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Disaggregation of CAPRI results

Disaggregation of CAPRI results. Renate Köble Adrian Leip. Outline. 1. Introduction 2. Existing approaches 3. Tentative solution of the problems 4. Overview on available data sets Corine Landcover 2000 LUCAS survey 7. First example. WP8 - CAPRI-GIS link.

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Disaggregation of CAPRI results

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  1. Disaggregation of CAPRI results Renate Köble Adrian Leip JRC-AL – Bonn on 10.03.2004

  2. Outline • 1. Introduction • 2. Existing approaches • 3. Tentative solution of the problems • 4. Overview on available data sets • Corine Landcover 2000 • LUCAS survey • 7. First example JRC-AL – Bonn on 10.03.2004

  3. WP8 - CAPRI-GIS link • “Link of CAPRI to GIS covering soil, climatic and land use maps” • Distribution of agricultural activities on the land • Correspondence between geo-coded data and geo-referenced data from land cover maps • Distribution of secondary agricultural parameters • livestock densities, feed composition • animal wastes (grazing / stabling / application)? • mineral fertilizer • other parameters? • Re-mapping for the calculation of indicators • grid size / thematic maps • Allocation of land use changes in the reference year • net / gross changes ? • use of additional information JRC-AL – Bonn on 10.03.2004

  4. Studies to built on ... (1) • Trees species map (Renate) • Calculation of Agricultural Nitrogen Quantity for EU River basins (JM Terres, JRC, 2000) • based on a methodology developed in a regional study (Loire and Elbe catchment) 2000 • used by Declan to disaggregate NUTS 2 NewCronos data to NUTS 3 level for the DNDC model JRC-AL – Bonn on 10.03.2004

  5. CORINE NUTS 2 NUTS 3 (or gridcell) allocationmatrix Use of a correspondence table Corine / FSS JRC-AL – Bonn on 10.03.2004

  6. VARESE PROVINCE JRC-AL – Bonn on 10.03.2004

  7. Land to be redistributed (FSS 2000 - arable land (D except rice)) • Lombardia 641 640 ha arable land • Varese 6 440 ha arable land • Land available (Corine Land Cover 90) • class 211: non-irrigated arable land • class 242: complex cultivation pattern • class 243: land principally occupied by agriculture JRC-AL – Bonn on 10.03.2004

  8. x distribution factor for potentially available land: • non-irrigated arable land 0.95 • complex cultivation pattern 0.80 • land principally occupied by agriculture 0.60 2.2% of land potentially available in Lombardia is located in the province of Varese JRC-AL – Bonn on 10.03.2004

  9. Disaggregation FSS2000 data • Total deviation: 45 000 ha (7% of total arable land distributed) • “Transfer” of arable land from the south to the north • total potential area: 891 kha JRC-AL – Bonn on 10.03.2004

  10. LOMBARDIA Non-irrigated land Permanently irrigated land Complex cultivation pattern Land principally occupied by agriculture with sign. areas of natural veg. Natural grassland Pastures Agro-forstry Fruit trees and berry plantations Rice Fields Vineyards Forests Water Urban JRC-AL – Bonn on 10.03.2004

  11. Problems? • Assumption of equal land use of land classes throughout Europe • Non-matching between statistical and land cover data • Interpretation errors and interpretation differences • Time lag between Satellite images and Statistical census • Corine 1990 has is based on images between 1985-1993 • FSS 2000 represents the situation in 2000 JRC-AL – Bonn on 10.03.2004

  12. Studies to built on ... (2) • Spatial redistribution of statistical data from the Farm Structure Survey (GIM report) • Match absolute values of land in both data sets • regrouping of CLC and FSS to aggregate classes • Matrix of land cover classes potentially available • Classes are filled-up successively • Coefficients are optimized Aj: area of Farm Structure category j CLCi: area of Corine class i cij:coefficient for redistribution of Corine class i to FSS category j JRC-AL – Bonn on 10.03.2004

  13. GIM approach SOIL MAP,DEM NUTS 2 CORINE allocationalgorithm NUTS 3 (or gridcell) JRC-AL – Bonn on 10.03.2004

  14. Ranking of differences FSS-CLC • for all classes except rough grazing • Determination of the fraction of temporary pasture to be distributed to permanent pasture: • when CLC overestimates arable land together with an underestimation of pasture, the possibility to allocate part of (211+212) to (231) up to a max. of 25% is evaluated • Distribution of complex classes successive determination of coefficients JRC-AL – Bonn on 10.03.2004

  15. Redistribution of complex classes JRC-AL – Bonn on 10.03.2004

  16. Interaction of permanent pasture and rough grazing if FSS (pasture) is bigger than CLC (pasture) • the coefficient “a” for allocating part of temporary pasture (D18) to permanent pasture (F01) will be evaluated • if F01 < class 2.3.1. • up to a maximum value of “a” that FSSarable CLCarable • up to a maximum value of “a” that FSSarable CLCarable JRC-AL – Bonn on 10.03.2004

  17. Parameters used for tuning • class 2.4.2. (complex cultivation pattern) • a minimum of 25% must be used for “pasture” • class 2.4.3. (Land principally occupied by agr. with sign. areas of natural vegetation) • a maximum of 75% can be used to match agricultural land. • the share of natural vegetation can be used to match rough grazing • Maximum tolerable error at district-level • the matching of FSS and CLC can be stopped if the error is <3%, when the addition of new classes makes the distribution too uncertain • class 2.1.1. • a maximum of 25% can be used to match pasture land JRC-AL – Bonn on 10.03.2004

  18. Problems • Assuming pure classes • also pure classes have a proportion of other land uses • Assumptions on coefficients and sequence arbitrary • methodology will have to be re-checked • Geo-referencing with soil map and digital elevation model • probabilities for aggregated classes only • Time difference between data sets • “buy” synchrony with statistical consistency JRC-AL – Bonn on 10.03.2004

  19. “Solution” • Use of updated data • “Corrected” Corine 1990 landcover map • Corine 2000 land cover map as it becomes available • Use of LUCAS to determine probabilities of a certain land use in a land cover class • clustering of LUCAS points • co-location problems • derive matching function between Corine and LUCAS land cover classes • Use of physical parameters • determine relationships between the occurrence of • disaggregated arable classes and • soil (texture, chemistry), climate (temperature, precipitation, vegetation period), elevation (absolute elevation, slope) JRC-AL – Bonn on 10.03.2004

  20. Gallego, 2003 Co-location problem JRC-AL – Bonn on 10.03.2004

  21. Proposed approach LUCAS SOIL MAP,DEM, climate NUTS 2 CORINE allocationmap+algorithm GRID JRC-AL – Bonn on 10.03.2004

  22. 5 or 10 km grid • landscape assessment: complexity of landscape • 2.5 or 1 km grid 1.3·106 km2 x 1 min = 2.5 years What is the target grid / map ? • Nested approach for DNDC? • Other maps according to the results of WP9 • Catchments ? • homogeneous units ? JRC-AL – Bonn on 10.03.2004

  23. CAPRI Definition of parameters to be disaggregated WP8 Allocation of land use into the land cover map CAPRI-indicators disaggregated (grid) CAPRI-indicators disaggregated (map) WP9 WP10 Definition of target scale and target map WP10 Simulation of nutrient cycling WP9 Landscape assessment indicators JRC-AL – Bonn on 10.03.2004

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