The HSMU approach in CAPRI-DYNASPAT (Homogeneous Spatial Mapping Units)

Transcription

1 CAP Regional Impact Assessment - DYNAmic and SPATial dimension The HSMU approach in CAPRI-DYNASPAT (Homogeneous Spatial Mapping Units) Adrian Leip, Giulio Marchi Climate Change Unit / Joint Research Centre Markus Kempen University of Bonn CAPRI-DYNASPAT Final Meeting February 27 th,

2 Motivation and Objectives HSMU Approach Background CAPRI Interactions between classical goals of agricultural policy and environmental side-effects at aggregate regional level Effect of agricultural activities on the environment is differentiated by differences in soil type, land cover and climate Land cover maps based on satellite images (CORINE, PELCOM) usually do not differentiate crops Link to bio-physical models Bio-physical models require detailed land use information Complex processes linked to politically relevant scenarios Forecast environmental effects on small scale units (1x1 km) 2

3 HSMU Approach Rationale Establish a European wide land use map ( crop level) Detailed forecast of environmental impacts (of political programs) Homogeneous Spatial Mapping Units Assuming similar conditions for crop Ensuring higher precision on linking cultivation practices and environmental conditions Spatial ground resolution of 1km Extent: EU15 + EU10+3 3

4 Homogeneous Spatial Mapping Units Similar environmental conditions (leading to high or low emissions of Green-House Gases or other pollutants) Regions belonging to the same FSS NUTS 2/3 - Farm Structure Survey 2000, Nomenclature of Territorial Units for Statistics (administrative data) CORINE 2000 land cover/use class (land cover data) SMU - Soil Mapping Unit; European Soil Database V2.0 (soil data) Slope class; CCM DEM 250, 2004, Catchment Characterisation and Modelling (slope data) 4

5 HSMU Component Layers FSS NUTS CORINE FSS REGIONS SOIL NUTS MAPPING LAND REGIONS SLOPE USE/COVER UNITS (NUTS2/3) (SMU) 2000 (NUTS2/3) + CORINE LAND USE/COVER SOIL MAPPING UNITS (SMU) + SLOPE 5

6 HSMU Creation FSS NUTS REGIONS (NUTS2/3) CORINE LAND USE/COVER 2000 SOIL MAPPING UNITS (SMU) SLOPE HSMU 1x1km Year 2000 Slope classes (deg)

7 HSMU Codes Reclassed maps of FSS districts 3 digits CORINE land cover/use 2 digits SMU 3 digits slope class 1 digits HSMU ID ((((((FSSNUTS*100)+LC)*1000)+SOIL)*10)+SLOPE) 9-digit HSMU code N U T L C S M U S 7

8 HSMU Polygons EU15 1,452,014 singlepart 143,535 HSMUs EU ,644 singlepart 63,904 HSMUs One consolidated dataset but bordering geographical issues spatial analysis issues 8

9 Sicily HSMU Example 11,880 singlepart polygons 2,178 multipart HSMUs 9

10 HSMU Class Example and Stats no agricultural use allowed CODE CORINE LAND USE/COVER CLASSES 111 CONTINIOUS URBAN FABRIC 112 DISCONTINUOUS URBAN FABRIC 121 INDUSTRIAL OR COMMERCIAL UNTS 122 ROAD AND RAILNETWORKS AND ASSOCIATED LAND 123 PORT AREAS 124 AIRPORTS 131 MINERAL EXTRACTION SITES 132 DUMP SITES 133 CONSTRUCTION SITES 141 GREEN URBAN AREAS 142 SPORT AND LEISURE FACILITIES 211 NON-IRRIGATED ARABLE LAND 212 PERMANENTLY IRRIGATED LAND 213 RICE FIELDS 221 VINEYARDS 222 FRUIT TREES AND BERRY PLANTATIONS 223 OLIVE GROVES 231 PASTURES 241 ANNUAL CROPS ASSOCIATED WITH PERMANENT CROPS 242 COMPLEX CULTIVATION PATTERNS 243 LAND PRINCIPALLY OCCUPIED BY AGRICULTURE 244 AGRO-FORESTRY AREAS 311 BROAD-LEAVED FOREST 312 CONIFEROUS FOREST 313 MIXED FOREST 321 NATURAL GRASSLAND 322 MOORS AND HEATHLAND 323 SCLEROPHYLLOUS VEGETATION 324 TRANSITIONAL WOODLAND-SHRUB 331 BEACHES, DUNES, AND SAND PLAINS 332 BARE ROCK 333 SPARSELY VEGETATED AREAS 334 BURNT AREAS 335 GLACIERS AND PERPETUAL SNOW 411 INLAND MARSHES 412 PEATBOGS 421 SALT-MARSHES 422 SALINES 423 INTERTIDAL FLATS 511 WATER COURSES 512 WATER BODIES 521 COASTAL LAGOONS 522 ESTUARIES 999 UNCLASSIFIED LAND SURFACES 523 SEA AND OCEAN Nr. of HSMUs Nr. of HSMUs m2 2 km 2 m2 >2-10 km 2 Size class m2 2 km 2 >2-10 km 2 Size class > km 2 EU15 > km 2 m2 m2 m2 > km 2 > km 2 > 1000 > km 2 EU10+3 > km 2 >

11 Land Use/Land Cover Area frame statistical Survey Observation points of the (LUCAS) Main land cover/use survey raster: 18x18 km with 10 subsampling units Field survey at ~100,000 observation points in EU15 First survey in 2001 (UK 2002) 57 land cover classes (including 34 agricultural classes) Data Source: European Commission (2003a): The Lucas survey. European statisticians monitor territory.. Theme 5: Agriculture and fisheries. Series Office for Official Publications of the European Communities, Luxembourg, pp 11

12 LUCAS Variables Parameters calculated per each LUCAS sampling unit (average, minimum and maximum value per HSMU) Set of Soil Type (Clustering according to WRB Soil Code) Drainage (yes/no) Stones (yes/no) Slope (continuous value) Elevation (continuous value) Rainfall (continuous value) Sum of temperature (>5 deg C, continuous value) 12

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14 CAP Regional Impact Assessment - Dynamic and Spatial dimension CAPRI-DYNASPAT Disaggregation Data Validation and Spatial Analysis Adrian Leip, Giulio Marchi Climate Change Unit / Joint Research Centre Markus Kempen University of Bonn CAPRI-DYNASPAT Final Meeting February 27 th,

15 CAPRI Disaggregation Classes TOMA SUGB CITR FODD OVEG ROOF LOLIV CERE FLOW SUNF LTWIN ROOT SWHE LRAPE NURS CER2 DWHE SOYA OCRO DRYC BARL LTEXT GRAS SUPO RYEM TOBA GRAE NEMA OATS OIND GRAI PERM LMAIZ PULS FORR SCRO PARI LFRUI SHRU OARA OCER OFAR OTHER NONA POTA LFALL ARAB UAAR 15

16 Disaggregation Data 16

17 Disaggregation Data 17

18 Disaggregation Data 18

19 Error Assessment: European Scale Disaggregation of NUTS-2 statistics and comparison with NUTS-3 statistics, where available 40 Error in the CAPRINUTS vs. Agricultural area of the CAPRINUTS 35 % of Misclassified Agricultural Area y = x R 2 = % of Agricultural Area in the CAPRINUTS % of Misclassified NUTS 2 Crop Area

20 NUTS-3 Misclassified Area (UAA % in NUTS-2 ES41) Single Crop Soft Wheat Durum Wheat Barley Rye Oats Maize Other Cereal Fallow Land Rice Sunflower Soya Texture Crops Pulses Other Crops Potatoes Sugar Beet Root Crops Rape Nurseries Tobacco Other Industrial Toma. and Other Veg. Flowers Citrus Trees Fruit Trees Olive Trees Vineyards Grassland Fodder production Cereals Fallow Land Group Rice, Oilseeds Root Crops/Rape Industrial Crops Perm. Crops Grassland and Fodder Arable Class Perm. Crops Grassland and Fodder Misclassified at NUTS-2: Single crops: 17% Crop groups: 11% Crop classes: 8% Total UAA: 4% Leveling out within groups Mainly caused by grassland 20

21 Error Assessment: Regional/Local scale Example: Rice in Mortara commune (Pavia province, northern Italy) Location of the Mortara Commune CORINE LC 100m Resolution CORINE LC resampled 1km no rice rice CORINE LC 100 m + Regional Map Disaggr. Result 1km + Regional Map CLC yes ERSAF no CLC yes ERSAF yes 60-70% 70-80% CLC no ERSAF yes CLC no ERSAF no 80-90% % ERSAF: Regional Office for Agriculture and Forestry 21

22 CAPRI-Solagro (France) Solagro: crops diversity indicator (1-10) at farm level Application to CAPRI crop data Aggregation at commune level ( 37,000 polygons) Comparison between Solagro data and Solagrized CAPRI 22

23 Conclusions Output: 1km resolution land use map at EU28 level Extensive land use types list Validations are comforting For many applications: crops aggregation further reduces uncertainties The approach offers good opportunities for expansion 23

24 Thanks Adrian Leip, Giulio Marchi Climate Change Unit / Joint Research Centre Markus Kempen University of Bonn CAPRI-DYNASPAT Final Meeting February 27 th,