wp 8 capri gis link
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WP 8 CAPRI GIS Link. Agricultural Policy – The Dynamic and Spatial Dimension ( CAPRI-DynaSpat ). Relevant spatial datasets for the disaggregation of CAPRI-DynaSpat parameters Description - Use - Constraints. Renate Köble and Adrian Leip. SPATIAL DATA SETS. LAND COVER/LAND USE MAPS - PowerPoint PPT PresentationTRANSCRIPT
CAPRIDynaSpat, Bonn 10.3.2003
Agricultural Policy – The Dynamic and Spatial Dimension (CAPRI-DynaSpat)
WP 8 CAPRI GIS Link
Relevant spatial datasets for the disaggregation of CAPRI-DynaSpat parameters
Description - Use - Constraints
Renate Köble and Adrian Leip
CAPRIDynaSpat, Bonn 10.3.2003
LAND COVER/LAND USE MAPSdetermine mainly the “spatial resolution” of the disaggregation
LAND USE/COVER AREA FRAME STATISTICAL SURVEYcan be used to create a decision matrix how to allocate the statistical
agricultural activity data and model outputs to the land cover classes
SPATIAL DATA ON ELEVATION, BIOGEOGRAPHICAL REGIONS AND SOIL
deliver additional information to allocate statistical agricultural activity data and model outputs especially for complex land cover classes
SPATIAL DATA SETS
CAPRIDynaSpat, Bonn 10.3.2003
CORINE (Coordination of Information on the Environment) land cover mapping program was proposed in 1985 by the EU Commission to satisfy the need of precise and easy accessible information on land cover in Europe
CLC describes land cover (and partly land use) according to a nomenclature of 44 classes organised hierarchically in 3 levels
Elaborated based on the visual interpretation of satellite images and ancillary data (aerial photographs, topographic maps etc.)
Acquisition period of satellite images 1985 to 1995
Smallest surface mapped: 25 ha. Scale of the output product 1:100 000
The 100 m2 grid data set is available for the CAPRI-DynaSpat area of interest except Sweden
For Switzerland a national land cover map is available with classes corresponding to Level II of the CORINE classification system
CORINE LAND COVER/LAND USE 1990
CAPRIDynaSpat, Bonn 10.3.2003
An update of the CORINE Land cover database for the year 2000 is under processing
The update will be more time consistent (satellite images from 2000 +/-1year)
Improvement of the geometric accuracy
CORINE LC90 will be revised (land cover classes and geometry will be reviewed)
Maps with land cover changes from “1990” to 2000 will be produced
Currently data is available for Ireland, Netherlands, Latvia, Luxembourg and Malta
Data for Lithuania, Poland, Spain, Sweden, Italy might be available before summer
the aim is to finish 80% of EU25 (+ Bulgaria, Croatia, Romania) by the end of 2004
CORINE LAND COVER/LAND USE 2000
CAPRIDynaSpat, Bonn 10.3.2003
CORINE CLASSIFICATIONLevel1 Level2 Level3Artificial surfaces Urban fabric Continuous urban fabric
Discontinuous urban fabricIndustrial, com m ercial and transport units Industrial or com m ercial units
Road and rail netw orks and associated landPort areasAirports
Mine, dum p and construction sites Mineral extraction sitesDum p sitesConstruction sites
Artificial, non-agricultural vegetated areas Green urban areasSport and le isure facilities
Agricultural areas Arable land Non-irrigated arable land
Perm anently irrigated land
Rice fieldsPerm anent crops Vineyards
Fruit trees and berry plantationsOlive groves
Pastures Pastures
Heterogeneous agricultural areas Annual crops associated w ith perm anent cropsCom plex cultivation patternsLand principally occupied by agriculture, w ith significant areas of natural vegetation
Agro-forestry areasForest and sem i natural areas Forests Broad-leaved forest
Coniferous forest
Mixed forest
Scrub and/or herbaceous vegetation associations Natural grasslands
Moors and heathlandSclerophyllous vegetationTransitional w oodland-shrub
Open spaces w ith little or no vegetation Beaches, dunes, sands
Bare rocksSparsely vegetated areasBurnt areasGlaciers and perpetual snow
Wetlands Inland w etlands Inland m arshes
Peat bogsMaritim e w etlands Salt m arshes
SalinesIntertidal flats
Water bodies Inland w aters Water courses
Water bodiesMarine w aters Coastal lagoons
EstuariesSea and ocean
CAPRIDynaSpat, Bonn 10.3.2003
CORINE LC IN THE BONN AREA
CAPRI DYNASPATKICK-OFF MEETING
CAPRIDynaSpat, Bonn 10.3.2003
The Pan-European Land Cover Monitoring (PELCOM) project was carried out 1996-99. Funded as a shared cost action within FP4.
The PELCOM land cover map distinguishes 14 land cover classes (4 agricultural classes)
Classification is based on 1km resolution satellite images (NOAA AVHRR) and ancillary data as e.g. topographic information, rivers/lakes/coastlines
Acquisition period of satellite images 1997
Covers Europe and parts of Russia and the Middle East
PELCOM LAND COVER/LAND USE
CAPRIDynaSpat, Bonn 10.3.2003
Level1 Level2 Level3Artificial surfaces Urban fabric Continuous urban fabric
Discontinuous urban fabricIndustrial, com m ercial and transport units Industrial or com m ercial units
Road and rail netw orks and associated landPort areasAirports
Mine, dum p and construction sites Mineral extraction sitesDum p sitesConstruction sites
Artificial, non-agricultural vegetated areas Green urban areasSport and leisure facilities
Agricultural areas Arable land Non-irrigated arable land
Perm anently irrigated land
Rice fieldsPerm anent crops Vineyards
Fruit trees and berry plantationsOlive groves
Pastures Pastures
Heterogeneous agricultural areas Annual crops associated w ith perm anent cropsCom plex cultivation patternsLand principally occupied by agriculture, w ith significant areas of natural vegetation
Agro-forestry areasForest and sem i natural areas Forests Broad-leaved forest
Coniferous forest
Mixed forest
Scrub and/or herbaceous vegetation associations Natural grasslands
Moors and heathlandSclerophyllous vegetationTransitional w oodland-shrub
Open spaces w ith little or no vegetation Beaches, dunes, sands
Bare rocksSparsely vegetated areasBurnt areasGlaciers and perpetual snow
Wetlands Inland w etlands Inland m arshes
Peat bogsMaritim e w etlands Salt m arshes
SalinesIntertidal flats
Water bodies Inland w aters Water courses
Water bodiesMarine w aters Coastal lagoons
EstuariesSea and ocean
Urban areas
Rainfed arable land
Irrigated arable land
Perm anent crops
Grassland
Deciduous forestConiferous forest
Mixed forest
Shrubland
Barren land
Perm anent Ice&Snow
Wetlands
Inland w aters
Sea
CORINE/PELCOM LC CLASSIFICATIONCORINE PELCOM
CAPRIDynaSpat, Bonn 10.3.2003
CORINE AND PELCOM LAND COVER
Rhein-Sieg-Kreis
PasturesComplex cultivation patternLand princip. occ. by agric. & sign areas of nat. veg.Not irrigated arable landForestUrban area
Grassland
CAPRIDynaSpat, Bonn 10.3.2003
LAND COVER DATA SETS AVAILABLE FOR THE CAPRI-DynaSpat AREA
CAPRIDynaSpat, Bonn 10.3.2003
COMPARISON OF CLC90 AND FARM STRUCTURE SURVEY DATA
Kayadjanian et al. (2001)
CLC90 11 agricultural classes, FSS 42 classes
RECLASSIFIED STATISTICS
LANDCOVER MAP
CAPRIDynaSpat, Bonn 10.3.2003
THE POSSIBLE REASONS FOR THE DEVIATIONS ARE MANYFOLD
Data is related to different time spans (FSS 1990, CLC 1985-95)
Per definition CLC omits areas <25 ha, therefore non irrigated arable land may be included to some extend also in other CLC classes as e.g. “Complex cultivation patterns with significant area of natural vegetation” or “Grassland”
FSS classes can not be exactly regrouped in the CLC classes due to different classification systems (e.g. within irrigated land)
Photo-interpretation inaccuracy for CLC
Errors in the FSS
CAPRIDynaSpat, Bonn 10.3.2003
The Land Use/Cover Area Frame Statistical Survey (LUCAS) has been launched by Eurostat and DG Agri* to:
obtain harmonised data (unbiased estimates) at EU 15 level of the main Land Use / Cover areas and changes.
evaluate the strengths and weaknesses of a point area frame survey as one of the pillars of the future Agriculture Statistical System (area frame means that the observation units are territorial subdivisions instead of agricultural holdings as in the Farm Structure Survey).
LUCAS SURVEY
*Decision N°1445/2000/EC of the European parliament and of the Council of the 22.05.2000 “on the application of area-frame survey and remote-sensing techniques to the agricultural statistics for 1999 to 2003”.
CAPRIDynaSpat, Bonn 10.3.2003
Main land cover/use survey raster: 18 km by 18 km with 10 subsampling Units
Phase 1: field survey at ~100000 observation points in EU15 (spring)
Phase 2: interview with ~5000 farmers to obtain additional technical or environmental information (autumn)
The first survey has been carried out in 2001 (UK 2002)
57 land cover classes are separated including 34 agricultural classes
High geometrical accuracy of the sampling locations (+/- 3m)
ORGANISATION OF THE LUCAS SURVEY
Sampling design: Primary sampling units in NL
CAPRIDynaSpat, Bonn 10.3.2003
LUCAS SURVEY CLASSIFICATIONBuildings w ith 1 to 3 floors Com m on w heat Broadleaved forest Bare land
Buildings w ith m ore than 3 floors Durum Wheat Coniferous forest Inland w ater bodies
Greenhouses Barley Mixed forest Inland running w ater
Non built-up area features Rye Other broadleaved w ooded area Coastal w ater bodies
Non built-up linear features Oats Other coniferous w ooded area Wetland
Maize Other m ixed w ooded area Glaciers, perm anent snow
Rice Poplars, eucalyptus
Other cereals Shrubland w ith sparse tree cover
Potatoes Shrubland w ithout tree cover
Sugar beet Perm anent grassland w ith sparse tree/shrub cover
Other root crops Perm anent grassland w ithout tree/shrub cover
Sunflow er
Rape seeds
Soya
Cotton
Other fibre and oleaginous crops
Tobacco
Other non perm anent industrial crops
Dry pulses
Tom atoes
Other fresh vegetables
Floriculture and ornam ental plants
Tem porary, artificial pastures
Fallow land
Apple fruit
Pear fruit
Cherry fruit
Nuts trees
Other fruit trees and berries
Oranges
Other citrus fruit
Olive groves
Vineyards
Nurseries
Perm anent industrial crops
CAPRIDynaSpat, Bonn 10.3.2003
FINE SCALING CORINE LC CLASSES WITH LUCAS DATA
Based on a study from J. Gallego (2002)
Fine scaling in this case means estimating the proportion of other land cover classes within a given CORINE class as e.g. “pastures”
To examine the possibility of fine scaling the CLC classes J. Gallego overlaid the CLC with the point observation of the LUCAS 2001 survey
The operation produces a matrix with 56 columns (LUCAS land cover classes) and 44 rows (CLC) that allows to analyse the composition of other land cover classes within a specific CLC land cover class
CAPRIDynaSpat, Bonn 10.3.2003
FINE SCALING CLC 2000 WITH LUCAS DATA
Bar
ley
Com
mon
whe
at
Dry
pul
ses
Mai
ze
Oat
s
Pot
atoe
s
Sug
ar b
eet
Fal
low
land
Per
man
ent
gras
slan
d w
ithou
t tr
ee/s
hrub
cov
er
Per
man
ent
gras
slan
d w
ith s
pars
e tr
ee/s
hrub
cov
er
Shr
ubla
nd w
ith s
pars
e tr
ee c
over
Shr
ubla
nd w
ithou
t tr
ee c
over
Con
ifero
us f
ores
t
Bro
adle
aved
for
est
Mix
ed f
ores
t
Oth
er b
road
leav
ed w
oode
d ar
ea
Oth
er c
onife
rous
woo
ded
area
Oth
er m
ixed
woo
ded
area
Bar
e la
nd
Inla
nd r
unni
ng w
ater
Inla
nd w
ater
bod
ies
Wet
land
Non
bui
lt-up
are
a fe
atur
es
Non
bui
lt-up
line
ar f
eatu
res
Bui
ldin
gs w
ith 1
to
3 flo
ors
Non-irrigated arable land 70 81 100 43 100 100 67 100 7 2 3 3 1 5 7 3 1 4 8 19Pastures 28 19 57 33 74 37 35 15 13 30 24 59 73 67 43 5 13 44 55 25Complex cultivation patterns 3 2 3 5 8 6Land princip. occ. by agric., with sign. areas of nat. veg. 5 15 15 10 3 8 8 4 6 8 5 6Coniferous forest 3 32 14 24 4 9 2 8Mixed forest 3 20 17Natural grasslands 1 1 1 3Moors and heathland 6 21 3 1 24Transitional woodland-shrub 2 6 3 8 30 27 20 11 18 17 5 2 4 3Bare rocks 2Sparsely vegetated areasInland marshes 2 1 2Peat bogs 7 28 21 55 18 8 4 9 55 5 72 5 6Salt marshes 1Water bodies 77 1Estuaries 1 43Sea and ocean 9 1Continuous urban fabric 4Discontinuous urban fabric 1 1 4 3 14 16 11 25Industrial or commercial units 1 16 5 13Green urban areas 3Sport and leisure facilities 3 3 7
Nr. of LUCAS SSU (Total 2160) 69 16 1 7 1 2 3 2 1284 178 34 40 150 37 25 27 11 6 33 7 22 126 25 38 16
LUCASC
OR
INE
Test for Ireland
CAPRIDynaSpat, Bonn 10.3.2003
SPATIALISATION OF STATISTICALLAND USE WITHIN ONE LAND COVER CLASS
A study of the Geographical Information Management (G.I.M, 2002) group showed to possible value of using topographical (elevation, slope) and soil information to disaggregate CLC land cover classes with complex patterns into single “classes” .
Example: CLC class ‘complex cultivation patterns’ contains 30% arable land, 40% pasture, 30% forest (based on CLC/LUCAS analysis). Roughly speaken: arable land will be attributed to the best growing/farming conditions -> good soils / low altitudes / flat terrain
The G.I.M method will be reviewed
Analysis if the assumptions can be improved by looking at relationships between LUCAS data – soil – topography
CAPRIDynaSpat, Bonn 10.3.2003
NETHERLANDS: Changes in Agricultural areas 1990 - 2000
-1200 -1000 -800 -600 -400 -200 0 200
Agricultural areas (total)
Arable land
Permanent crops
Pastures
Heterogeneous agricultural areas
km2
NETHERLANDS: Agricultural areas converted into:
0 200 400 600 800 1000
Forest and semi natural areas
Artifical surfaces
Wetlands
Water bodies
km2
IRELAND: Changes in Agricultural areas 1990 - 2000
-2000 -1500 -1000 -500 0 500 1000 1500 2000
Agricultural areas (total)
Arable land
Permanent crops
Pastures
Heterogeneous agricultural areas
km2
IRELAND: Agricultural areas converted into:
0 50 100 150 200 250 300 350
Forest and semi natural areas
Artifical surfaces
Wetlands
Water bodies
km2
94
CHANGES IN AGRICULTURAL AREABASED ON CLC90 AND CLC2000
CAPRIDynaSpat, Bonn 10.3.2003
Amsterdam
Agricultural area to Artificial surfaces
Agricultural area to Wetlands
Agricultural area to Forest & seminatural areas
LAND COVER CHANGES IN NL
CAPRIDynaSpat, Bonn 10.3.2003
INFRASTRUCTURE FOR SPATIAL DATA IN EUROPE (INSPIRE)
With the INSPIRE initative, the European Commission intends to trigger the creation of a European Spatial Data Infrastructure (ESDI)
The ESDI has to be set up in a way that will allow public users at European to local level to discover, access and acquire spatial data from a wide range of sources for a wide range of applications
INSPIRE expert groups has been set up for several topics e.g.•Reference data and metadata•Data policy and legal issues•Architecture and standards (reference system, projections, European reference grid system)•…