Post on 13-Dec-2015
LAND Statistical Information Systems
Exploitation of data from the
Community's LUCAS surveyLot 2
State of Progress
Gerd Eiden, LANDSIS g.e.i.e.
Eurostat Working Group Agri-Environmental Indicators3rd and 4th December 2002
LAND Statistical Information Systems
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
LAND Statistical Information Systems
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
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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?
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Indicator 35: Impact on landscape diversity
•Simulation of LUCAS segments using French TERUTI data•How are changes reflected in LUCAS compared to TERUTI?
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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
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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
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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)
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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 sequence…. Ba – 2 – Ba ….
SSUN° 11
SSUN° 12
Transect Code sequence: Ba 2 Ba
SSUN° 13
(arable land) (green linear) (arable land)
SSUN° 14
SSUN° 15
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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
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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
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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
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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
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Indicator 24: Resource depletion: Land Cover changelevel 1 level 2 Number of
SSU’s% from
total SSU’s
I. Artificial land I.1 built up and non built up areas
2568 3,0
I.2 transport infrastructure 1806 2,1
I.3 artificial green 2255 2,6
II. Agricultural land II.1 arable land 14298 16,6
II.2 permanent crops 3334 3,9
II.3 grassland 11302 13,1
II.4 fallow land 2163 2,5
II.5 mixed agricultural land
207 0,2
III. Woodland III.1 broadleaved 7654 8,9
III.2 coniferous 14769 17,1
III.3 Mixed 6226 7,2
IV. Semi natural land
IV.1 woodland 4122 4,8
IV.2 shrubland 5579 6,5
IV.3 grassland 1076 1,2
IV.4 wetland 3056 3,5
IV.5 bare land 2290 2,7
V. Water bodies 3564 4,1
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Indicator 24: Resource depletion: Land Cover change
• Analysis of LC/LU flows
• Conversion • Modification
• Extensification/ Intensification
• Afforestation • Deforestation• Development• Reclamation
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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
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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
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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
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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)
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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. )
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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.