1. Some considerations on 2009-2012LUCAS
By Mauro Masselli

2. topics The reference population The sample design Estimator
Data “projection”
Other quality indicators

3. In the framework of the grant support by Eurostat we proposed two methods to integrate LUCAS statistics in national statistical framework
The first method is LUCAS based and looks to improving LUCAS accuracy by making LUCAS consistent/coherent with other national official statistics
The second approach looks to replace LUCAS with sources and statistics more reliable than LUCAS and available in the national system
Both methods use auxiliary variables recorded on some cartographic layers rasterized to 20x20 mt
Lucas integration. Luxembourg

4. The reference population
In 2009 and the second phase sample is selected from subpopulations identified by restrictions of master sample;
so the estimates should be referred to the corresponding areas….
while the estimates are produced for the whole area of participating country

5. The reference population
The reference population is defined by
Eligibility rules
Accessibility rules
Ex ante criteria - missing units ?
In field missing units

6. 2015 Master country number of points <1500 mt
total
percentage of points > 1500 mt AT
16629
4350
20979
20,7 BE
7682 . BG
26718
1023
27741
3,7 CY
2305 6
2311
0,3 CZ
19717 1
19718 DE
89357
144
89501
0,2 DK
10825 EE
11354 EL
32100
945
33045
2,9 ES
120239
4374
124613
3,5 FI
84542 FR
133140
4166
137306
3,0 HU
23271 IE
17557 IT
69157
6178
75335
8,2 LT
16334 LU
646 LV
16145 MT 80 NL
8864 PL
78125 16
78141 PT
22242 19
22261
0,1 RO
58623
987
59610
1,7 SE
112371
123
112494 SI
4938
129
5067
2,5 SK
12164 99
12263
0,8 UK
62008
22560
2,1
2015
Master

7. 2012 sample country number of NUTS_2 with points >1500
number of points >1500
average points > per Nuts_2 AT 7
4350
621 BE . BG 5
1023
205 CY 1 6 CZ DE 2
144 72 DK EE EL 9
945
105 ES 14
4374
312 FI FR
4166
595 HU IE IT 20
6178
309 LT LU LV MT NL PL 16 PT 19 RO
987
141 SE
123 62 SI
129 65 SK 99 50 UK
total 81
22560
279
2012 sample

8. 2012 Land cover: ratio between estimates related to the population <1500 mt and the estimates for the whole population; percentages of LC in the whole population

9. estimates for the whole population
 ratio = estimates for the population <1500/
estimates for the whole population
Absolute Value
percentages
number of NUTS 2 with a ratio > 101 % 77
29,5
number of NUTS 2 with a ratio < 99 % 74
28,4
number of nuts 2 with a ratio <99 or >101
151
57,9
number of NUTS 2
261
100.0
number of estimates with a ratio >101
590
number of estimates with a ratio < 99
571
28,5
number of estimates with a ratio <99 or >101
1161
58,0
number of estimates
2001

10. The distribution of points by elevation

11. 0-1000
>1500
total
2012
97,13
2,85
0,02
100
master
93,22
4,69
2,09

12. Elevation - percent ratio of distribution in 2012 and distribution in master
up to 300
>1500 AT
119,6
154,1
150,3
107,9
76,9
62,7
1,0 BE
101,7
94,2
60,1 BG
118,3
107,4
89,5
73,2
61,6
24,2
0,4 CY
73,4
144,6
152,2
160,3 CZ
102,0
95,7
83,2
32,3
10,8 DE
101,6
100,6
95,5
70,1
49,9
2,8 DK
100,0 EE EL
115,1
109,1
100,3
73,0
59,3
42,0 ES
116,5
109,2
111,4
104,9
52,7 FI
106,1
19,3
1,8 FR
106,9
100,7
98,5
78,6
52,9
0,3 HU
100,9
85,3
67,3 IE
104,1
22,9
0,0 IT
120,5
110,3
98,0
83,4
70,4
58,3
0,8 LT LU
106,6
97,0 LV MT NL PL
91,9
56,4
38,0
31,9 PT
97,7
94,4
79,1
56,1
26,4 RO
123,9
57,9
31,5
24,3
7,8 SE
118,6
103,5
15,5 SI
111,7
109,5
102,2
73,9
62,2
7,3 SK
106,0
111,5
97,6
57,2
41,8
14,8 UK
108,1
64,2
10,4
24,9 EU
106,7
102,1
91,8
68,7
50,7

13. ratio sample /master
up to 300
>1500 AT
116,1
152,5
174,8
128,3
71,2
22,7
1,7 BE
98,9
104,5
99,7 CZ
100,1
101,2
101,7
82,8
40,5
0,0 DE
101,6
101,9
91,6
39,0
16,6
11,8 DK
100,0 EE EL
102,9
121,9
125,2
90,8
50,9
9,7
0,9 ES
111,2
118,2
131,5
133,8 FI
100,7
91,0
96,2 FR
104,2
112,0
122,2
97,6
37,7
9,3
0,5 HU
99,9
105,4
66,9 IE
99,3
81,4 IT
116,9
116,7
113,9
90,9
60,3
18,5
2,3 LT LU
104,7
97,9 LV NL PL
100,2
101,1
94,5
75,5
42,2 PT
103,9
101,3
63,9
43,3
8,9 SE
100,6
104,1
102,1
86,5
27,9
9,4 SI
112,1
110,3
111,6
83,8
36,5
13,8
6,5 SK
101,0
106,4
110,0
82,1
52,6
12,6 UK
98,3
109,2
106,8
112,6
Total
103,3
108,4
120,6
109,0
24,4
8,3
1,3

14. Implications
with yhe present method: LC and LU, typical of the area with a lower elevation, are overestimated;
possible solution: use a calibrated estimator / poststratification by elevation
If we limit the estimates to the «actual» reference population we obtain a partial comparability between different LUCAS rounds

15. The sample design
double sampling: we assume that in every NUTS2 region the strata weights Wh = (Nh/N) estimated from the first phase sample, are correct estimates of the related percentage Wh* in the population, that is E(Wh ) = Wh*
From the stratified first phase sample, a second phase simple random sample (SRS) of points is chosen; the stratified second phase sample is selected independently in each NUTS2 region and in every stratum

16. Some questions
We use the master because the points are “stratified” (in 2005); the stratification do not produces so much gains in efficiency ; so the rationale could be to control the sampling allocation of land cover because the correlation with land cover (see the K.statistics)
The maintaince of the master is costly; so which role can play elevation (less costly and invariant over time) ? There are other inespensive variable to be used?
In different rounds indipendent samples should be selected; are all the selection rules in line with this requirement?
The longitudinal structure is very important because of it decreases the errors of variations between survey rounds but it is not esplicity and clearly controlled; at which level it should be controlled?

17. estimator
calibration estimator using constraints on the following totals :
Nuts2*Strata;
Nuts1*Elevation (<=300, , , >901)
Country*Strata*Elevation
The algorithm starts by the inclusion probability that is changed during the steps, in order to reproduce the known totals.
Weakness: at moment no external source on elevation easy available for EU; information from master sample is used (estimate)

18. Calibration Estimator
Adopting a calibration estimator at EU/national level:
coherence with other relevant available statistics/variables
Reduction of biases
Flexibility with regards to the availability of sources in time / in countries

19. Summary of the proposals: improvement of Lucas accuracy
to smooth these problems and other similar consistency problems with other sources it is possible :
to use LUCAS only for the altimetry class (that’s could be useful only for Italian case)
to calibrate LUCAS’ sample weights to auxiliary information (known totals or benchmarks)
to combine estimates produce by calibrated LUCAS with those belonging from other available specialized sources (e.g. forest inventory, AGRIT, etc.)
to estimate the area over 1200 mt using other sources that (for such altimetry class) can approximate quite well the LUCAS’ nomenclature
Lucas integration. Luxembourg

20. S L = ∑h [∑k ILkh ykh ]* S * whk
ESTIMATOR – level NUTS 2
S L = ∑h [∑k ILkh ykh ]* S * whk
where whk is obtained as the final result of the following iterations
𝑤 𝑖; 𝑣 1 ,…, 𝑣 𝑚 𝑡 1 = 𝑁 𝑣 1 ,…, 𝑣 𝑚 𝑛 𝑣 1 ,…, 𝑣 𝑚 𝑤 𝑖; 𝑣 1 ,…, 𝑣 𝑚 𝑡 0
Where:
𝑡 1 and 𝑡 0 represent two consecutive iterations;
i refers to the i-th point;
𝑣 1 ,…, 𝑣 𝑚 refers to the values observed for the 1,…,m variables;
𝑁 𝑣 1 ,…, 𝑣 𝑚 are the number of points (derived from the master data set) of the values for the 1,…,m variables;
𝑛 𝑣 1 ,…, 𝑣 𝑚 are the totals of the values for the 1,…,m variables as observed in the sample;
𝑤 𝑖; 𝑣 1 ,…, 𝑣 𝑚 𝑡 1 and 𝑤 𝑖; 𝑣 1 ,…, 𝑣 𝑚 𝑡 0 are, respectively, the new and the old weight for the i-th point; starting from the inclusion probability
IL is a binary function equal 1 if Y = L and 0 otherwise

21. 2012 estimates and variations 2012/2009

22. Table 13: estimates of land cover by country – absolute values ( km2)
Artificial land
Bare land
Cropland
Grassland
Shrub land
Water areas
Wetland
Woodland
total AT
4405
2312
14295
20316
1572
1636
222
39170
83.928 BE
3748
154
8887
9953
135
438 69
7283
30.668 BG
2007
918
35475
22862
6734
961
100
41922 CY
598
433
3146
1221
1999 39 16
1795
9.246 CZ
3484
519
27133
16327
582
1040
123
29661
78.870 DE
26285
2719
118539
82476
3728
6383
1832
115802 DK
3022
472
20989
9245
580
730
441
7584
43.065 EE
964
503
5447
9341
1279
2240
747
24850
45.372 EL
5029
2988
30840
18023
33014
1924
631
39242 ES
18501
23955
141699
79143
80618
4567
603
149456 FI
5520
2314
20429
14199
7841
33747
16537
237254 FR
29874
4832
169654
153693
19008
7731
1043
163236 HU
3173
1022
43540
19460
2120
1779
1129
20787
93.013 IE
2964
448
4135
44155
2899
1809
4596
8940
69.946 IT
21871
4714
97634
51625
18808
8809
646
96530 LT
1606
452
17166
19410
763
1694
618
23192
64.899 LU
265 23
539
865 26 19
858
2.596 LV
1049
670
8390
15878
966
2421
1422
33790
64.586 MT
103 24 83 35 51 8 12
315 NL
4555
537
9122
14085
478
2215
182
4344
35.518 PL
10468
2648
107687
75783
3450
5661
1394
104836 PT
5108
2883
16103
15072
15089
1239
245
33105
88.843 RO
5056
1397
83516
64278
4019
4737
1707
73682 SE
8090
2860
19127
27491
23759
38168
22598
307630 SI
677
278
2205
4470
456 89 66
12035
20.277 SK
1429
249
13758
9855
1599
556 40
21540
49.026 UK
14892
2998
52040
100728
20600
5716
6352
41247 EU
184964
63353
901416
252341
136051
63211

23. country
Artificial land
Bare land
Cropland
Grassland
Shrub land
Water areas
Wetland
Woodland
total AT
5,2
2,8
17,0
24,2
1,9
0,3
46,7
100,0 BE
12,2
0,5
29,0
32,5
0,4
1,4
0,2
23,7 BG
1,8
0,8
32,0
20,6
6,1
0,9
0,1
37,8 CY
6,5
4,7
34,0
13,2
21,6
19,4 CZ
4,4
0,7
34,4
20,7
1,3
37,6 DE
7,3
33,1
23,1
1,0
32,4 DK
7,0
1,1
48,7
21,5
1,7
17,6 EE
2,1
12,0
4,9
1,6
54,8 EL
3,8
2,3
23,4
13,7
25,1
1,5
29,8 ES
3,7
4,8
28,4
15,9
16,2
30,0 FI
6,0
4,2
10,0
70,2 FR
5,4
30,9
28,0
3,5
29,7 HU
3,4
46,8
20,9
1,2
22,3 IE
0,6
5,9
63,1
4,1
2,6
6,6
12,8 IT
17,2
6,3
2,9
32,1 LT
2,5
26,5
29,9
35,7 LU
10,2
20,8
33,3
0,0
33,0 LV
13,0
24,6
2,2
52,3 MT
7,5
26,3
11,3
16,3 NL
25,7
39,7
6,2 PL
34,5
24,3
33,6 PT
5,7
3,2
18,1
37,3 RO
35,0
27,0
2,0 SE
4,3
5,3
8,5
5,0
68,4 SI
3,3
10,9
22,0
59,4 SK
28,1
20,1
43,9 UK
21,3
41,2
8,4
16,9 EU
24,9
38,0

24. % variations 2012/2009 country Artificial land Bare land Cropland
Grassland
Shrub land
Water areas
Wetland
Woodland
total AT
131,1
77,2
106,3
96,0
72,6
118,2
96,1
100,0
100 BE
112,4
47,5
107,5
96,8
52,1
110,6
52,3
94,9 CZ
104,3
99,0
97,4
101,8
110,4
100,1
66,1
101,0 DE
107,2
127,8
100,6
99,6
132,5
99,3
91,1
97,1 DK
108,3
120,4
100,8
96,4
78,7
108,0
88,7
100,4 EE
135,8
141,7
103,9
102,7
120,0
94,8
31,3
102,9 EL
113,0
89,7
102,2
98,3
95,5
105,1
79,9 ES
111,8
95,0
94,4
104,1
80,6
106,6 FI
102,8
54,8
100,9
126,2
36,3
98,7
85,3
107,1 FR
110,1
75,9
102,6
104,8
80,7
99,9
95,4 HU
105,3
219,8
98,5
100,2
113,4
95,6
91,9
99,2 IE
83,1
116,2
98,8
68,6
93,7
108,6
110,0 IT
109,7
74,3
102,0
96,9
85,8
168,4
85,9
99,1 LT
104,4
108,9
109,1
91,6
75,8
84,5
170,2
102,3 LU
126,8
69,7
95,2
144,4
118,8 LV
96,7
125,0
107,0
92,5
41,2
130,2
96,5
104,7 NL
106,9
139,8
72,8
51,7
95,8 PL
113,8
157,2
95,7
98,6
112,9
103,6 PT
116,6
81,9
97,5
110,2
92,6
65,7 SE
119,1
22,2
118,7
60,2
85,6 SI
114,4
66,5
107,8
82,9
71,8
115,8 SK
120,9
137,6
106,1
81,6 UK
81,2
106,7
95,3
84,1
103,0
113,7 EU
82,6
112,3
111,3
87,6
105,6
92,4

25. L. Fattorini, M. Marcheselli, C
L. Fattorini, M. Marcheselli, C. Pisani (2006), A Three-Phase Sampling Strategy for Large-Scale Multisource Forest Inventories. Journal of Agricultural, Biological, and Environmental Statistics, Volume 11, Number 3, American Statistical Association and the International Biometric Society

26. Table 27: Land cover CV (%) by countries l
Table 27: Land cover CV (%) by countries l
country
Artificial land
Bare land
Cropland
Grassland
Shrub land
Water areas
Wetland
Woodland AT
4,86
11,76
2,11
2,13
12,95
6,73
23,56
1,18 BE
4,28
28,6
2,51
2,6
30,24
12,7
40,55
2,74 BG
7,55
13,35
1,19
2,18 5
12,67
44,83
1,2 CY
8,12
9,51
2,9
5,41
4,31
33,36
55,49
4,64 CZ
16,32
1,4
2,33
15,58
8,27
34,16 DE
2,04
7,15
0,74
1,07
6,16
3,92
8,71
0,69 DK
5,75
15,7
1,56
3,2
14,47
11,36
17,16
3,27 EE
12,04
19,62
4,83
3,65
12,29
5,81
17,07
1,32 EL
5,08
7,46
1,58
2,72
1,9
7,64
16,66 ES
2,3
2,22
0,65
1,16
1,23
4,54
15,57
0,73 FI
5,83
10,89
2,19
3,9
3,79
0,45 FR
1,73
5,54
0,58
0,71
2,7
3,25
11,91
0,59 HU
6,46
13,92
1,14
2,56
7,24
13,15
2,05 IE
7,06
20,75
6,13
8,07
6,43
6,22
3,76 IT
2,03
6,6
0,77
1,45
2,8
3,99
15,34
0,81 LT
8,43
20,05
2,23
14,87
8,51
17,28
1,46 LU
15,62
72,84
10,86
7,77
68,26
49,48 LV
10,18
14,66
3,46
12,2
6,5
9,43
1,04 MT
16,21
39,51
18,86
31,6
25,54 . 57 NL
16,7 3
17,18
5,72
29,26
4,45 PL
3,47
7,27
0,79
1,12
6,4
3,84
10,11
0,72 PT
4,25
6,35
2,46
2,52
8,31
22,87
1,39 RO
4,89
10,95
0,89
1,24
6,75
5,34
10,69
0,93 SE
4,74
2,53
2,83
2,89
0,39 SI
13,14
16,11
6,8
4,6
16,25
35,92
42,81
1,96 SK
9,23
28,62
3,45
13,04
70,91
1,48 UK
8,11
2,82
4,43
5,46
1,77 EU
0,78
0,25
0,34
0,80
1,64
0,20

27. efficiency indicator - land cover
efficiency indicator - land cover
country
Artificial land
Bare land
Cropland
Grassland
Shrubland
Water areas
Wetland
Woodland AT
0,90
0,84
1,01
1,00
1,02
0,93
0,89
0,98 BE
0,99 BG
1,03
1,09 CY
0,94
1,06 CZ
1,05 DE DK EE EL
1,04
0,95
1,07 ES
1,08 FI FR
0,92
1,13 HU IE
0,97 IT
0,96 LT LU LV MT NL PL PT RO
1,14
0,91 SE
0,77
0,86 SI
0,57 SK
1,10 UK EU

28. Commerce, finance, business Community services Construction
country
Agriculture
Commerce, finance, business
Community services
Construction
Energy production
Fishing
Forestry
Industry and manifacturing
Mining and quarrying
Not used and abandoned
Recreation, leisure, sports
Residential
Transport, communication networks, stora
Water and waste treatment AT
1,39
26,83
22,59
34,12
28,09
28,38
1,13
27,31
36,68
7,00
9,67
5,91
6,91
55,52 BE
1,52
23,01
19,51
37,56
69,20
27,71
3,20
27,59
40,36
8,80
16,09
5,04
8,00
60,96 BG
0,93
34,21
28,41
41,65
48,59
23,10
1,33
34,84
33,93
3,49
21,80
8,38
11,17
29,63 CY
2,61
35,78
37,53
29,85
53,37
8,24
38,47
2,56
28,70
12,65
14,10
40,76 CZ
26,27
20,68
49,84
45,17
11,58
1,28
20,46
24,56
5,83
12,49
7,78
7,80
23,57 DE
0,46
8,04
5,97
19,60
13,78
9,60
0,74
9,83
8,15
3,02
4,31
2,93
14,08 DK
1,11
17,53
17,54
43,82
57,12
34,18
4,08
29,34
106,63
5,47
8,75
6,11
8,96
42,39 EE
2,21
100,00 .
35,94
13,39
1,31
70,69
18,80
8,85
18,33
16,27 EL
1,19
23,45
21,79
28,83
17,39
14,26
2,16
33,02
21,81
1,56
15,97
8,69
7,07
23,24 ES
0,45
16,42
10,10
14,09
11,65
18,26
1,04
16,82
10,98
0,85
7,98
4,21
3,50
7,14 FI
1,94
29,31
55,56
15,37
4,24
0,47
34,57
12,27
2,72
2,59
7,23
6,09
59,05 FR
0,35
10,83
6,21
16,20
15,61
7,20
13,28
12,14
1,55
4,58
2,13
2,51
14,67 HU
0,84
33,77
25,07
102,40
49,91
14,93
2,10
27,60
30,08
13,76
6,59
10,54
22,21 IE
0,98
50,46
52,24
101,17
58,41
18,53
4,85
58,22
9,82
5,09
12,72
8,91
11,15
37,75 IT
0,57
9,16
12,39
13,52
12,03
10,99
1,05
11,62
16,91
1,62
6,92
3,11
3,56
23,87 LT
1,01
49,49
10,07
1,46
37,69
7,42
18,65
11,47
12,25
58,54 LU
4,61
81,56
96,90
106,73
6,80
58,36
60,83
35,12
23,59 LV
1,60
57,60
35,16
9,45
70,43
18,55
4,86
10,63
10,47
70,71 MT
15,33
70,26
22,50
36,33 NL
1,41
20,76
20,39
26,48
95,52
10,85
27,40
58,62
6,62
7,09
6,49
5,86
38,56 PL
0,53
15,46
8,94
17,92
33,76
8,25
0,76
15,74
13,32
2,22
5,39
3,44
4,65
17,29 PT
1,21
23,05
22,95
24,14
32,99
59,71
1,58
28,18
25,88
22,29
6,97
5,94
34,64 RO
0,51
34,33
26,51
28,00
43,48
6,58
0,92
21,20
25,05
22,93
5,65
7,87
39,30 SE
1,69
28,37
12,35
59,31
10,79
2,68
0,44
21,17
20,08
1,70
2,46
5,95
5,17
43,08 SI
3,66
60,79
41,59
59,73
68,05
52,22
2,18
57,10
45,35
9,35
24,50
15,15
17,11
61,76 SK
102,55
29,83
104,36
35,46
22,02
1,50
56,12
6,77
21,18
12,77
14,49
36,06 UK
0,60
12,05
32,79
23,25
10,61
2,24
17,07
13,69
2,26
4,69
3,64
5,38
16,94 EU
0,17
3,72
2,84
5,79
4,51
1,74
0,23
4,34
3,52
0,52
1,27
1,15
4,76

29. Commerce, finance, business Community services Construction
country
Agriculture
Commerce, finance, business
Community services
Construction
Energy production
Fishing
Forestry
Industry and manifacturing
Mining and quarrying
Not used and abandoned
Recreation, leisure, sports
Residential
Transport, communication networks, stora
Water and waste treatment AT
1,03
0,86
1,06
0,76
1,18
1,20
0,95
0,99
1,05
0,98
0,94
1,01
0,91
1,21 BE
1,00
0,97
0,79 BG
1,02
0,92
0,96
1,04 CY
0,93 . CZ DE DK EE EL
1,08 ES FI FR
1,15 HU IE IT
1,11 LT LU
0,82
1,07 LV MT NL PL PT RO SE
1,13
1,14
0,85 SI
0,87 SK
1,23 UK EU

30. Data “projection”
The sample selection in 2012 survey did not follow the random rules established for the previous and the successive occasions because of the pressure from the users of the LUCAS point data to select “accessible points” ;
so some biasess are found in the estimates when comparing and analysing the changes.
A solution in combination with the weight system: to impute, into the 2012 sample, the units randomly collected in 2009 but not present in 2012, hypothesizing a sort of “enlargement” of the longitudinal structure

31. The model
Because of the lapse of time we have to take into account the changes at micro level
Problems
How to identify the units to be changed
How to change the selected units
Method: to model the “change probability” of the points according to specific characteristics.
The model has been estimated from the actual changes from 2009 to 2012 of the points in common to the two surveys; then the model was applied to the 2009 data not present in 2012, obtaining the estimated status of a specific point in 2012.

32. The model In mathematical expressions:
LCt1 = f(LCt0, LUt0, elevation, country)
where
t1 represents the “imputation” year,
t0 represents the “base” year,
land cover estimated for “imputation” year;
f identifies a linear logistic function;
LC,LU, elevation, country refer, respectively, to the land cover, land use, elevation and Country for the point as observed in the base year;
For what concerns the Elevation, the following values are considered: <300; between 301 and 600, between 601 and 900; more than 901.
For land cover it is intended the first letter of the variable LC1
For land use are intended the first three letters of the variable LU1

33. 2012 data
2009 data
Data «projected»
from 2012 to 2009
Model estimation
Data in common
New participating countries

34. From 2009 to 2012 - Main results – land cover
For the total of the participating countries, the imputation procedure increases significantly bareland, shrubland and wetland, where increases higher of 10% occur.
Water areas, cropland and grassland remain substantially stable (with small increase/decreases); artificial land (-4%) and woodland (-2%) decrease their amounts of respectively -4% and 2%.
Of the three most relevant areas cropland and grassland remain substantially unchanged while woodland shows a small decrease of 2%.
The procedure produces an increase in estimation (ratios greater than 100) in the most of countries for wetland (14 countries) followed by shrubland and woodland (13 countries) while for the remaining typologies the number of countries with ratios lower than 100 are the majority.
Regarding the “intensity” of changes operated by the procedure, it can be pointed out the increases greater than 5% in 11 countries for wetland and 6 countries for shrubland and the decreases lower than 5% for bareland (10 countries) and water areas (5 countries).
Tables 6 e 8 LC e 14 LU

35. Ratios tables - 2012 projected/original land cover LC_CVs projected/LC_CVs original

36. percentages ratios between projected and original land cover by countries
country
Artificial land
Bare land
Cropland
Grassland
Shrub land
Water areas
Wetland
Woodland AT
93,38
76,96
103,58
99,60
105,44
94,34
116,44
100,93 BE
99,54
90,01
100,13
98,74
92,46
93,68
93,78
102,60 BG
99,99
99,87
100,00
100,01
100,02 CY
100,04
99,96
100,52
97,66
99,98 CZ
99,65
101,97
99,72
100,66
104,89
104,96
100,67
99,63 DE
97,54
107,00
99,37
99,53
97,23
99,45
100,64
101,48 DK
97,87
88,96
99,78
102,70
87,91
92,03
99,31
100,60 EE
84,95
94,62
94,10
94,82
104,56
299,75
97,64 EL
90,79
99,48
98,62
98,98
101,84
95,01
112,08
101,28 ES
95,50
110,58
98,85
99,14
102,83
100,33
117,52
98,80 FI
98,95
108,04
103,90
89,13
243,57
100,21
119,86 FR
96,45
80,90
99,88
97,10
105,17
97,94
107,39
103,51 HU
97,46
87,27
99,66
99,93
93,93
101,99
109,16
101,75 IE
91,81
79,62
100,76
137,33
104,86
91,43
91,53 IT
96,70
82,39
100,86
97,22
104,49
85,66
108,36 LT
95,98
86,33
99,57
99,07
97,48
106,35
88,22
101,57 LU
99,36
99,33
100,07
98,45
98,65
100,38 LV
97,40
100,15
98,14
100,09
118,41
86,91
106,91
100,62 MT
99,39
98,44
99,62
101,25
100,37 NL
96,93
89,49
99,50
125,43
101,21
171,15
103,64 PL
97,56
97,65
98,64
102,10
104,95
100,22 PT
95,35
116,30
98,13
95,38
112,86
113,86
99,95 RO
100,14
99,97 SE
87,17
399,58
101,04
92,56
165,93
106,41
106,31
91,80 SI
97,28
98,91
97,01
94,89
165,63
110,91
101,14 SK
95,48
83,88
97,61
89,87
95,32
127,47
102,58 UK
70,89
99,21
104,32
100,12
98,88
89,38 EU
96,29
112,97
99,70
99,03
113,41
101,12
110,47
98,08

37. country
Artificial land
Bare land
Cropland
Grassland
Shrub land
Water areas
Wetland
Woodland AT
99,81
121,53
111,01
95,18
87,96
96,64
94,18
89,76 BE
96,04
100,71
97,25
95,95
97,80
97,86
96,37
90,96 BG
100,05
99,97
100,20
100,15
100,03
100,00
99,98
99,91 CY
100,01
99,96
100,09
99,99 CZ
99,35
97,09
98,97
96,39
94,19
97,63
99,33 DE
99,20
93,34
98,91
97,53
95,25
94,77
93,87 DK
97,79
102,53
97,91
94,48
96,77
101,16
91,40
93,85 EE
94,66
91,26
94,58
92,87
87,94
75,48
46,19
95,39 EL
97,12
89,73
94,75
92,12
86,97
91,47
83,95
86,86 ES
96,57
92,54
97,20
95,10
88,98
91,95
84,22
92,07 FI
77,93
71,69
81,88
80,93
47,48
93,57
68,78
90,20 FR
97,32
106,39
98,47
98,30
88,68
95,03
92,01
89,93 HU
92,17
97,47
93,35
91,20
93,32
89,36
86,22
89,55 IE
91,57
95,97
91,10
89,50
74,12
85,66
93,22
92,35 IT
96,93
102,70
98,18
96,30
88,51
97,66
90,81
88,41 LT
98,40
97,40
96,94
90,46
80,23
90,35
92,30 LU
99,45
99,70
99,85
99,50
100,40
98,66 LV
98,93
93,15
99,46
96,42
82,50
93,39
80,06
94,59 MT NL
94,73
98,49
95,19
95,20
83,00
91,62
71,14
90,37 PL
99,40
98,78
97,51
95,69
92,93
95,11 PT
87,14
97,95
98,90
91,88
83,06
95,14 RO
100,13
100,35
100,02
99,59 SE
93,13
40,78
90,90
89,49
63,11
86,15
80,28
97,64 SI
99,29
98,95
99,02
100,52
76,33
91,97
96,70 SK
93,55
99,12
93,93
94,67
92,58
80,83
88,35 UK
90,39
103,95
92,80
87,10
83,19
87,98
85,30
92,62 EU

38. Land use main results
The redistribution operated by the procedure for land use is heavier than for land cover. For the total of the 23 participating countries the imputation procedure increases the areas of “community services” , “not used”, and “water and waste treatment”; in particular the areas of “not used” and “community services” are enlarged for about 15% and 10%.
The procedure decreases the areas of the remaining types of land use where the higher decreases are related to “fishing”, about 15%, and “energy production”, about 14%, that however represent small percentages of land use. Of the bigger areas “agriculture” remain substantially unchanged but “unused” and “forestry” present respectively an increase of about 15% and a decrease of about 3%.
The procedure produces an increase in estimation (ratios greater than 100) in the most of countries for “community services” (13 countries) and “mining” (12 countries); for “forestry” and “not used” the number of countries with an increase equals the number of those with a decrease (11 countries) while for the remaining typologies the number of ratios lower than 100 are the majority ( it ranges from 1 to 10).
Regarding the “intensity” of changes operated by the procedure, it can be pointed out that the number of increases greater than 5%, is lower than the number of decreases lower than 5%; these last ones are present in almost all the typologies while in “agriculture”, “commerce”, “construction” and “residential” there is any increase greater than 5%.
country
Community services
Commerce, finance, business
Agriculture
Construction
Forestry
Fishing
Energy production
Not used and abandoned
Mining and quarrying
Industry and manifacturing
Recreation, leisure, sports
Water and waste treatment
Transport, communication networks, stora
Residential
90,9
99,1 AT
96,2
91,8
94,0
110,0
91,4
93,4
112,3
100,4
93,8
93,0
98,9
99,0
99,7
96,3 BE
87,0
103,4
101,6
88,9
91,1
96,4
91,5
97,0 BG
101,7
94,8
100,0
100,1
100,2
99,9 CY
21,4
0,0
134,0
31,0
203,6
20,3
99,4
99,6 CZ
100,3
47,1
103,8
104,7
98,0
92,7
99,8 DE
75,7
90,2
88,0
92,4
101,3
92,0
98,4
97,5
97,1
98,7
95,8 DK
94,5
101,8
91,0
89,3
83,9
100,6
97,3
96,8
85,4
105,9
97,9
97,4 EE
99,5
115,6
92,9
80,1
35,5
61,8
92,2
94,4 EL
94,6
95,1
95,3
78,8
86,8
91,6
96,6
83,6
87,1
96,9
94,9 ES
88,2
87,9
92,3
95,0
92,6
98,1 FI
79,6
82,4
91,9
77,0
82,6
94,7
85,2
90,7
74,2
85,3
55,6
80,0 FR
100,5
78,6
96,0
102,0
96,1
85,9
95,2
95,5
98,6
97,6 HU
93,7
97,7
86,9
101,1
89,9
85,7
81,1
86,1 IE
73,1
88,5
98,8
88,6
93,2
82,2
89,2
100,9
95,4 IT
87,5
96,5
88,8
77,8
97,2 LT
57,9
57,8
110,5
89,8
83,0
89,7
98,3
63,1 LU
76,4
101,0 LV
103,6
88,4
79,9 MT
73,2
93,1 NL
93,6
86,6
73,7
96,7
92,8
87,2 PL
94,1
98,2
99,3 PT
52,5
80,4
93,3
88,1
92,1 RO
82,5 SE
93,5
101,2
78,0
91,2 SI
95,9
99,2
89,5 SK
57,6
69,9
81,3
85,1
84,4
101,9 UK
82,0
90,3
95,7
88,7
79,5
89,4 EU
 tables 12 e 14

39. Ratios tables - 2012 projected/original land use LU_CVs projected/LU_CVs original

40. Commerce, finance, business Community services Construction
country
Agriculture
Commerce, finance, business
Community services
Construction
Energy production
Fishing
Forestry
Industry and manifacturing
Mining and quarrying
Not used and abandoned
Recreation, leisure, sports
Residential
Transport, communication networks, stora
Water and waste treatment
total AT
101,1
89,4
98,9
102,3
100,8
102,7
100,1
89,0
59,8
101,9
99,1
94,9
95,7
101,0
100,0 BE
95,3
116,5
91,0
88,9
88,2
120,1
91,6
95,2
96,2
103,3
88,3 BG
99,8
99,9
99,7
100,5
100,2 CY
99,5
99,4
98,1
98,7
100,7
99,2 CZ
431,6
97,6
95,5
90,4
96,9
107,3
100,9
97,9
151,1 DE
98,3
111,0
97,1
94,8
110,6
102,2
106,6
96,0
97,0
102,5 DK
93,6
89,6
115,0
104,3
95,8
94,2
90,8
97,7
72,6 EE
74,9
65,7
37,3
95,9
73,7
108,4
170,9
194,0
81,6
91,2 EL
92,5
91,5
92,0
82,5
80,2
93,9
114,7
94,0
93,3
111,9
93,8 ES
110,4
93,7
86,3
105,7
102,0
99,3
93,0
96,1
119,6 FI
81,2
62,8
69,2
89,5
91,3
83,9
174,1
94,7
89,7
59,6 FR
99,0
100,4
97,8
95,4
95,0
106,5
89,3
104,0 HU
82,8
107,9
79,0
88,5
101,8
107,5
106,1
111,6
92,3 IE
102,4
81,5
151,5
80,5
98,5
66,7
81,9
108,3
92,6
104,4
91,7
87,7
58,8 IT
97,5
112,3
87,3
103,2
125,9 LT
98,8
259,6
267,2
66,2
121,1
98,0
167,6
105,2
125,2 LU
107,0
153,1 LV
84,7
80,0
83,3
79,2
91,1
143,8 MT
98,4 NL
109,4
89,8
145,3
101,6
105,0
90,3
92,8 PL
108,9
97,2
96,5
97,4
101,3 PT
102,1
91,8
128,2
291,2
101,7
103,9
100,6
110,1
96,4
91,9 RO
100,3 SE
75,3
82,0
73,4
90,6
106,4
177,4
68,8
90,7
83,4
75,0 SI
98,2
101,5
115,3
96,8 SK
164,2
233,3
82,6
83,5
124,1
80,3
112,7
96,7
92,4 UK
104,5
115,9
87,2
79,6
87,0
104,7
117,7
94,1
94,3 EU
99,6
86,4
115,1
105,5

41. country
Agriculture
Commerce, finance, business
Community services
Construction
Energy production
Fishing
Forestry
Industry and manifacturing
Mining and quarrying
Not used and abandoned
Recreation, leisure, sports
Residential
Transport, communication networks, stora
Water and waste treatment AT
99,1
90,9
96,2
110,0
94,0
91,8
91,4
100,4
112,3
93,4
93,8
99,0
98,9
93,0 BE
96,3
99,7
87,0
101,6
103,4
91,1
88,9
91,5
96,4
97,0
94,8
101,7 BG
100,1
100,0
100,2
99,9 CY
0,0
21,4
134,0
20,3
203,6
31,0 CZ
99,6
99,4
47,1
100,3
104,7
103,8
99,8
92,7
98,0
75,7 DE
90,2
88,0
92,0
101,3
92,4
97,1
97,5
98,4
98,7
94,5 DK
95,8
91,0
101,8
83,9
89,3
100,6
85,4
96,8
97,3
97,4
97,9
105,9 EE
92,9
115,6
99,5
80,1
61,8
35,5
92,2 EL
94,4
94,6
95,1
86,8
78,8
95,3
91,6
87,1
83,6
96,6
96,9 ES
94,9
88,2
87,9
95,0
92,3
92,6
98,1
79,6 FI
82,4
82,6
77,0
91,9
90,7
85,2
94,7
74,2
80,0
55,6
85,3
78,6
100,5 FR
96,0
96,1
102,0
85,9
98,6
95,5
95,2
97,6
97,7
93,7 HU
86,9
101,1
85,7
89,9
81,1 IE
86,1
73,1
88,5
88,6
98,8
89,2
82,2
93,2
100,9 IT
95,4
87,5
96,5
77,8
88,8
97,2 LT
57,9
57,8
110,5
89,7
83,0
89,8
63,1
98,3
76,4 LU
101,0 LV
103,6
88,4
79,9
93,1
73,2 MT NL
86,6
93,6
73,7
87,2
92,8
96,7 PL
94,1
98,2
99,3 PT
80,4
52,5
93,3
92,1
88,1
82,5 RO SE
93,5
101,2
78,0
91,2 SI
95,9
99,2
89,5 SK
69,9
57,6
81,3
101,9
84,4
85,1 UK
90,3
82,0
95,7
79,5
88,7
89,4 EU

42. From 2012 to 2009 - Main results – land cover
For the total of the 23 participating countries, the imputation procedure increases the artificial land, water and woodland; the highest increase is about 3.2% for artificial land.
It decreases the other typologies of land cover; in particular it has a relevant impact for bareland, where the ratio is about 86% or, in other words, the area is 14% shortened.
Of the three most relevant areas cropland and grassland remain substantially unchanged while woodland shows a light increase of 1.5%.
The procedure produces an increase in estimation (ratios greater than 100) in the most of countries for artificial land (19 countries) followed by cropland, grassland and woodland (15 and 14 countries); for water areas the increase equals the decreases (11 countries) while for bareland, shrubland and wetland the number of ratios lower than 100 are the majority ( respectively 20, 18 and 14).
Regarding the “intensity” of changes operated by the procedure, an increases greater than 5% in 8 and 6 countries respectively for artificial land and water areas and decreases lower than 5% for bareland shrubland and wetland (respectively in 16, 11 and 12 countries).
Tables 7 e 8 LC e 14 LU

43. percentages ratios between projected and original land cover by countries (from2012 to 2009)
Artificial land
Bare land
Cropland
Grassland
Shrubland
Water areas
Wetland
Woodland AT
120,88
50,64
103,31
101,45
82,42
111,01
101,60
100,63 BE
107,06
67,20
102,61
99,47
81,37
102,40
48,67
97,60 CZ
100,51
88,00
99,35
100,17
111,79
102,69
89,23
100,45 DE
103,45
84,07
100,72
99,15
98,37
91,11
98,71 DK
106,03
93,15
100,50
98,95
96,19
101,97
88,34
99,06 EE
108,49
101,32
99,44
100,22
111,46
98,57
93,74
100,02 EL
99,05
93,00
100,92
100,24
94,64
103,38
92,83
104,71 ES
104,67
78,46
101,19
96,90
94,63
92,00
103,81 FI
98,43
90,88
101,04
103,66
84,70
98,84
102,04
101,42 FR
103,74
84,40
100,37
101,95
91,26
98,65
98,50
99,22 HU
100,96
98,20
100,11
99,87
100,35
98,35
100,61
99,91 IE
101,76
90,26
99,33
100,38
97,42
98,26
99,31
100,41 IT
103,83
92,32
97,21
94,69
143,22
90,80
99,85 LT
101,22
94,53
101,21
99,58
87,94
142,50
100,26 LU
120,02
108,73
90,89
108,90
71,45
116,45
0,00
92,42 LV
96,67
85,90
97,91
79,15
112,74 NL
101,38
101,94
99,64
100,21
96,11
96,79
90,91
101,53 PL
107,05
82,96
98,78
97,85
103,06
98,09
101,30
102,65 PT
108,24
90,48
101,43
101,09
95,67
108,50
77,38
100,86 SE
103,05
96,54
99,71
104,37
93,85
98,24
101,74 SI
107,57
86,99
104,86
103,97
100,81
128,03
109,64
97,61 SK
102,99
97,30
99,95
98,07
99,17
104,00
99,77 UK
99,90
96,49
100,52
94,54
101,81
113,13
104,14
Total
103,20
86,07
99,81
99,63
94,90
102,03
99,19
101,54

44. coefficient of variations (%) for land cover estimates (from 2012 to 2009)
Artificial land
Bare land
Cropland
Grassland
Shrubland
Water areas
Wetland
Woodland AT
4,89
16,35
2,08
2,04
8,45
6,51
23,41
1,11 BE
4,21
22,69
2,54
2,40
22,23
12,53
36,06
2,48 CZ
4,88
16,86
1,35
2,31
15,28
7,74
28,86
1,18 DE
2,03
8,17
0,73
1,03
6,83
3,73
8,30
0,64 DK
5,62
16,46
1,52
3,03
11,99
11,25
15,70
3,10 EE
11,57
20,39
4,52
3,31
11,09
4,43
7,88
1,25 EL
4,99
6,56
1,49
2,47
1,69
6,67
13,69
1,36 ES
2,24
2,44
0,58
1,10
4,19
13,31
0,68 FI
4,60
6,28
1,74
3,30
2,83
1,31
2,61
0,40 FR
4,80
0,57
0,69
2,30
3,06
11,15
0,53 HU
6,01
18,85
2,33
9,15
6,33
11,33
1,81 IE
6,54
17,00
6,05
1,00
5,85
5,51
5,80
3,48 IT
1,98
5,41
0,75
3,90
14,14 LT
8,21
19,21
2,35
12,28
6,72
16,04 LU
15,68
58,40
7,43
97,41
49,48
0,00
7,35 LV
9,98
15,89
3,44
2,13
7,91
6,09
7,58
1,02 NL
4,11
18,50
2,91
13,97
5,19
20,53
3,93 PL
3,51
9,69
0,76
1,09
6,42
3,66
9,41 PT
4,22
5,67
2,09
2,32
7,40
18,55 SE
3,29
2,22
1,85
1,20
0,38 SI
13,26
14,93
6,97
4,62
14,47
26,55
42,39
1,90 SK
8,90
30,73
3,20
9,55
12,07
57,32
1,30 UK
2,57
6,38
1,27
0,82
2,27
3,96
4,66
1,61 EU

45. Main results land use
The redistribution operated by the procedure for land use is heavier than for land cover.
For the total of the 23 participating countries the imputation procedure increases the areas of “commerce, financial and business” , “fishing”, “residential” , “transport” and “forestry”; in particular the area of “commerce” is enlarged for about 13% but it is related to not relevant amount.
The procedure decreases the areas of the remaining types of land use where the higher decrease, about 7%, are related to “mining and quarrying” and “energy production” that however represent small percentages of land use. The bigger areas remain substantially unchanged; the increase or decrease for “forestry”, “agriculture” and “not used” are not relevant.
The procedure produces an increase in estimation (ratios greater than 100) in the most of countries for “residential” (16 countries); for “fishing”, “not used” and “transport” the increase equals the decreases (10/11 countries) while for the remaining typologies the number of ratios lower than 100 are the majority ( it varies from 5 to 9).
Regarding the “intensity” of changes operated by the procedure, it can be pointed out that increases greater than 5% are present in almost all the land use typologies for a relevant number of countries (from 6 to 11); the same for the decreases lower than 5%.

46. Commerce, finance, business
country
Agriculture
Commerce, finance, business
Community services
Construction
Energy production
Fishing
Forestry
Industry and manifacturing
Mining and quarrying
Not used and abandoned
Recreation, leisure, sports
Residential
Transport, communication networks, stora
Water and waste treatment AT
102,01
94,50
97,67
125,00
201,00
99,33
101,00
135,00
304,00
75,57
76,16
114,70
103,15
68,00 BE
99,50
131,50
82,13
110,00
0,00
148,50
98,17
87,33
98,21
88,52
108,79
101,20
86,50 CZ
99,88
100,50
88,14
52,00
103,50
100,67
140,67
125,50
99,44
107,36
106,16
93,46
89,60 DE
100,29
104,17
91,00
165,00
85,20
97,56
98,00
92,00
105,66
100,65
101,70
104,68 DK
98,81
100,25
117,88
82,50
87,29
91,04
153,50
85,00
113,70
96,14
115,86
110,23
140,00 EE
100,00
70,00
103,00
183,50
100,34
113,25
96,79
87,60
116,21
96,17 EL
99,53
77,50
109,50
118,00
79,00
91,33
92,71
117,00
132,50
108,03
92,50
97,79
106,25
106,50 ES
95,47
76,00
104,67
146,00
154,00
90,50
102,82
93,33
108,33
100,62
99,00
94,33 FI
101,86
90,33
168,00
107,68
101,09
99,60
94,71
96,39
107,82 FR
99,94
86,67
91,43
109,00
97,39
137,00
93,50
105,81
92,79
105,09
105,10 HU
100,16
64,00
111,33
108,00
101,33
99,93
107,00
95,00
100,06
99,29
102,42
102,37
100,40 IE
100,10
81,67
115,00
113,80
95,61
98,66
105,40
95,24
101,54
99,17 IT
98,96
93,60
89,75
133,00
142,50
102,50
111,65
90,00
88,67
88,98
105,82
107,39
99,32
89,00 LT
102,00
63,00
147,44
99,41
88,00
109,76
73,20
96,15
96,41 LU
98,64
79,11
93,89
112,19
85,32
149,63
123,48
70,43 LV
99,43
59,00
105,25
99,37
99,96
114,06
116,92
105,57 NL
99,61
97,08
40,13
90,63
104,78
100,87
102,25
136,00 PL
98,06
121,80
61,00
102,47
89,50
116,50
99,27
99,08
110,39
105,47
119,00 PT
104,40
124,00
140,50
114,50
177,00
65,50
94,15
151,00
82,67
100,38
81,00
100,96
119,58
71,00 SE
100,44
120,50
115,87
102,43
111,00
130,00
91,64
105,88
102,55
105,85 SI
101,95
51,00
279,00
213,00
97,81
82,00
216,00
90,69
123,44
108,10
114,20
155,00 SK
99,92
94,31
66,00
94,00
101,40
100,54
97,00
104,00
96,96
94,25
102,52
103,80 UK
98,42
106,14
107,35
105,00
95,60
105,75
97,47
99,82
101,27
69,60 EU
98,89
113,32
95,83
98,75
93,03
100,90
98,22
93,13
99,40
98,12
105,19
103,87
98,29

47. Commerce, finance, business
country
Agriculture
Commerce, finance, business
Community services
Construction
Energy production
Fishing
Forestry
Industry and manifacturing
Mining and quarrying
Not used and abandoned
Recreation, leisure, sports
Residential
Transport, communication networks, stora AT
93,54
75,97
87,38
98,92
52,59
79,48
91,58
58,10
49,66
132,05
102,69
82,38
81,81 BE
88,27
72,77
88,44
73,24
55,40
83,62
86,71
71,63
78,55
84,66
78,12
83,86 CZ
94,58
84,47
96,24
121,65
98,09
92,75
80,69
81,87
90,72
87,81
94,41 DE
92,24
88,03
86,17
95,74
82,44
91,75
93,01
88,42
88,55
85,84
87,52
90,38
87,30 DK
86,39
81,44
72,33
101,43
73,19
89,32
87,18
67,65
79,73
74,94
81,59
78,41
80,49 EE
97,72
0,00
100,21
88,32
64,28
95,22
70,69
85,07
96,25
108,04
89,14
99,41 EL
89,11
99,34
85,77
85,30
94,82
94,47
92,93
95,50
83,16
82,08
88,34
91,30
88,21 ES
78,63
84,27
85,86
74,10
97,01
81,30
88,45
83,34
79,25
81,06
86,79
87,84 FI
95,27
92,51
91,85
91,94
81,89
90,80
91,04
95,52
85,95
94,88
97,98
91,63
94,83 FR
91,67
91,56
88,56
90,16
76,42
87,57
88,19
83,22
85,98
81,60
89,59
85,75
87,20 HU
99,20
90,03
95,09
99,61
97,36
92,50
99,14
100,23
99,80
98,80
99,43
98,25
98,42 IE
96,43
100,83
100,49
102,37
70,51
97,57
99,70
94,59
97,47 IT
89,82
90,19
89,58
79,74
55,00
83,48
76,13
92,28
81,73
90,34
80,78
84,82
87,97 LT
96,30
100,03
99,18
100,00
99,37
65,07
94,28
100,08
73,83
84,88
102,44
96,89
93,79 LU
96,66
101,29
79,30
70,03
78,93 LV
93,13
84,91
100,56
72,79
78,09
90,90
100,22
82,96
86,69
79,45
83,27
84,10 NL
98,83
99,73
95,49
103,09
127,98
97,37
101,71
81,66
91,50
96,53
92,49 PL
93,15
94,24
82,22
92,79
84,48
94,23
85,28
91,91
89,26
88,13
87,05
87,63 PT
82,90
74,40
75,94
79,31
68,92
76,84
83,23
80,58
88,40
82,46
75,56 SE
93,84
101,06
88,54
98,32
92,00
80,82
88,96
98,14
90,32
96,50
86,09
92,46 SI
83,80
101,31
41,18
87,37
46,74
87,27
100,15
69,62
100,10
91,93
80,93
79,41 SK
99,01
98,60
93,07
100,46
96,71
98,59
88,94
98,64
97,67
97,00
98,18 UK
95,00
98,85
95,21
82,59
82,54
86,43
96,74
86,37
88,09
93,12
96,46
96,15 EU

48. 2009 data
2012 data
Data in common
Model estimation
Data «projected»
from 2012 to 2009
New participating countries

49. Quality report 2012 Stratification
Double classification and estimation
The production process

50. Recoding of land cover and land use in 2009 data
In 2012 the introduction of a more restrictive definition of bareland (from a coverage of 50% to 90%) and the exclusion of mire and swamp forests from land cover peatbogs and the contextual assignment of points to woodland, if the tree canopy covers more than 10%.
In comparison with 2009, this explains mostly the decrease of bareland, due to the more restrictive definition and the swap from Wetland to Wooded areas.
As far as land use is concerned, 2 classes were suppressed Hunting and natural reserve as they represent more a “status” rather than a real use; the suppression caused a redistribution of the areas of the different uses and impacted the comparison with previous year.

51. The reclassification procedure
Deterministic: the original code is simply replaced by the new one (as for example, of “wet forest ” recoded as “wooded area”).
For the points in which, in 2009, land use is equal to “hunting”, “nature reserve” and “unused and abandoned areas” (code that were dropped in the 2012 classification) the procedure uses the information collected over the same point in 2012 if the land cover remain unchanged.
For the points that changed the land cover in 2012 or not surveyed in 2012 the new land use is derived from a probabilistic imputation that is a random selection of the code among the three most frequent land use codes, given the related land cover; the probabilities are derived by considering the cross distribution of land cover and the land use for those point in common to 2009 and to 2012 (and the points are restricted only to those that, in 2009, had the land use that will be changed).
In the 2009 data set the new recoded variables are added and the original ones are preserved.

52. Table 1: land cover and land use recoding
not changed
changed
Totale
195338
39001
234339
174 32
206
195512
39033
234545

53.  country
land use changed
land cover changed
Total collected points
percentages
(1)
(2)
(3)
(1)/(3)
(2)/(3) AT
198 4
4959
3,99
0,08 BE
130 6
1804
7,21
0,33 CZ
288 1
4663
6,18
0,02 DE
1251 18
21118
5,92
0,09 DK
218
2541
8,58
0,04 EE
354
2666
13,28
0,00 EL
2359
7762
30,39
0,05 ES
7435 27
29912
24,86 FI
3920 15
19896
19,70 FR
3856 26
32329
11,93 HU
419 10
5513
7,60
0,18 IE
314
4164
7,54 IT
3313 9
17849
18,56 LT
231
3861
5,98 LU
152
3,95 LV
539
3825
14,09 NL
309 25
2401
12,87
1,04 PL 23
18502
12,75
0,12 PT
1008 2
5428
18,57 SE
8204 19
26657
30,78
0,07 SI
144
1203
11,97 SK
318
2898
10,97 UK
1860 16
14442
12,88
0,11 EU
39033
206
234545
16,64

54. Code transitions
Land cover: great part of the transitions (174 cases) are concentrated in the passage from B43 to B23.
land use: the codes U410 and U420 are new ones and so the percentages are equals to 100%; they derive for the great part from the old U400.
land use: the new codes U130 and U361 derives from the old U364 and U400 in about 30% of the cases.
For the other codes the passages are low or in terms of percentages or in terms of absolute value.

55. Stratification – double classification
in case of uncertain classifications or in other cases envisaged in interpretation guidelines, it was possible to classify the point under two different strata.
The percentage of double classification can be considered an indicator of uncertainty in photo-interpretation process;
it is in average 6.2% but it is greater for “grassland” (21.5%) and “woodland” (13.4%) strata

56. Principal land cover
Secondary land cover
Artificial land
Cropland
Woodland
Shrub land
Grassland
Bare land
Total 48 4
1059
200
6740
3719
11722
112
840
3336 91
4379 3 1
165
169 34 2 73
109 6 25 31
Water areas
Wetland
1256
1046
10101
4048
16458

57. Double classification and estimation
The main variable represents only partially the actual state of the surveyed point (e.g. in the case of mixed or overlapping crops ) and it could generate some biases when we summarize all the information only by the main land cover.
the points classified by only the principal land cover are about 94% of the total.
The remaining 6% are classified in the other cells of the table that contain the “changes” operated by the double classification but it depends also on the level of classification used
The double codes are concentrated in the combination of the main “cropland” with secondary “grassland” (about 41% of the total of points double classified) and “bareland” (23%) and principal “woodland” with secondary grassland (about 20%).

58. Principal land cover
Secondary land cover
<5%
5%-10%
10% -25%
25% - 50 %
50% - 75%
>75%
total 34 11 14 16 28
135
238
5% -10% 12 30 52 58
122
468
742
10% - 25% 38 49
248
370
680
1677
3062
25% - 50% 45 70
377
943
1419
2390
5244 32 91
334
1108
1271
1840
4676
> 75% 88
161
355
416
1134
2531
Total
249
412
1380
2872
3936
7644
16493

59. Un-weighted transition matrix - strata by recoded land cover
Table 20:
Un-weighted transition matrix - strata by recoded land cover
land cover reclassified (2012)
Strata (2005)
Arable land
Permanent crops
Grassland
Wooded areas and shrub land
Bare land
Artificial land
Water
total
56262
2208
16383
3118
2103
1355
281
81710
657
7046
656
615
123
179 11
9287
5269
717
28346
6651
458
1392
1047
43880
Wooded areas and shrub land
1681
1415
9492
95123
692
2035
1989
112427
127 81
720
1410
561
363
882
4144
499
291
2536
1269
146
7521 97
12359 39 1
208
481 51 49
5624
6453
Total
64534
11759
58341
108667
4134
12894
9931
270260

60. The production process

61. EU 739 270260 407 COUNTRY No. Surveyors Surveyed Points Ex-ante PI
Survey Time
Start
End
Austria 13
6467 9
15-apr-12
08-sep-12
Belgium 6
2446
17-may-12
01-nov-12
 Bulgaria 28
6642
03-may-12
01-oct-12
 Cyprus 15
1442 54
03-apr-12
04-oct-12
Czech Republic 11
5514
23-apr-12
20-aug-12
Germany 31
24943
04-may-12
29-oct-12
Denmark
3444
14-may-12
17-sep-12
Estonia 3
2202
30-apr-12
19-sep-12
 Greece 39
7828
202
28-mar-12
26-sep-12
Spain 75
35377
02-mar-12
07-oct-12
Finland 24
13482
28-may-12
France
115
38338
07-apr-12
21-oct-12
Hungary 19
4637
05-apr-12
26-aug-12
Ireland
3484
19-dec-12
Italy
110
21013
17-apr-12
28-jan-13
 Lithuania 7
3889
07-may-12
28-sep-12
Luxembourg 1
215
26-apr-12
08-aug-12
 Latvia 10
4420
 Malta 79
01-may-12
10-may-12
Netherlands
2229
12-may-12
14-sep-12
Poland 41
21806
11-nov-12
Portugal 14
7336
13-sep-12
 Romania 44
14278
22-nov-12
Sweden 36
22421
11-may-12
Slovenia
1621
123
30-aug-12
Slovak Republic
2455
United Kingdom 62
12252 EU
739
270260
407

62. Graph 2- Average time spent per point by country (in min).

63. Graph 1: Average number of points surveyed per surveyor by country

64. Table 10: Number of surveyed points by countries and type of observation
Country
points
Total
% of observed points
observed
in field PI
Ex ante PI
Austria
5801
657 9
6467
89,70
Belgium
2290
156
2446
93,62
 Bulgaria
6152
490
6642
92,62
 Cyprus
1251
137 54
1442
86,75
Czech Republic
5449 65
5514
98,82
Germany
24229
714
24943
97,14
Denmark
3276
168
3444
95,12
Estonia
1911
291
2202
86,78
 Greece
6798
828
202
7828
86,84
Spain
32290
3087
35377
91,27
Finland
11350
2132
13482
84,19
France
35290
3048
38338
92,05
Hungary
4467
170
4637
96,33
Ireland
2866
618
3484
82,26
Italy
17805
3189 19
21013
84,73
 Lithuania
3729
160
3889
95,89
Luxembourg
214 1
215
99,53
 Latvia
3644
776
4420
82,44
 Malta 74 5 79
93,67
Netherlands
2111
118
2229
94,71
Poland
20496
1310
21806
93,99
Portugal
6835
501
7336
93,17
 Romania
11131
3147
14278
77,96
Sweden
20041
2380
22421
89,38
Slovenia
1463 35
123
1621
90,25
Slovak Republic
2205
250
2455
89,82
United Kingdom
10423
1829
12252
85,07 EU
243591
26262
407
270260
90,13
The percentage of the directly observed points is about 75%; it ranges from about 61 % to 99%

65. points
Total
% of observed points
observed
missing
in field PI
Ex ante PI
LUCAS 2009
174749
179
29875
29742
234545
74,51
LUCAS 2012
243591  -
26262
407
270260
90,13

66. Table 17: Rate of checked points by country.
total points
Visually Controlled %
First rejected points
Austria
6467
2047
31,7
224
3,5
Belgium
2446
620
25,3
238
9,7
 Bulgaria
6642
2857
43,0
840
12,6
 Cyprus
1442
494
34,3 60
4,2
Czech Republic
5514
1396
105
1,9
Germany
24943
6618
26,5
1652
6,6
Denmark
3444
1293
37,5
221
6,4
Estonia
2202
1093
49,6
197
8,9
 Greece
7828
3376
43,1
455
5,8
Spain
35377
18144
51,3
3091
8,7
Finland
13482
4601
34,1
543
4,0
France
38338
11717
30,6
2201
5,7
Hungary
4637
1407
30,3
202
4,4
Ireland
3484
1240
35,6
480
13,8
Italy
21013
8249
39,3
1580
7,5
 Lithuania
3889
21,6 39
1,0
Luxembourg
215 95
44,2 5
2,3
 Latvia
4420
1830
41,4
154
 Malta 79
100,0 15
19,0
Netherlands
2229
917
41,1
214
9,6
Poland
21806
6021
27,6
1006
4,6
Portugal
7336
3290
44,8
536
7,3
 Romania
14278
5668
39,7
1490
10,4
Sweden
22421
7428
33,1
1699
7,6
Slovenia
1621
631
38,9 54
3,3
Slovak Republic
2455
1112
45,3
265
10,8
United Kingdom
12252
4795
39,1
1370
11,2 EU
270260
97858
36,2
18936
7,0

67. Check by external company
At the end of 2013, on points belonging to the 2009 and 2012 LUCAS campaigns.
24% of the checked points were corrected for positional errors and 51% for classification errors. Among this last group, 5% were corrected for both type of errors.
Positional errors were mainly attributed to the use of different ortho-photos in 2009 and 2012.
For both 2009 and 2012 data the main corrections on the classifications regards the following land cover classes:
artificial land;
woodland;
grassland;
shrub land.

69. E shrubland C cropland A artificial land

70. Table 24: Distance of observation of the points by country
class of distance (meters)
Average distance
Median distance
% of points with distance >100
0 -3
4-50
>100
Total
(meters) %
Austria
4083
1436
180
102
5801
11,0 2
1,76
Belgium
1385
772 74 59
2290
12,7
2,58
 Bulgaria
4407
876
298
571
6152
30,0 1
9,28
 Cyprus
926
247 35 43
1251
12,9
3,44
Czech Republic
4457
799 91
5449
7,7
1,87
Germany
14698
6775
1364
1392
24229
23,6
5,75
Denmark
1821
886
266
303
3276
30,6
9,25
Estonia
1277
460 67
107
1911
23,4
5,60
 Greece
4065
1449
467
817
6798
50,7
12,02
Spain
26155
3577
990
1568
32290
19,8
4,86
Finland
7871
1924
421
1134
11350
67,7
9,99
France
24265
8773
975
35290
2,76
Hungary
3603
550
139
175
4467
16,0
3,92
Ireland
1121
1122
259
364
2866
42,3 7
12,70
Italy
5912
8529
1431
1933
17805
43,6
10,86
 Lithuania
3308
306 57 58
3729
7,2
1,56
Luxembourg
155
214
4,6
0,00
 Latvia
2841
590 89
124
3644
14,9
3,40
 Malta 6 65
14,1 10
1,35
Netherlands
1264
468
166
213
2111
29,4
10,09
Poland
12686
5472
994
1344
20496
25,4
6,56
Portugal
4857
1167
221
205
6450
3,18
 Romania
9366
1291
253
11131
10,0
2,27
Sweden
11263
6744
552
1482
20041
30,3 3
7,39
Slovenia
914
514 21 14
1463
6,6
0,96
Slovak Republic
1874
245 33 53
2205
10,3
2,40
United Kingdom
4770
3717
744
1192
10423
47,4 4
11,44 EU
159350
58811
10461
14584
243206
25,8
6,00

71. Class of distance (meters) average distance Median distance
land cover
Class of distance (meters)
average distance
Median distance
% of points with distance >100
0 -3
4-50
>100
Total
(meters) %
Artificial land
5635
5505
429
194
11763
13,7 4
1,65
Cropland
50885
13889
4188
4969
73931
22,3 1
6,72
Woodland
50433
23583
2172
2425
78613
14,5 2
3,08
Shrub land
8029
2895
625
1084
12633
35,6
8,58
Grassland
40022
10080
1836
2179
54117
15,6
4,03
Bare land
3101
435 88
161
3785
17,1
4,25
Water areas
286
1788
928
3262
6264
287,8
111
52,08
Wetland
959
636
195
310
2100
50,4
4.5
14,76
159350
58811
10461
14584
243206
25,8
6,00

72. COUNTRY
POINTS
Visually Controlled %
First rejected points
Austria
6467
2047
31,7
224
3,5
Belgium
2446
620
25,3
238
9,7
Bulgaria
6642
2857
43,0
840
12,6
Cyprus
1442
494
34,3 60
4,2
Czech Republic
5514
1396
105
1,9
Germany
24943
6618
26,5
1652
6,6
Denmark
3444
1293
37,5
221
6,4
Estonia
2202
1093
49,6
197
8,9
Greece
7828
3376
43,1
455
5,8
Spain
35377
18144
51,3
3091
8,7
Finland
13482
4601
34,1
543
4,0
France
38338
11717
30,6
2201
5,7
Hungary
4637
1407
30,3
202
4,4
Ireland
3484
1240
35,6
480
13,8
Italy
21013
8249
39,3
1580
7,5
Lithuania
3889
21,6 39
1,0
Luxembourg
215 95
44,2 5
2,3
Latvia
4420
1830
41,4
154
Malta 79
100,0 15
19,0
Netherlands
2229
917
41,1
214
9,6
Poland
21806
6021
27,6
1006
4,6
Portugal
7336
3290
44,8
536
7,3
Romania
14278
5668
39,7
1490
10,4
Sweden
22421
7428
33,1
1699
7,6
Slovenia
1621
631
38,9 54
3,3
Slovak Republic
2455
1112
45,3
265
10,8
United Kingdom
12252
4795
39,1
1370
11,2 EU
270260
97858
36,2
18936
7,0