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Exploitation of data from the Community's LUCAS survey Lot 2 State of Progress Gerd Eiden, LANDSIS g.e.i.e. Eurostat Working Group Agri-Environmental Indicators 3rd and 4th December 2002. Lucas Lot 2: Aim and Objectives.
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Exploitation of data from the Community's LUCAS survey Lot 2 State of Progress Gerd Eiden, LANDSIS g.e.i.e. Eurostat Working Group Agri-Environmental Indicators 3rd and 4th December 2002
Lucas Lot 2: Aim and Objectives • To propose and quantify concrete (agri-) environmental indicators according to COM(2001) 144 and based on LUCAS data • To elaborate recommendations for improved LUCAS survey in 2003
Focus of LUCAS data analysis (2002): Methodological and conceptual questions: • Indicator 24: Resource depletion: Land Cover change ------------------------- • Indicator 35: Impact on landscape diversity (Indicator 32: Landscape state (group b) - LU Matrix) ------------------------- • Indicator 33: Impact on habitats and biodiversity ------------------------- • Indicator 23: Soil erosion ------------------------- • Indicator proposals on Agri-environmental indicators based on LUCAS Phase 2
Indicator 35: Impact on landscape diversity LUCAS: • Segment (PSU) • Transect Approach: • Landscape metrics to capture spatial properties of the segment • Method of M.F. Slak Crucial Question: • Are 10 points (SSU’s) adequate?
Indicator 35: Impact on landscape diversity • Simulation of LUCAS segments using French TERUTIdata • How are changes reflected in LUCAS compared to TERUTI?
Indicator 35: Impact on landscape diversity Results: • From a conceptual point of view landscape metrics can be applied on just 10 points • Compared to TERUTI, LUCAS segments do not necessarily reflect the identical structural properties, but the regional pattern is similarly reflected • LUCAS segments “over” pronounce changes • Segment design: indications that a LUCAS segment composed of 4 lines (20 SSU’s) would be a compromise
Indicator 35: Impact on landscape diversity Proposal: (1) Characterisation of structural properties of each PSU by means of four different indices: • Number of land cover classes (richness) • Shannon Diversity Index (diversity) • Interspersion and Juxtaposition Index (spatial arrangement) • INT (heterogeneity/homogeneity) (2) Changes of indices values in time as indication of structural changes (3) Further development of method of M.F. Slak
Indicator 33. Impact on habitats and biodiversity (group c) Indicator concept: • Linear features as elements with several environmental functions: buffer and habitat • State and change in linear habitats (boundary features in agricultural landscapes) Potential data source: • LUCAS transect data
Indicator 33. Impact on habitats and biodiversity (group c) Approach: • Analysis of sequences of land cover codes and linear features and their “environmental” significance Transect Code sequence: Ba 2 Ba (arable land) (green linear) (arable land) SSU N° 12 SSU N° 15 SSU N° 14 SSU N° 13 SSU N° 11 Transect sequence …. Ba – 2 – Ba ….
Indicator 33: Impact on habitats and biodiversity (group c) Example: “environmental beneficial” sequence (good agricultural practice): • Ba – 1 or 2 (arable land - green linear features) • Number in 2001: 4291 Sequence with negative environmental effects: • Ba – 5 or 6 (arable land – water courses) • Number in 2001: 2794
Indicator 33: Impact on habitats and biodiversity (group c) Proposal: • Identification and quantification of environmentally relevant transect sequences • Observation of changes in time • Characterisation of transects with regards to presence of linear features (sequences) • Observation of changes in time
Indicator 24: Resource depletion: Land Cover change Indicator concept: • Matrix of changes in land cover (LC) in order to track developments Proposal: • Post classification (combination and aggregation of land use/land cover) • Establishing land cover/land use matrices • Analysis of stock and flows
Indicator 24: Resource depletion: Land Cover change Creation of a post classification by combining Land Cover and Land Use Codes: Land Cover Land Use Combination U11 pastures and meadows E01 U36 public parks U37 residential gardens • Fully exploitation of LUCAS data • Added value for change analysis
Indicator 24: Resource depletion: Land Cover change • Analysis of LC/LU flows • Conversion • Modification • Extensification/ Intensification • Afforestation • Deforestation • Development • Reclamation
Indicator 23: Soil Erosion Indicator concept: • Risk assessment (vulnerability, potential soil erosion risk) LUCAS information: • Presence of visible soil erosion damages during field observation • Rills • Gullies • Accumulation
Indicator 23: Soil Erosion First results: • Validation show that field observation method on visible soil erosion damages is a feasible approach • Consistency to be improved • Limitation: • non-recurring observation of sporadic soil erosion events • Time of observation in May/June • Incomplete/partial picture about the current state due Cartography: Eurostat
Indicator 23: Soil Erosion Best practice: • repeated observation according to occurrence of rainfall events and crop calendar Crucial question: • How can the incomplete information provided be used? Proposals are currently under discussion: • Long term monitoring of measures against soil erosion • Validation of soil erosion models • Link between Farmers interview – Soil erosion observation • Integration of soil erosion issue in Farmers Interview
Elaboration of indicator proposals based on the Farmers Interview Complementary information for the following Agri-environmental indicators: • Regional levels of good farming practice (indicator 2, group b) • Quantities of nitrogen (N) and phosphate (P) fertilisers used (indicator 8, group a) • Soil surface nutrient balance, incl. indicator 8: fertiliser use (indicator 18, group a) • Consumption of pesticides (group a/c, indicator 9) • Land use: cropping/livestock patterns (group a/c indicator 13) • Area under nature protection (indicator 4, group b)
Elaboration of indicator proposals Tasks: Review and assessment of the questionnaire regarding information return for • Indicators concerned • on agricultural practices and their positive/negative effect on the environment Preliminary Results: A set of modifications/ precision of questions are proposed in order to retrieve concrete information on “environmentally friendly” agricultural practices such as: • Farming intensity (based on the cultivated crops, rotation system, • Nutrient balance • Framing practices (conservation tillage, drilling etc, pesticide usage. )
Preliminary Conclusions • LUCAS provides harmonised and precise data on land cover and land use at EU level and thus a unique data source for: • Indicator 24: Resource depletion: Land Cover Change • Indicator 32: Landscape State - LU Matrix • Indicator 35: Impact on Landscape Diversity • … complementary information for: • Indicator 23: Soil Erosion • Indicator 33: Impact on habitats and biodiversity • The farmers interview offers a flexible tool to retrieve information on agricultural practices which is complementary to FSS data. • Adaptations and modifications for improvement of the LUCAS survey and farmers interview necessary.