# NTTS 2009 Brussels February 20 1 A Downscaled Population Density Map of the EU from Commune Data and Land Cover Information NOTES.

## Presentation on theme: "NTTS 2009 Brussels February 20 1 A Downscaled Population Density Map of the EU from Commune Data and Land Cover Information NOTES."— Presentation transcript:

NTTS 2009 Brussels February 20 2 In most countries, population data are available for public use only per administrative unit (commune) In many cases this may be insufficient for geographical analysis. –It depends on the size of the geographic units and the scale of the event under assessment. –Population hit by a flood –Population in the 65 decibel contour of airports –Population at a distance > 2 km of the closest primary school. In some countries, population data exist for 1 km grids –Bottom-up approach (much better..) Rationale

NTTS 2009 Brussels February 20 3 Population density downscaling Starting data: Population per commune and CORINE Land Cover. Result: Approximate population density with 1 ha resolution (GIS grid) + =

NTTS 2009 Brussels February 20 4 CORINE Land Cover Land cover map from photo- interpreted Landsat-TM images 44 classes –Urban dense –Urban discontinuous –…… Minimum mapping unit: 25 ha. –Smaller patches swallowed by dominant class –heterogeneous classes if no one is dominant (~10% of the total area) For this exercise, simplified nomenclature of 9 classes

NTTS 2009 Brussels February 20 5 A simple model for downscaling X m : population in commune m S cm : area of land cover type c in commune m. Y cm : density of population for land cover type c in commune m. Inside each commune Y cm is assumed to be proportional to given coefficients U c for each land cover type: If we know U c, W m are computed to respect the total population of the commune Problem: estimating reasonable coefficients U c

NTTS 2009 Brussels February 20 6 Version 1 of the downscaling Estimating U c with an iterative algorithm: 1.Pretend for a moment that population is known only per region (not per commune) 2.Downscale with a provisional set of coefficients 3.Compute the population that would be attributed to each commune X * m 4.Compare each X * m with the known population X m and compute a disagreement index 5.Modify U c to reduce the disagreement (ask paper for details) 6.Turn to step 2 or stop if modification very small

NTTS 2009 Brussels February 20 7 LUCAS 2001/2003 (Land Use/Cover Area-frame Survey) Managed by Eurostat (Common specifications for EU15 ) nomenclature Land cover (57 classes) * Land use (14 classes) The land Use residential gives information useful to assess the density of buildings in CLC non- urban classes. The residential area is used as proxy of the population density in CLC non-urban areas. Introducing LUCAS data

NTTS 2009 Brussels February 20 8 % of LUCAS residential points for different CLC2000 classes

NTTS 2009 Brussels February 20 9 Coefficients suggested by the % of residential area Version 3 of the disaggregated grid

NTTS 2009 Brussels February 20 10 Application of logit regression Assumption: the probability that a random point has residential land use depends on the CLC class and on the average population density of the commune The logit model assumes more specifically: Where Jc is an 0-1 indicator of the CLC class c

NTTS 2009 Brussels February 20 11 Residuals of the logit regression (2001) The residuals of the logit regression can be used for the geographical tuning of the coefficients (not yet done…)

NTTS 2009 Brussels February 20 12 EM Algorithm Iterative algorithm (Expectation – Maximum likelihood): Assumption: the population X mc in land cover class c for the commune m follows a Poisson distribution with parameter U c x S cm M step computes a maximum lilelihood estimator of U c E step makes an adjustment to ensure that the population attributed to the communes territory equals X m (known)

NTTS 2009 Brussels February 20 13 Validation in 5 countries A reliable reference grid available for 5 countries with 1 km 2 cells To be extended to other countries Disagreement index for map m: cell Disaggregated map Reference map disagreement of different disaggregated maps with reference data Austria DenmarkFinlandSweden Netherlands Communes (non disaggregated)8.966.086.7912.4818.3 CLC-iterative4.554.075.448.057.13 CLC-LUCAS simple4.393.975.068.099.03 CLC-LUCAS logit4.353.955.038.077.08 CLC EM4.503.985.128.089.29 CLC limiting variable4.834.025.107.787.95

NTTS 2009 Brussels February 20 14 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.

NTTS 2009 Brussels February 20 15 Further developments Reference maps available might be used also for calibrating models, not only for validation – Downscaling the reference maps to 1 ha resolution? New layers of geographic data should be tried, e.g.: – night time light – Tele-Atlas Adding Switzerland and Norway Producing a first version with 2006 data – Still some countries missing for population data – CLC2006 not yet distributed Layer of population density changes Introducing more detailed data for urban areas (Urban Atlas)

Download ppt "NTTS 2009 Brussels February 20 1 A Downscaled Population Density Map of the EU from Commune Data and Land Cover Information NOTES."

Similar presentations