUCAS
Reference data

7. 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

8. 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)

9. % of LUCAS residential points for different CLC2000 classes

10. 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

11. 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%).

12. 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.

13. 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.

14. 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