land statistical information systems exploitation of data from the community's lucas survey lot...

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


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?



•Simulation of LUCAS segments using French TERUTI data•How are changes reflected in LUCAS compared to TERUTI?



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



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 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)


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


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



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 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



• 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



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



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.

land statistical information systems exploitation of data from the community's lucas survey lot...

Documents

data indicator

landscape diversity

landscape diversity

indicator proposals

lucas data analysis

lucas phase

land cover change

land cover codes