Integrated GMES Project on Landcover and Vegetation geoland Grid based Spatial Disaggregation of Population Data Klaus Steinnocher – ARC systems research – Geostatistics Kongsvinger – Co-funded by the European Commission within the GMES initiative in FP-6

geoland Background Integrated project geoland Observatory Spatial Planning Klaus Steinnocher ARC systems research funded within the 6th framework programme of the EC represents a network of more than 50 research organisations, public administrations and service providers aims to provide and establish geo-information products and services to support the European Global Monitoring for Environment and Security (GMES) programme utilises available Earth Observation resources, and integrates them with existing models into pre-operational end-user applications

geoland Background Observatory Spatial Planning Klaus Steinnocher ARC systems research Introducing innovative EO based services and products into the domain of spatial planning Building upon a representative user group representing European, national and regional policy requirements DG Regio, ESPON Environmental agencies Regional governments Serving user needs by integrating EO-derived land cover and use information with existing socio-economic data Spatial Planning on European level focuses to a very high degree on socio-economic data alone Land cover and use information can substantially improve statistical data

geoland Linking people and pixels Spatial disaggregation Observatory Spatial Planning Klaus Steinnocher ARC systems research Population density per artificial surface areas NUTS3 population density Share of artificial surface areas + =

geoland Spatial disaggregation Population density Observatory Spatial Planning Klaus Steinnocher ARC systems research Parameters Total population – global parameter on administrative units level Housing density – local parameter from Earth observation Spatial Disaggregation Distributes population according to housing densities Results in local distribution of population Assumptions Population density is proportional to housing density, no population occurs outside housing areas, and relationship between population and housing density is constant within a region, but might differ between regions. Question Is the assumption valid? How accurate are the resulting data?

geoland European case study Transnational test site Observatory Spatial Planning Klaus Steinnocher ARC systems research Region Central Europe 7 countries Data base Residential areas from CLC (class 1.1 urban fabric) Population per NUTS 3 area (Eurostat) Reference data (Austria) Population grid (250m) –Statistik Austria Population per district / municipality (census)

geoland European case study CORINE land cover 2000 Observatory Spatial Planning Klaus Steinnocher ARC systems research Artificial surfaces Agricultural areas Forest and semi- natural areas Wetlands Waterbodies CORINE land cover level 1 Source: CLC 2000 Wien Praha München Stuttgart Nürnberg Chemnitz Erfurt Kassel Milano Venezia Bratislava

geoland European case study Proportion of urban fabric 2000 per 3x3km grid cell Observatory Spatial Planning Klaus Steinnocher ARC systems research no urban fabric below to 5 5 to to to to to to to to to 100 Proportion of urban fabric [%] Source: CLC

geoland European case study Population density 2000 per NUTS 3 area Observatory Spatial Planning Klaus Steinnocher ARC systems research Source: Eurostat Regio Data Base below to to to to to to to above Population density [pop/km 2 ]

geoland European case study Population density 2000 on urban fabric per 3x3km grid cell Observatory Spatial Planning Klaus Steinnocher ARC systems research no population below to to to to to to above Population density [pop/km 2 ] Source: CLC 2000 Eurostat Regio Data Base

geoland European case study Population density 2000 on urban fabric per 3x3km grid cell Observatory Spatial Planning Klaus Steinnocher ARC systems research Source: CLC 2000 Eurostat no population below to to to to to to above Population density [pop/grid cell]

geoland European case study Population density 2000 from census per 3x3km grid cell Observatory Spatial Planning Klaus Steinnocher ARC systems research Source: Statistik Austria no population below to to to to to to to above Population density [pop/grid cell]

geoland European case study Comparison of census and disaggregation results Observatory Spatial Planning Klaus Steinnocher ARC systems research Total cells Populated cells: Statistik Austria census grid7.739 NUTS 3 / CLC 1.1 disaggregation Disaggregation covers only 51,8 % of cells, BUT 91,3 % of total population District level all districtsurban districts excluded average error 21,4% (14.505) 13,8% (8.278)

geoland European case study Comparison on district level Observatory Spatial Planning Klaus Steinnocher ARC systems research Source: CLC 2000 Eurostat / Statistik Austria below to to to to 40 above 40 Relative population difference [%]

geoland Regional case study Vorarlberg Observatory Spatial Planning Klaus Steinnocher ARC systems research Region State of Vorarlberg 5 districts, 93 municipalities Data sets Housing density 1: – 3 density classes (250m grid) Residential areas 1: – 1 class (from CLC) Population – total for entire region Validation data Population density raster (250m) – from Statistik Austria Population totals for districts / municipalities

geoland Regional case study Comparison of housing and population density (250m grid) Observatory Spatial Planning Klaus Steinnocher ARC systems research

Satellite image geoland Regional case study Comparison of population densities (250m grid) Observatory Spatial Planning Klaus Steinnocher ARC systems research Reference data (census)Disaggregation results

geoland Regional case study Comparison of population densities (250m grid) Observatory Spatial Planning Klaus Steinnocher ARC systems research Reference data (census)Disaggregation results Difference to reference

geoland Regional case study Comparison of population on district level Observatory Spatial Planning Klaus Steinnocher ARC systems research housing densitiesresidentialproportional relative average error 8,4% (5.904) 12,7% (8.874) 94,7% (66.325)

geoland Regional case study Comparison of population on district level Observatory Spatial Planning Klaus Steinnocher ARC systems research Absolute deviations from reference per municipality housing densitiesresidentialproportional relative average error 12,8% (467) 26,9% (981) 113,3% (4.136)

geoland Conclusions Observatory Spatial Planning Klaus Steinnocher ARC systems research Spatial disaggregation of population leads to reliable results Accuracies improving with level of detail of land cover data (housing densities) depending on spatial reference unit (districts, municipalities, etc.) smaller units lead to lower relative but higher absolute accuracies urban centers are underestimated, due to missing information on building heights sparsely populated areas are underestimated, due to minimum mapping unit For disaggregation of population housing density classes are required Large cities should be treated separately

Integrated GMES Project on Landcover and Vegetation geoland Thank you for your attention! Co-funded by the European Commission within the GMES initiative in FP-6 Contact: ARC systems research GmbH Klaus Steinnocher +43–(0)50550–3876 geoland coordinators: Medias-France Infoterra GmbH