Marta Pérez-Soba

Han Naeff

Janneke Roos

Wim Nieuwenhuizen

Alterra, The Netherlands

Haarlem, 22nd March 2002

Use of national data to improve the localisation of livestock

Where are the different livestock types geographically located?

Where are the livestock systems located?

Biophysical features

Land cover: CORINE 43 Others: altitude, soils, climate

Selection land cover classes

Allocation maps (European approaches)

Validation: geo-referenced national/regional databases

Conclusions for the ELPEN system

CORINE Land cover

Scale 1:100.000, 43 classesMinimum mapping element: 25 ha

Validation ofEuropean approach 5

From the 43 CORINE classes we selected 8 classes:– pastures– land principally occupied by agriculture– annual crops associated with permanent crops– complex cultivation patterns– moors and heath lands– natural grasslands– agro-forestry areas– non-irrigated arable land (10%)

For the validation we distinguished 4 land-dependent livestock categories

Livestock category Livestock Units (LU)

Dairy cows 1.0

Other cows (suckler) 0.8

Other bovine 0.4; 0.7; 0.8; 1.0

Sheep & Goats 0.1

Example: The Netherlands

Questions to be answered

• How (in)accurate is the allocation procedure of approach 5:

• Inaccuracy caused by chosen regional level?

• Inaccuracy caused by chosen land cover classes?

By applying the ELPEN algorythm of approach 5 to the same Dutch data, we ruled out inaccuracies caused by different data sets

Validation (in)accuracy regional levelGeo-referenced Giab-2000 farm data

Data aggregated grid 5x5

according to ELPEN algorythm

Giab-2000

Grid 5x5 km2

Our reference

Data aggregated grid 5x5 Data aggregated at three regional levels

Municipalities (500)

Agricultural regions (66)

Province (12)

Levels we used for validation

Provincial levelAgricultural regionsMunicipality level

Our reference maps: GIAB 2000Geo-referenced Giab-2000 farm data : aggregated at 5x5 km grid

Nr. of livestock farms:1 - 1011 - 5051 - 100101 - 212no data

Nr. of dairy cows LU:1 - 10

10 - 30

30 - 60

60 - 100

100- 200

200- 350

350- 600

600-2500

2500-5000

Inaccuracy caused by regional level: dairy cows

Province (12)

Data aggregated 5x5 km grid

according to ELPEN algorithm

Data aggregated at regional levelsGeo-referenced

Giab-2000 farm data

Giab-2000

Grid 5x5 km2

Our reference Municipalities (500)

Nr. of dairy cows LU:1 - 10

10 - 30

30 - 60

60 - 100

100- 200

200- 350

350- 600

600-2500

2500-5000

Results comparison GIAB - Elpen algorithm

Green: too many dairy cows in ELPEN approach (-2000 - -50 LU) Gray : approximately correctRed : too few dairy cows in ELPEN approach (50 - 2000 LU)

Dairy: aggregated / Province Dairy: aggregated / Municipality

Results comparison GIAB - Elpen algorithm

Green: too many sheep in ELPEN approach (-400 - -10 LU)Gray : approximately correctRed : too few sheep in ELPEN approach (10 - 400 LU)

Sheep/goat: aggregated / Province Sheep/goat: aggregated / municipality

Validation of Corine classesProcedure:

• Overlay GIAB farm data with Corine 100 x 100m (derived from polygon map with smallest area of 25 ha)

• Analyse which Corine classes are relevant

• Define a methodology to improve localisation:

• Calculate livestock density / Corine class / province

• Derive relative attractivity for the different livestock types of each Corine class per province

• Derive better rules for localisation in ELPEN

Overlay GIAB farm data with CORINE 100 x 100m

• Farm 203

• nr of dairy cows: 40

• nr of sheeps: 100

• fodder area: 25 ha

• pasture area: 30 ha

• cadastral area: 60 ha

• etc

Example of error due to lack of data on location of farm land:

In Groningen is only onesmall area of Annual crops.Most of the farm land of the3 farms within this area might be outside this Corine class, but is computed as being inside.

Overlay GIAB farm data with CORINE 100 x 100m

Error due to use of farm address instead of location of farm land(not available yet):Many (post) addresses of farms are in urban areas

Livestock density (LU/ha) per Corine class per province

Livestock type Corine class Groningen Friesland Drenthe Overijssel Flevoland Gelderland Utrecht N-Holland Z-Holland Zeeland N-Brabant LimburgDairy cows Pastures 0.7 0.9 0.6 0.9 0.6 0.6 0.8 0.5 0.7 0.2 0.6 0.3

Land pp occ agric 0.3 0.7 0.7 0.4Complex cultivation 0.4 0.6 0.7 0.8 0.5 0.2 0.2 0.6 0.3Non-irrigated arable 0.2 0.3 0.2 0.6 0.1 0.5 0.2 0.1 0.1 0.2 0.2

Other cows Pastures 0.03 0.03 0.06 0.07 0.01 0.06 0.05 0.05 0.04 0.01 0.06 0.06Land pp occ agric 0.04 0.07 0.06 0.00Complex cultivation 0.03 0.03 0.08 0.05 0.02 0.01 0.07 0.07 0.06Non-irrigated arable 0.01 0.01 0.02 0.05 0.00 0.05 0.02 0.01 0.02 0.03 0.03 0.04

Other bovine Pastures 0.4 0.5 0.4 0.6 0.3 0.7 0.6 0.3 0.4 0.1 0.5 0.3Land pp occ agric 0.2 0.6 0.6 0.4Complex cultivation 0.3 0.5 0.9 0.6 0.3 0.1 0.2 0.6 0.3Non-irrigated arable 0.1 0.2 0.1 0.5 0.1 0.5 0.1 0.1 0.1 0.2 0.3

Sheep&goats Pastures 0.08 0.09 0.03 0.04 0.02 0.05 0.08 0.15 0.08 0.03 0.05 0.02Land pp occ agric 0.02 0.03 0.04 0.06Complex cultivation 0.03 0.04 0.05 0.06 0.19 0.04 0.04 0.04 0.03Non-irrigated arable 0.03 0.08 0.01 0.02 0.01 0.04 0.06 0.03 0.02 0.03 0.03

Legend bold characters large enough area to be representative (> 10.000 ha)normal characters indicative (area <10.000 ha)

highest density per livestock type per provincelowest density per livestock type per province

Conclusion: Pastures: mostly highest density per livestock type per province Land pp occ agr: in most provinces too small area, density in between Complex cult pt: In some provinces high density, in others low Non-irr ar land: mostly lowest density per livestock type per province

<------ Provinces ----->

Livestock density (LU/ha) per Corine class per province

Livestock type Corine class Groningen Friesland Drenthe Overijssel Flevoland GelderlandDairy cows Pastures 0.7 0.9 0.6 0.9 0.6 0.6

Land pp occ agric 0.3 0.7 0.7Complex cultivation 0.4 0.6 0.7Non-irrigated arable 0.2 0.3 0.2 0.6 0.1 0.5

Other cows Pastures 0.03 0.03 0.06 0.07 0.01 0.06Land pp occ agric 0.04 0.07 0.06Complex cultivation 0.03 0.03 0.08Non-irrigated arable 0.01 0.01 0.02 0.05 0.00 0.05

Other bovine Pastures 0.4 0.5 0.4 0.6 0.3 0.7Land pp occ agric 0.2 0.6 0.6Complex cultivation 0.3 0.5 0.9Non-irrigated arable 0.1 0.2 0.1 0.5 0.1 0.5

Sheep&goats Pastures 0.08 0.09 0.03 0.04 0.02 0.05Land pp occ agric 0.02 0.03 0.04Complex cultivation 0.03 0.04 0.05Non-irrigated arable 0.03 0.08 0.01 0.02 0.01 0.04

Legend bold characters large enough area to be representative (> 10.000 ha)normal characters indicative (area <10.000 ha)

relative high densityrelative low density

Dairy cowsand

Sheep area

Dairy/Bovine

area

Dairy/Bovine

area

Livestock type Corine class Utrecht N-Holland Z-Holland Zeeland N-Brabant LimburgDairy cows Pastures 0.8 0.5 0.7 0.2 0.6 0.3

Land pp occ agric 0.4Complex cultivation 0.8 0.5 0.2 0.2 0.6 0.3Non-irrigated arable 0.2 0.1 0.1 0.2 0.2

Other cows Pastures 0.05 0.05 0.04 0.01 0.06 0.06Land pp occ agric 0.00Complex cultivation 0.05 0.02 0.01 0.07 0.07 0.06Non-irrigated arable 0.02 0.01 0.02 0.03 0.03 0.04

Other bovine Pastures 0.6 0.3 0.4 0.1 0.5 0.3Land pp occ agric 0.4Complex cultivation 0.6 0.3 0.1 0.2 0.6 0.3Non-irrigated arable 0.1 0.1 0.1 0.2 0.3

Sheep&goats Pastures 0.08 0.15 0.08 0.03 0.05 0.02Land pp occ agric 0.06Complex cultivation 0.06 0.19 0.04 0.04 0.04 0.03Non-irrigated arable 0.06 0.03 0.02 0.03 0.03

Legend bold characters large enough area to be representative (> 10.000 ha)normal characters indicative (area <10.000 ha)

relative high densityrelative low density

Livestock density (LU/ha) per Corine class per province

Other cowsarea

Bovinearea

Livestockpasture

area

Dairy +sheeparea

What can we do with these results?

From the overlay of national data (2000) with Corine we know:

• The approximate livestock density of each corine class per livestock type, per province

From this we can derive:

• The relative attractivity of each corine class per livestock type, per province

• Restrictions on the nr of LU/ha to be allocated per Corine class per livestock type, per province

Attractivity and Restrictions are input for the new allocation procedure: approach 6, that has been implemented in the ELPEN system

New allocation procedure: Approach 6: Competition for grassland

Allocation procedure Approach 6

Climate map

Altitude map

Corine land use map Attractivity map bovine

Attractivity map sheep

Attractivity map dairy

National statisticaldata on livestock

restriction map bovine

restriction map sheep

restriction map dairy

Knowledge rules

European statisticaldata on livestock

Allocation map bovine

Allocation map sheep

Allocation map dairyAllocation

proc. 6