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WP 8 CAPRI GIS Link

WP 8 CAPRI GIS Link. Agricultural Policy – The Dynamic and Spatial Dimension ( CAPRI-DynaSpat ). Relevant spatial datasets for the disaggregation of CAPRI-DynaSpat parameters Description - Use - Constraints. Renate Köble and Adrian Leip. SPATIAL DATA SETS. LAND COVER/LAND USE MAPS

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WP 8 CAPRI GIS Link

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  1. WP 8 CAPRI GIS Link Agricultural Policy – The Dynamic and Spatial Dimension (CAPRI-DynaSpat) Relevant spatial datasets for the disaggregation of CAPRI-DynaSpat parameters Description - Use - Constraints Renate Köble and Adrian Leip CAPRIDynaSpat, Bonn 10.3.2003

  2. SPATIAL DATA SETS • LAND COVER/LAND USE MAPS • determine mainly the “spatial resolution” of the disaggregation • LAND USE/COVER AREA FRAME STATISTICAL SURVEY • can be used to create a decision matrix how to allocate the statistical agricultural activity data and model outputs to the land cover classes • SPATIAL DATA ON ELEVATION, BIOGEOGRAPHICAL REGIONS AND SOIL • deliver additional information to allocate statistical agricultural activity data and model outputs especially for complex land cover classes CAPRIDynaSpat, Bonn 10.3.2003

  3. CORINE LAND COVER/LAND USE 1990 • CORINE (Coordination of Information on the Environment) land cover mapping program was proposed in 1985 by the EU Commission to satisfy the need of precise and easy accessible information on land cover in Europe • CLC describes land cover (and partly land use) according to a nomenclature of 44 classes organised hierarchically in 3 levels • Elaborated based on the visual interpretation of satellite images and ancillary data (aerial photographs, topographic maps etc.) • Acquisition period of satellite images 1985 to 1995 • Smallest surface mapped: 25 ha. Scale of the output product 1:100 000 • The 100 m2 grid data set is available for the CAPRI-DynaSpat area of interest except Sweden • For Switzerland a national land cover map is available with classes corresponding to Level II of the CORINE classification system CAPRIDynaSpat, Bonn 10.3.2003

  4. CORINE LAND COVER/LAND USE 2000 • An update of the CORINE Land cover database for the year 2000 is under processing • The update will be more time consistent (satellite images from 2000 +/-1year) • Improvement of the geometric accuracy • CORINE LC90 will be revised (land cover classes and geometry will be reviewed) • Maps with land cover changes from “1990” to 2000 will be produced • Currently data is available for Ireland, Netherlands, Latvia, Luxembourg and Malta • Data for Lithuania, Poland, Spain, Sweden, Italy might be available before summer • the aim is to finish 80% of EU25 (+ Bulgaria, Croatia, Romania) by the end of 2004 CAPRIDynaSpat, Bonn 10.3.2003

  5. CORINE CLASSIFICATION CAPRIDynaSpat, Bonn 10.3.2003

  6. CORINE LC IN THE BONN AREA CAPRI DYNASPAT KICK-OFF MEETING CAPRIDynaSpat, Bonn 10.3.2003

  7. PELCOM LAND COVER/LAND USE • The Pan-European Land Cover Monitoring (PELCOM) project was carried out 1996-99. Funded as a shared cost action within FP4. • The PELCOM land cover map distinguishes 14 land cover classes (4 agricultural classes) • Classification is based on 1km resolution satellite images (NOAA AVHRR) and ancillary data as e.g. topographic information, rivers/lakes/coastlines • Acquisition period of satellite images 1997 • Covers Europe and parts of Russia and the Middle East CAPRIDynaSpat, Bonn 10.3.2003

  8. CORINE/PELCOM LC CLASSIFICATION CORINE PELCOM CAPRIDynaSpat, Bonn 10.3.2003

  9. CORINE AND PELCOM LAND COVER Pastures Complex cultivation pattern Land princip. occ. by agric. & sign areas of nat. veg. Not irrigated arable land Forest Urban area Grassland Rhein-Sieg-Kreis CAPRIDynaSpat, Bonn 10.3.2003

  10. LAND COVER DATA SETS AVAILABLE FOR THE CAPRI-DynaSpat AREA CAPRIDynaSpat, Bonn 10.3.2003

  11. COMPARISON OF CLC90 AND FARM STRUCTURE SURVEY DATA RECLASSIFIED STATISTICS CLC90 11 agricultural classes, FSS 42 classes Kayadjanian et al. (2001) LANDCOVER MAP CAPRIDynaSpat, Bonn 10.3.2003

  12. THE POSSIBLE REASONS FOR THE DEVIATIONS ARE MANYFOLD • Data is related to different time spans (FSS 1990, CLC 1985-95) • Per definition CLC omits areas <25 ha, therefore non irrigated arable land may be included to some extend also in other CLC classes as e.g. “Complex cultivation patterns with significant area of natural vegetation” or “Grassland” • FSS classes can not be exactly regrouped in the CLC classes due to different classification systems (e.g. within irrigated land) • Photo-interpretation inaccuracy for CLC • Errors in the FSS CAPRIDynaSpat, Bonn 10.3.2003

  13. LUCAS SURVEY The Land Use/Cover Area Frame Statistical Survey (LUCAS)has been launched by Eurostat and DG Agri* to: • obtain harmonised data (unbiased estimates) at EU 15 level of the main Land Use / Cover areas and changes. • evaluate the strengths and weaknesses of a point area frame survey as one of the pillars of the future Agriculture Statistical System (area frame means that the observation units are territorial subdivisions instead of agricultural holdings as in the Farm Structure Survey). *Decision N°1445/2000/EC of the European parliament and of the Council of the 22.05.2000 “on the application of area-frame survey and remote-sensing techniques to the agricultural statistics for 1999 to 2003”. CAPRIDynaSpat, Bonn 10.3.2003

  14. ORGANISATION OF THE LUCAS SURVEY • Main land cover/use survey raster: 18 km by 18 km with 10 subsampling Units • Phase 1: field survey at ~100000 observation points in EU15 (spring) • Phase 2: interview with ~5000 farmers to obtain additional technical or environmental information (autumn) • The first survey has been carried out in 2001 (UK 2002) • 57 land cover classes are separated including 34 agricultural classes • High geometrical accuracy of the sampling locations (+/- 3m) Sampling design: Primary sampling units in NL CAPRIDynaSpat, Bonn 10.3.2003

  15. LUCAS SURVEY CLASSIFICATION CAPRIDynaSpat, Bonn 10.3.2003

  16. FINE SCALING CORINE LC CLASSES WITH LUCAS DATA • Based on a study from J. Gallego (2002) • Fine scaling in this case means estimating the proportion of other land cover classes within a given CORINE class as e.g. “pastures” • To examine the possibility of fine scaling the CLC classes J. Gallego overlaid the CLC with the point observation of the LUCAS 2001 survey • The operation produces a matrix with 56 columns (LUCAS land cover classes) and 44 rows (CLC) that allows to analyse the composition of other land cover classes within a specific CLC land cover class CAPRIDynaSpat, Bonn 10.3.2003

  17. FINE SCALING CLC 2000 WITH LUCAS DATA LUCAS Test for Ireland CORINE CAPRIDynaSpat, Bonn 10.3.2003

  18. SPATIALISATION OF STATISTICALLAND USE WITHIN ONE LAND COVER CLASS • A study of the Geographical Information Management (G.I.M, 2002) group showed to possible value of using topographical (elevation, slope) and soil information to disaggregate CLC land cover classes with complex patterns into single “classes” . • Example: CLC class ‘complex cultivation patterns’ contains 30% arable land, 40% pasture, 30% forest (based on CLC/LUCAS analysis). Roughly speaken: arable land will be attributed to the best growing/farming conditions -> good soils / low altitudes / flat terrain • The G.I.M method will be reviewed • Analysis if the assumptions can be improved by looking at relationships between LUCAS data – soil – topography CAPRIDynaSpat, Bonn 10.3.2003

  19. CHANGES IN AGRICULTURAL AREABASED ON CLC90 AND CLC2000 94 CAPRIDynaSpat, Bonn 10.3.2003

  20. LAND COVER CHANGES IN NL Agricultural area to Artificial surfaces Agricultural area to Forest & seminatural areas Amsterdam Agricultural area to Wetlands CAPRIDynaSpat, Bonn 10.3.2003

  21. INFRASTRUCTURE FOR SPATIAL DATA IN EUROPE (INSPIRE) • With the INSPIRE initative, the European Commission intends to trigger the creation of a European Spatial Data Infrastructure (ESDI) • The ESDI has to be set up in a way that will allow public users at European to local level to discover, access and acquire spatial data from a wide range of sources for a wide range of applications • INSPIRE expert groups has been set up for several topics e.g. • Reference data and metadata • Data policy and legal issues • Architecture and standards (reference system, projections, European reference grid system) • … CAPRIDynaSpat, Bonn 10.3.2003

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