Spatial Analysis at EEA and CORINE Land Cover GeoForum meeting, EEA, 18 th May 2010

Outline GIS at EEA from the desktop user perspective –Context –Spatial analysis CORINE Land Cover –Project set up –Results –Derived analysis examples

EEA mission The EEA aims to support sustainable development and to help achieve significant and measurable improvement in Europe’s environment, through the provision of timely, targeted, relevant and reliable information to policy-making agents and the public.

By means of... Reports, publications  spatial analysis, maps Indicators  spatial analysis, maps Datasets download  spatial data Online datasets

Our spatial data context Subsidiarity principle  local authorities, regions, countries produce data Target: 1:100,000 The problem: to have harmonized comparable data Data flows

EIONET & data flows

EEA mapping standards Guideline to data & maps: de.dochttp:// de.doc – Map templates – Metadata editor/metadata profile – Good practices: projections, formats, how to report spatial data

Spatial analysis Try to answer policy questions in a dynamic changing environment: how much? Independently assess the state of environment and drivers: land use/land cover change, water availability, agriculture and environment,... Produce derived datasets: accessibility maps, fragmentation indexes, urban temperature,... Homogenous data rather than very detailed Low amount of data  specialized spatial analysis Techniques: all available, but very raster based

Examples Hydrology: ECRINS Derived datasets: Green Background Fragmentation Accessibility maps Land cover statistics: trends of land cover change

ECRINS – hydro model

Green Background map

Landscape fragmentation

Accessibility maps

Corine Land Cover (CLC) Scale 1: , seamless vector database 44 classes in 3 hierarchical levels 25 ha Minimum Mapping Unit (MMU) 5 ha MMU for land cover changes 39 countries, about 5.5 Million square Km Classes illustrated:

Main political demand Environment Policy Habitat Directive (Natura2000), Biodiversity convention, 2010 target Water Framework Directive Integrated Coastal Zone Management INSPIRE Common Agriculture Policy Impact of agricultural policy on the environment Regional Policy European Spatial Development Perspective Territorial cohesion Research Policy Climate change + others

Ortho-rectified satellite image database Visual image interpretation (national teams) Verification – qualitative (EEA - ETC/LUSI) Final vector database (national team) Validation – quantitative (EEA - ETC/LUSI) European Data integration – vector & raster (EEA - ETC/LUSI) Methodology

CLC concept IMAGE200xCLC200x Centralised activity based on satellite images Decentralised activity based on national CLC databases

Organisational set-up EEA JRC LCTU IMAGE2000 team National CLC2000 teams European Steering Committee National Steering Committee

Methodology

History CLC1990 Process from 1985 to year process Growing process No common data policy CLC2000 Coordinated approach Snapshot (2000 +/- 1 year) 29 countries Agreed data policy for image and mapping data Output: –CLC2000 –CLC changes –CLC90 corrected

CLC2006 Why? –High interest in land cover changes –More frequent updates (< 10 years) –Better fulfil reporting obligations Integration into GMES Reliable, up-to-date and accessible information on the environment for Europe –GMES Fast Track Service on Land (delivery 2008) CLC2006 update 2 high-resolution layers

GMES FTS Land first set of core land cover data products CLC 2006 Built-up area / sealing CLC Changes

CORINE Land Cover map

Validation of European CLC data Need for an independent database –LUCAS – Land Use land Cover Area Sampling Statistical sampling grid Similar timeframe points over Europe (18 countries) Field survey of land use and land cover Field photographs Re-interpretation of field photographs

Validation results Display of LUCAS points on IMAGE2000 Interpretation of point from satellite image and field photographs Creation of error matrix Overall accuracy: 87.0% ± 0.8%

CLC - a success story Number of downloads from EEA web site Applications Value of downstream applications

Corine land cover downloads from CLC2000

Use of Corine Land Cover Breakdown per economic sector Investment cost CLC2000: 13 Meuro Estimated revenues generated by underpinning downstream activities using CLC: 250 Meuro* *Based on analysis of 500 activities out of 5658 registered users

State & outlook of Europe’s Environment

Urban aglomerations

Example: Population density (based on CLC and Eurostat) + = Source: EEA, JRC (2005)

Land cover change accounts: from maps to statistics LCF1Urban land management LCF2Urban residential sprawl LCF3Sprawl of economic sites and infrastructures LCF4Agriculture internal conversions LCF5Conversion from other land cover to agriculture LCF6Withdrawal of farming LCF7Forests creation and management LCF8Water bodies creation and management LCF9Changes due to natural & multiple causes Land cover 1990 & 2000 and land cover change are first converted to a grid (below, 1x1 km) Individual changes are grouped by land cover flows that describe processes

CLC products 1.Ortho-rectified satellite images for the reference year 2006 (+/- 1 year); 2.European mosaic based on ortho-rectified satellite imagery (IMAGE2006); 3.Corine land cover changes ; 4.Corine land cover map 2006 (CLC2006); 5.High resolution built-up areas including degree of soil sealing 2006;

The national and regional perspective Denmark: NERI LC2000/ LC2000/ Some regions/countries extend the CLC: –Andalusia (87000 sq Km, South of Spain) Better thematic accuracy (CORINE compliant) 1:25.000, no MMU Better update frequency (4 years) Downdated to 1956 In general it’s a success: co-ownership, involvement of technical teams, multipurpose

CHANGES ANALYSIS EU Example

Land cover change CLC available for all EU27 countries except SE, GR, UK, FI 3,321,035 square Km 114,417 square Km changed (aproximately the size of Bulgaria) for the period  3.45% changed –only 25% are “main land use” changes, –75% are internal conversions

“Main land use” changes 25% of the total changes 0.86% of the territory EU27: 36,200 sq Km (like NL) Per year: 2,300 sq Km (like LU) Facts Urban sprawl per year in the EU: 1100 square Km  equals to Moscow urban agglomeration area (source UN)

Internal conversions 75% of the total changes 2.58% of the territory square Km (bigger than AT) 5346 square Km / year (2 times LU) Most of the internal conversions happened: 1 st Forest and semi natural 2 nd Agriculture Facts

Total turnover

Trends

Change rates differ by Biogeographical Regions

Mediterranean Bigger LC change pressure Patterns are the same, but agriculture competes with urban for the space

Trends 1990 – 2000 – 2006 (*) (*) 100% = status in 1990; the lines show the relative increase (trend) for the 2 periods, , Urbanisation: same trend, above 0.5% yearly increase Forest and semi-natural are stable Wetlands don’t disappear as quickly as in the previous period; strong trend change (from 0.22% yearly loss to 0.06% yearly loss) Water bodies are created at a slower pace (0.19% yearly increase to 0.08%)

Urban sprawl – trends analysis Same rate: 0.5% yearly increase For EU27 that means aprox sq Km per year  the surface of Moscow’s urban agglomeration or Ruhr’s region big urban agglomeration In  more recycling of other urban areas Bigger pressure on forests and seminatural areas  For both time steps, 80% or more is happening in agriculture or already existing artificial areas

Green urban areas– trends analysis GUAs grew at a 1% relative increase rate (for both periods)  slightly above 100 sq Km a year (75 times London Hyde Park a year) In artificial areas increased by 8%, whereas Green urban areas increased by 16% In the period , green urban areas grew mainly on agricultural areas In the period , the recycling of other artificial to green areas was doubled, but they also more forest and semi natural areas were taken

Trends in the coast: 1975 to 2006 (30 years of changes) Artificialisation has a constant growth rate: 0.5% relative increase each year Water bodies were created in Agriculture shows a constant decline Wetlands and forest and semi- natural decreased heavily (around 10%) in ; it has slowed down

Denmark Hectares

Denmark changes

Urban Atlas

GlobCORINE

Thank you!