Geir-H Strand 1 June 2011
Attribution of Corine Land Cover Classes using LCML
The document describes an exercise with attribution of Corine Land Cover (CLC) classes using elements or
characteristics adapted from ISO 19144-2 Land Cover Meta Language (LCML). The list and encoding of LCML
elements is clearly open for further discussion. The purpose of the exercise is to show that the approach is
possible, not to decide how the method finally should be implemented.
Broadly speaking, the method is to select a number of land cover elements (or characteristics). These are (in
this exercise) taken from LCML. The characteristics should
1) thoroughly describe; and
2) properly distinguish between
the CLC classes. The land cover characteristics constitute an attribute vector which must be encoded
separately for each CLC class. The encoding chosen in this exercise is rather simple, but sufficient. More
elaborate encoding can of course be carried out.
Land cover elements or characteristics [I would not describe all these as land cover elements, many are land
use or overlapping.]
30 elements or characteristics were used in the exercise
1. Abiotic surface
2. Biotic surface
3. Anthropogenic surface
4. Natural or semi-natural surface
5. Open water
6. Water-saturated land
7. Dry land
8. Water running
9. Tidal water
10. Salty water
11. Ice or Snow
12. Linear constructions
13. Buildings
14. Other non linear constructions (not buildings)
15. Deposits
16. Extraction sites
17. Cultivated land
18. Irrigated land
19. Rice production
20. Vine production
21. Olive production
22. Orchards
23. Trees
24. Shrubs
25. Grass
26. Broadleaf trees
27. Conifer trees
28. Sand (exposed)
29. Rock (exposed)
30. Burnt areas
Notice that several characteristics are mutually exclusive (e.g. 1. Abiotic surface and 2. Biotic surface). It is,
however, necessary to keep them all as characteristics because they can coexist within the same CLC class (due
to the generalization implied in the CLC product). Other characteristics overlap (23. Trees, 26. Broadleaf trees
and 27. Conifer trees). This structure is kept because some CLC classes clearly contains trees, but they may be
both deciduous or conifers. Other CLC classes contains only one kind of trees (either deciduous or conifers).
Other solutions for this situation are surely possible.
Encoding the land cover characteristics
The encoding of the land cover characteristics is done on a simple, ordinal scale
0: The element/characteristic is insignificant in the CLC class (but may still be present due to generalization)
1: The element/characteristic can be expected in the CLC class but is not a defining element of the class
2: The presence of the element/characteristic is a defining element of the class and must be present
CLC class 111 to 124
1
2
3
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5
6
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8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Abiotic surface
Biotic surface
Antropogenic surface
Natural or semi-natural surface
Open water
Water-saturated land
Dry land
Water running
Tidal water
Salty water
Ice or snow
Linear constructions
Buildings
Other non-linear constructions
Deposits
Extraction sites
Cultivated land
Irrigated land
Rice production
Vine production
Olive production
Orchard
Trees
Shrubs
Grass
Broadleaf trees
Conifer trees
Sand (exposed)
Rock (exposed)
Burnt areas
111
2
0
2
0
0
0
2
0
0
0
0
1
2
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
112
2
1
2
1
0
0
2
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
1
1
1
1
1
0
0
0
121
2
0
2
0
0
0
2
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
122
2
0
2
0
0
0
2
0
0
0
0
2
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
123
2
0
2
0
1
0
1
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
124
2
1
2
0
0
0
2
0
0
0
0
1
1
2
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
All these classes (111 - 124) are characterized (defined) by the presence of abiotic and anthropogenic surfaces.
Presence of dry land is also a defining characteristic of all but class 123. Dry land is also expected to be present
in class 123, but it is not a defining element. Another characteristic that separates class 123 from the other
classes in this group is that open water can be expected here. Biotic surface (along with the abiotic surface) can
be expected in classes 112 and 124. Linear constructions can be expected in all these classes, and is a defining
characteristic of class 122. Trees shrubs and grass are all elements expected in class 112. Etc…
The next few pages include tables with preliminary attribution of all CLC classes. These tables should be
discussed in the upcoming Eagle meeting
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Abiotic surface
Biotic surface
Antropogenic surface
Natural or semi-natural surface
Open water
Water-saturated land
Dry land
Water running
Tidal water
Salty water
Ice or snow
Linear constructions
Buildings
Other non-linear constructions
Deposits
Extraction sites
Cultivated land
Irrigated land
Rice production
Vine production
Olive production
Orchard
Trees
Shrubs
Grass
Broadleaf trees
Conifer trees
Sand (exposed)
Rock (exposed)
Burnt areas
131
2
0
2
0
0
0
2
0
0
0
0
0
0
1
0
2
0
0
0
0
0
0
0
0
0
0
0
1
1
0
132
2
0
2
0
0
0
2
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
133
2
0
2
0
0
0
2
0
0
0
0
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
141
0
2
2
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
1
1
0
0
0
142
1
1
2
0
0
0
2
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Abiotic surface
Biotic surface
Antropogenic surface
Natural or semi-natural surface
Open water
Water-saturated land
Dry land
Water running
Tidal water
Salty water
Ice or snow
Linear constructions
Buildings
Other non-linear constructions
Deposits
Extraction sites
Cultivated land
Irrigated land
Rice production
Vine production
Olive production
Orchard
Trees
Shrubs
Grass
Broadleaf trees
Conifer trees
Sand (exposed)
Rock (exposed)
Burnt areas
211
0
2
2
0
0
0
2
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
2
0
0
0
0
0
212
0
2
2
0
0
0
2
0
0
0
0
0
0
0
0
0
2
2
0
0
0
0
0
0
2
0
0
0
0
0
213
0
2
2
0
0
0
2
0
0
0
0
0
0
0
0
0
2
1
2
0
0
0
0
0
2
0
0
0
0
0
221
0
2
2
0
0
0
2
0
0
0
0
0
0
0
0
0
2
0
0
2
0
0
0
1
0
0
0
0
0
0
222
0
2
2
0
0
0
2
0
0
0
0
0
0
0
0
0
2
0
0
0
0
2
2
1
1
2
0
0
0
0
223
0
2
2
0
0
0
2
0
0
0
0
0
0
0
0
0
2
0
0
0
2
0
2
0
1
2
0
0
0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Abiotic surface
Biotic surface
Antropogenic surface
Natural or semi-natural surface
Open water
Water-saturated land
Dry land
Water running
Tidal water
Salty water
Ice or snow
Linear constructions
Buildings
Other non-linear constructions
Deposits
Extraction sites
Cultivated land
Irrigated land
Rice production
Vine production
Olive production
Orchard
Trees
Shrubs
Grass
Broadleaf trees
Conifer trees
Sand (exposed)
Rock (exposed)
Burnt areas
231
0
2
2
1
0
0
2
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
1
0
2
1
1
0
0
0
241
0
2
2
0
0
0
2
0
0
0
0
0
0
0
0
0
2
1
0
1
1
1
1
1
2
1
1
0
0
0
242
0
2
2
0
0
0
2
0
0
0
0
0
0
0
0
0
2
1
1
1
1
1
1
1
1
1
1
0
0
0
243
0
2
2
2
0
0
2
0
0
0
0
0
0
0
0
0
2
1
1
1
1
1
1
1
1
1
1
0
0
0
244
0
2
2
2
0
0
2
0
0
0
0
0
0
0
0
0
2
1
0
0
0
0
2
1
2
1
1
0
0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Abiotic surface
Biotic surface
Antropogenic surface
Natural or semi-natural surface
Open water
Water-saturated land
Dry land
Water running
Tidal water
Salty water
Ice or snow
Linear constructions
Buildings
Other non-linear constructions
Deposits
Extraction sites
Cultivated land
Irrigated land
Rice production
Vine production
Olive production
Orchard
Trees
Shrubs
Grass
Broadleaf trees
Conifer trees
Sand (exposed)
Rock (exposed)
Burnt areas
311
0
2
0
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
0
2
0
0
0
0
312
0
2
0
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
0
0
2
0
0
0
313
0
2
0
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
0
2
2
0
0
0
321
0
2
0
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
2
0
0
0
0
0
322
0
2
0
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
0
0
0
0
0
323
0
2
0
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
0
0
0
0
0
324
0
2
0
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
1
2
2
0
0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Abiotic surface
Biotic surface
Antropogenic surface
Natural or semi-natural surface
Open water
Water-saturated land
Dry land
Water running
Tidal water
Salty water
Ice or snow
Linear constructions
Buildings
Other non-linear constructions
Deposits
Extraction sites
Cultivated land
Irrigated land
Rice production
Vine production
Olive production
Orchard
Trees
Shrubs
Grass
Broadleaf trees
Conifer trees
Sand (exposed)
Rock (exposed)
Burnt areas
331
2
1
0
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
2
0
0
332
2
0
0
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
333
1
2
0
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
1
0
334
0
2
0
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
0
0
2
335
2
0
0
2
0
0
2
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Abiotic surface
Biotic surface
Antropogenic surface
Natural or semi-natural surface
Open water
Water-saturated land
Dry land
Water running
Tidal water
Salty water
Ice or snow
Linear constructions
Buildings
Other non-linear constructions
Deposits
Extraction sites
Cultivated land
Irrigated land
Rice production
Vine production
Olive production
Orchard
Trees
Shrubs
Grass
Broadleaf trees
Conifer trees
Sand (exposed)
Rock (exposed)
Burnt areas
411
0
2
0
2
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
2
0
0
0
0
0
412
0
2
0
2
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
421
1
1
0
2
2
1
1
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
1
2
0
0
0
0
0
422
2
1
2
1
2
1
1
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
423
2
1
0
2
2
1
1
0
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Abiotic surface
Biotic surface
Antropogenic surface
Natural or semi-natural surface
Open water
Water-saturated land
Dry land
Water running
Tidal water
Salty water
Ice or snow
Linear constructions
Buildings
Other non-linear constructions
Deposits
Extraction sites
Cultivated land
Irrigated land
Rice production
Vine production
Olive production
Orchard
Trees
Shrubs
Grass
Broadleaf trees
Conifer trees
Sand (exposed)
Rock (exposed)
Burnt areas
511
1
1
0
2
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
512
1
1
0
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
521
1
1
0
2
2
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
522
1
1
0
2
2
0
0
2
2
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
523
2
0
0
2
2
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Analysis
Clustering – five groups
The matrix was subjected to hierarchical clustering (using SPSS®) into five clusters. The exercise resulted in five
groups that closely resemble CLC Level 1.
Cluster 1: CLC classes 111 – 142
Cluster 2: CLC classes 211 – 244
Cluster 3: CLC classes 311 – 331, 333, 334, 411 and 412
Cluster 4: CLC classes 332, 335,
Cluster 5: CLC classes 421 – 423, 511 - 523
Obviously, there is some questions regarding the characterization of the wetland classes. 411 Inland marshes
and 412 Peatbogs are more similar to forest and semi-natural areas, while the other (oceanic?) wetland classes
are more similar to the water classes (maybe due to the salty characteristic?). The two classes that form cluster
four are instead 332 Bare rock and 335 Ice and glaciers – probably due to their abiotic character.
Clustering – 15 groups
The matrix was subjected to hierarchical clustering (using SPSS®) into 15 clusters (as in CLC level 2). The
exercise resulted in the following clusters:
Cluster 01: CLC classes 111, 121 – 133, 142
Cluster 02: CLC classes 112
Cluster 03: CLC classes 141
Cluster 04: CLC classes 211 – 213
Cluster 05: CLC classes 221
Cluster 06: CLC classes 222
Cluster 07: CLC classes 223
Cluster 08 CLC classes 231 – 244
Cluster 09: CLC classes 311 – 313, 324, 334
Cluster 10: CLC classes 321 – 323, 333, 411 – 412
Cluster 11: CLC classes 331
Cluster 12: CLC classes 332, 335
Cluster 13: CLC classes 421 – 422, 521, 523
Cluster 14: CLC classes 423
Cluster 15: CLC classes 511, 512, 522
(Grey built-up areas)
(Discontinuous urban fabric)
(Green urban areas)
(Agricultural areas)
(Vineyards)
(Fruit trees and berry plantations)
(Olive groves)
(Pastures and various mixed agriculture)
(Forest, including transitional and burnt)
(Grassland, shrubland, sparse vegetation and mire)
(Sand)
(Bare rock and ice)
(Salty wetlands, lagoons and ocean)
(Intertidal flats)
(Fresh or brackish water)
The results of these two exercises may to some extent be an artifact of the assigned characteristics, but the
results does make sense.
Attribution used in mapping
The following examples illustrate the attribution exercise used in mapping. The attribution table is attached
(“joined”) to the attribute table of a CLC dataset, providing 30 additional thematic variables.
0: The element/characteristic is insignificant in the CLC class (but may still be present due to generalization)
1: The element/characteristic can be expected in the CLC class but is not a defining element of the class
2: The presence of the element/characteristic is a defining element of the class and must be present
Illustration above: Hedmark County, Norway.
Left: Shrub [Grey (0), Yellow (1) and Orange (2)]
Centre: Conifer forest [Grey (0), Light green (1) and Dark green (2)]
Right: Abiotic [Green (0), Grey (1) and Black (2)]
Illustration above: Hordaland County, Norway.
Left: Bildings [Grey (0), Pink (1) and Dark red (2)]
Right: Bare rock [Green (0), Grey (1) and Black (2)]
EAGLE exercises
To be discussed at the EAGLE meeting in Malaga
1.
2.
3.
4.
Is this a meaningful approach?
a. Why or why not? The approach is meaningful, but I think the land cover elements need a further
revision and simplification based on real land cover attributes and what can be visible from
remote sensing.
b. For which purposes can this method be used? Testing how information on basic land cover
elements can be combined and analysed to populate landscape objects.
c. When is it not useful? When the elements are poorly defined.
Are the 30 selected characteristics appropriate? No.
a. Should other characteristics have been selected (additions or replacement)? So characterisitics
are fine (e.g. water, abiotic surface etc.), but things like irrigated land and rice production should
not be in the same list.
Is the encoding [0,1,2] meaningful? Yes
a. Why or why not? Because it is difficult to develop meaningful keys for things which may be quite
subjective.
b. What are the viable alternatives? Probabilistic scores?
Is the description of the individual CLC classes correct (or at least acceptable) when the current encoding
[0,1,2] is used? See my comments.