Photo Intercalibration Course (Photo ICC), exercise in...

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FURTHER DEVELOPMENT AND IMPLEMENTATION OF AN

EU-LEVEL FOREST MONITORING SYSTEM

- FUTMON-

ACTION: C1 TREE 30 NWD: REPORT ON

RESULTS OF PHOTO ICC 2010

IN COOPERATION WITH THE

INTERNATIONAL COOPERATIVE

PROGRAMME ON ASSESSMENT AND

MONITORING OF AIR POLLUTION

EFFECTS ON FORESTS (ICP FORESTS)

Photo Intercalibration Course

(Photo ICC), exercise in 2010

Northwest German Forest Research Station

37079 Göttingen, Grätzelstr. 2

Germany

Elaborated by: Johannes Eichhorn1, Arthur Bauer1, Ludmilla Bohacova2,

Inge Dammann1, Paloma Garcia3, Joerg Weymar1 and Soeren Wulff4

1Northwest German Forest Research Station, Göttingen, Germany 2VULHM - Forestry and Game Management Research Institute Czech Republic

3General Directorate for Nature and Forest Policy Spain 4SLU, Dept of Forest Resource Management, Sweden

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Photo Intercalibration Course

(Photo ICC), exercise in 2010

1. Introduction ............................................................................................................... 3

1.1 Quality checks ......................................................................................................3 1.2 Responsibilities and gratitude to EC and Life plus ...............................................3

2. Objectives .................................................................................................................. 4

3. Scope: European regions and tree species .................................................................. 4

4. Methods .................................................................................................................... 6

4.1 Criteria .................................................................................................................6 4.2 Sample trees and photographic quality ................................................................7 4.3 Assessable crown ................................................................................................8 4.4 Photographic meta data, photo data base and codes ...........................................9 4.5 Participating countries and teams ...................................................................... 10 4.6 Assessment quality indicators and outliers ......................................................... 12

5. Results ..................................................................................................................... 13

5.1 Team assessment quality: frequencies of outliers of photo assessments ........... 13 5.2 Team assessment quality: variation of photo assessments. Assessments in different countries of the same region ...................................................................... 16 5.21 Region: Northern Europe ................................................................................. 16 5.22 Region: Central Europe .................................................................................... 20 5.23 Region: Mediterranean Europe ........................................................................ 26

6. Conclusions .............................................................................................................. 30

Advantages of the photo ICC concept. ..................................................................... 31 Disadvantages of the photo ICC concept. ................................................................ 31

7. Recommendations ................................................................................................... 32

ANNEX ......................................................................................................................... 33

Annex 1: Frequency distribution of tree species (number of trees) and EEA forest types according to Level 1 net of ICP Forests. ......................................................... 33 Pictures in the database ........................................................................................... 34

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1. Introduction Records of the condition of forest trees provide one with an important indicator in the process

of sustainable forest development in Europe. The Ministerial Conference on the Protection of

Forests in Europe (MCPFE; www.foresteurope.org) is agreed on this point, which is also in

accordance with the history of forest ecological monitoring in Europe (www.icp-forests.org).

The distribution of forest types of the European Environment Agency (EEA) shows that there

is a considerable variation in the environmental conditions of forest development as well as in

the optical appearance of forests in different forest types of Europe. This, for example, is

reflected in the distribution of tree species. But even the same species manifests itself

regionally in various forms. It is thus of no mean importance to ensure that quality control

techniques, provide a constancy of assessment over medium term periods and a constancy of

tree assessment in the major forest types.

1.1 Quality checks

The major concept to understand and document the quality of tree assessment data are

calibration courses on international and national level. Calibration courses offer the option to

analyze variation of defoliation classes in a sample under the condition of several assessors.

Field ICCs document tree condition assessments under field condition. Photo ICCs support

the quality system, by assessment of photo sets of mayor tree species in Northern, Central and

Mediterranean Europe.

This report deals mainly with the methodology and the first results of the 2010 photo

intercalibration course. For selected tree species and eco regions a minimum of 30 tree photos

have to be assessed. It is necessary to include all relevant classes or codes in the calibration

course. E.g. regarding defoliation, in the range from 0 % to 100 % at least each 10 % step

should be represented in the sample.

Below follows a description of a method which should enable one to obtain with some degree

of certainty reproducible results of crown assessment via photos all over Europe (separated in

North, Central and Mediterranean Europe), particularly with regard to the key indicator of

defoliation.

1.2 Responsibilities and gratitude to EC and Life plus

The FutMon contract (LIFE07 ENV/D/000218 – C1/ p. 57) defines quality control and

assurance measures to be carried out by the associated beneficiaries responsible for collecting

monitoring data.

Revision of Photo Intercalibration concept (Photo ICC) and exercise in 2010 is a task of the

project: FutMon C1-tree-30 (NWD): Quality expertise and evaluation within tree health

assessments, chaired by Eichhorn, J. (Germany). Coordinators for North Europe and the

Baltic states: Wulff, S. (Sweden); for Central Europe: Bauer, A. (Germany), and for

Mediterranean Europe: Garcia, P. (Spain).

Partners of the photo exercise in 2010: The Expert Panel on Crown Condition and Damaging

agents, National Focal Centers (NFC´s) and the FutMon D1-community.

http://www.foresteurope.org/

http://www.icp-forests.org/

http://dict.leo.org/ende?lp=ende&p=Ci4HO3kMAA&search=particularly&trestr=0x8008

http://dict.leo.org/ende?lp=ende&p=Ci4HO3kMAA&search=with&trestr=0x8008

http://dict.leo.org/ende?lp=ende&p=Ci4HO3kMAA&search=regard&trestr=0x8008

http://dict.leo.org/ende?lp=ende&p=Ci4HO3kMAA&search=to&trestr=0x8008

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2. Objectives

The main aims of the Photo ICC method are:

1. Proof of temporal and spatial consistency of crown condition assessment

to check that assessment consistency is maintained over a long period

o to ensure that assessment standards of an expert or of a team remain

constant over long periods, even when there is a fluctuation among team

members

to check assessment consistency of a tree species in a given major EEA forest type

covering different national and international regions

o to find out systematic or non systematic assessment differences through a

comparative analysis of different tree species and state of defoliation

to check the assessment proficiency of individual experts or of a field teams

o to check out an individual's quality in relation to the team

2. Comparative appraisal of photographs with field pictures of the same trees and digital

reference photographs, possibly in connection with field ICC courses.

3. Completion of the manual's criteria definitions through the addition of pictures that cover

the complete range of main damaging symptoms, particularly those contained in the "national

lists". Check assessment consistency in the face of characteristic biotic or abiotic criteria.

4. Regional photo guides for two to three tree species for each eco region one are an essential

help towards harmonizing tree assessment.

In 2010 the new Photo ICC method was developed and implemented for the first time. The

following elaborations mainly refer to the first of the mentioned objectives. In particular:

Test the method of photo assessments to use for QA QC of crown condition

Implement a basis for future test of temporal consistency of crown assessments

Give recommendations for use of Photo ICC method in future

3. Scope: European regions and tree species

Photo ICCs are desirable for important EEA forest types

(www.eea.europa.eu/publications/technical_report_2006; Fig. 1) as well as for main European

tree species. The Level 1 net of ICP Forests serves as the basis for deciding which tree species

and forest types are to be classified as major important. The average frequency distribution of

the past years, as shown by this net, is shown in Table 1.

http://www.eea.europa.eu/publications/technical_report_2006

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1 Boreal2 Hemiboreal3 Alpine4 Acido. oak and oak/birch5 Mesophytic decidous forest6 Beech forest7 Mounitain beech forest8 Thermo. decidous forest9 Broadleaved evergreen for.10 Mediterr. conif. forest11 Mire and swamp forest12 Flood plain forest13 Non river alder/birch14 Plantations, exotic forests

Fig. 1: EEA forest types and main tree species (after inventory results of ICP Forests Level

1 plots (www.eea.europa.eu/publications/technical_report_2006)

Picea

abies

Pinus

sylvestris

Fagus

sylvatica

Quercus

ilex and Q.

rotundifolia

Pinus

pinaster

Quercus

robur,

Q.

petraea

Northern

Europe

BOREAL

HEMIBOREAL

NEMORAL

Central

Europe

ALPINE

CONIFEROUS

MESOPHY.

DECIDUOUS

BEECH

Mediterranean

Europe

MONTANE

BEECH

THERMOPH.

DECIDUOUS

EVERGREEN

BROAD-

LEAVES

MEDITERR.

CONIFEROUS

Tab. 1: Distribution of tree species and EEA forest types according to Level 1 net of ICP

Forests. Colours indicate the occurrence of tree species in EEA forest types.

http://www.eea.europa.eu/publications/technical_report_2006

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Overview of tree species for which photo ICCs can be carried out in particular forest types

according to the EEA (vid. Tab. 1). The essentially different growth conditions in northern,

central and mediterranean Europe will be taken into consideration on the photo QA project.

Following from this, photographs for Photo ICCs are available:

Region Photo set of 30/100 photos per tree species

Northern Europe Scots pine (Pinus sylvestris)

Norway spruce (Picea abies)

Central Europe Beech (Fagus sylvatica)

Norway spruce (Picea abies)

Scots pine (Pinus sylvestris)

European Oak (Quercus petraea and Q. robur)

Mediterranean Europe Scots pine (Pinus sylvestris)

Maritime pine (Pinus pinaster)

Mediterranean oak (Quercus ilex)

Abies borissi-regis

Pinus halepensis

Tab.2: European Regions and Tree Species in the Photo ICC 2010. Italicized tree species are

not used in the first Photo ICC 2010.

4. Methods

Though some aspects of crown condition survey can not be assessed on photos, main

indicator criteria such as defoliation are clearly shown on high quality photograph. Hence,

experts and field teams can refer to the pictures and shown patterns over a certain period

when main indicator criteria are clearly shown on ideal photographs. The knowledge of clear

patterns helps to transfer photographic assessment results in the course of field work to the

actual objects under appraisal.

4.1 Criteria

Ideally, all mandatory parameters of the Level 1 and 2 crown condition and damage surveys

should be covered by the ICCs. However, as a start it was decided to test defoliation

assessment.

During the EP Crown and Damage meeting in Tampere (2010) it was convened that quality

control procedures should be carried out for the essential criteria defoliation and fructification.

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Additional parameters may be assessed after explicit requests by participating countries or in

consequence of changes to the manual on a voluntary basis. Plot ID, date and ICC participant

code should be recorded by the participants once per plot. All these parameters and codes

must be entered in the field form. The field forms should be supplied by the host countries.

4.2 Sample trees and photographic quality

Photos have to be selected according to defined quality requirements.

A batch of photographs (e.g. defoliation, beech, Central Europe) should consist of at least 30

pictures. The minimum number per tree species and eco region serves as sample for the photo

test in 2010. In the medium term, the number of photos per tree species and eco region should

be increased to at least 100 high-quality photos per object. A large number of photographs

aids statistical analysis and prevents rapid recognition of assessed pictures. The periodically

used sample of photos in each group remains 30.

Photographic concepts hitherto used were discussed by the participants of previous photo

concepts and the upshot was, that an essential weakness of photographic procedures

frequently lies in the poor quality of the photographs. The present proposition for Photo ICCs

thus places the emphasis on optimum picture quality.

The following rules should be taken into account:

Technical characteristics:

High camera resolution (min. 4.5 megapixels; reasons: standard density for

printing 300 dpi = resolution for A5 min. 1800 x 2500 pixels = 4.5 megapixels =

min. 2.0 MB (format JPG)

Satisfactory lighting, the use of a tripod.

Photographs should offer a very good visibility of tree crown. No crowns showing

major effects of competition, no staggered crowns that partially obliterate one

another, the whole viewer to be filled out with the object, if possible picture the

entire crown from tree-top to point of greatest expanse. It is recommended, that

photos should be taken on the angle of 45o accordingly to the horizontal distance

of the tree height.

Pictures of tree crowns should neither be taken against the sun nor in windy

conditions.

A set of photographs should show all criteria variations. Example defoliation: the

range of the criterion 'defoliation' goes in 5% steps from 0% to 100%. The photos

must show trees with a variation of defoliation scores. 0% trees serve as a

reference.

Apply a scale, numbered zero to ten, on the left and on the right side of the photograph to help

assess 10 consecutive crown sections (vid. title picture), as a mean of documenting the

assessed crown. The scale was prepared by NW-FVA.

The limitation to high quality photographs would lead to pictures predominately depicting

free standing crowns. Photos are limited to two dimensions. In reality, under field conditions,

usually only the view from different angles will lead to correct assessment of a sample tree.

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Thus Photo ICC does not mirror all the properties of forest condition inventories made under

field conditions. This is the main reason for implementing an alternating system of Photo and

Field ICCs.

4.3 Assessable crown

Due to historical reasons, some countries use different field definitions of assessable crown,

even if these countries are located in the same general ecvological zone.

Country Scots pine Norway spruce Silver birch

Estonia 1/3 of the living

crown

1/3 of the living

crown

1/3 of the living

crown

Finland 2/3 of the living

crown

1/2 of the living

crown

2/3 of the living

crown

Norway 2/3 of the living

crown

1/2 of the living

crown

whole living

crown

Latvia unknown whole living

crown

whole living

crown

Sweden 2/3 of the living

crown

1/2 of the living

crown

2/3 of the living

crown

Lithuania unknown whole living

crown

whole living

crown

Tab. 3: Use of assessable crown definitions in Northern Europe countries.

(Becher, 2008)

In 2010 there is a test to compare defoliation scores based on two definitions of the assessable

crown: a national definition of assessable crown and a EU wide definition.

The EU wide definition of assessable crown is related to figure IV-1 of Manual Part IV:

Visual Assessment of Crown Condition and damaging agents. It illustrates the definition:

Assessment of the tree crown ranges from the tip of the tree to the widest horizontal span of

the crown.

This means, in 2010 every assessor has to give two values:

defoliation related to the regional assessable crown;

defoliation scores related to a European definition of assessable crown (widest

span).

Photo assessors have to indicate their national assessable crown via scales on both sides of the

crown photo. All photos will show red scales on both sides left and right (0-10). The numbers

refer to horizontal lines, the scale value of 100 % ends at the bottom begin of the photo. This

concept provides best analysis of the temporal consistency of defoliation assessments.

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Fig. 2: Coding system of assessable crown (e.g. national definition: upper third: left: 3, right:

3: defoliation score: 5 %; national definition: widest span left: 9; right: 3; defoliation score: 15

%)

4.4 Photographic meta data, photo data base and codes

Each photograph is to be provided with meta data (see Annex list ) . Information is needed

regarding i) the basic photo form, data in particular needed for the data bank and ii) the form

that is used by the photo assessor.

The data base is to be administered centrally by the PCC or through a commissioned body.

The NW-FVA is effecting initial preparations in 2010 for the institution of a photo data base

within the framework of the C1 Tree FutMon Project, which will be put at the disposal of the

central administration (PCC). The complete range of digitized photographs will be

incorporated in a central data base. The person responsible for this data base will supervise its

contents and see that everything is kept up to date. In addition, NFCs may keep regional data

banks.

Any manipulation of the photographic material may only be carried out centrally. The storage

system must have a facility which preserves all data of the original photograph, despite the

changes made to it. In addition it must be possible to index pictures hierarchically, following

certain criteria and by assigning key words. The original photo meta data of each picture must

be visible, as well as the meta data assigned for forestry use as above.

The details of the technical specifications are provided in a separate technical document. This

will include the used data management system, the entity relationship diagram which is the

basis of the database and the description of the used procedures.

Coding rules for Assessment team numbers and Photo ID see Annex.

0

1

2

3

4

5

6

7

8

9

10

0

1

2

3

4

5

6

7

8

9

10

10

4.5 Participating countries and teams

Fig. 3: Participating countries and number of teams per country

The participation at the Photo ICC was, on the whole, good. Of the 15 partners in the FutMon

D1 project, 12 responded. Furthermore, four partners formally not belonging to the D1 project

took part in the Photo ICC: Sweden, Norway, Lithuania and Estonia.

The Photo ICC concept aims to involve the directing team (National Reference Team) as well

as the executive teams, which often change from year to year, in the various countries. Only

co-operation within this hierarchy enables the making of spatial and temporal comparisons of

the rating quality on a national and international level.

Bearing this in mind, the countries are invited to participate in and make use of future Photo

ICC proceedings not only with their national reference team but with possibly all executive

teams. In particular this is recommended in countries representing large forest area and a hugh

number of teams.

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Region Number of teams

Number of assessed photos

Northern Europe

32 1918

Central Europe

65 7800

Mediter-ranean Europe

34 3089

sum 131 12717

Tree species Number of team assessments

Fagus sylvatica 97

Picea abies 65

Pinus pinaster 33

Pinus sylvestris 131

Quercus ilex 33

Quercus robur 65

sum total 424

Tab 4: Number of teams and assessed photos (above); number of trees species set assessments

by teams (below)

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4.6 Assessment quality indicators and outliers

dark Green

0

Light green

1-5

Yellow

6-10

Orange

11-15

Red

16-20

Fig. 4: Definition of assessment quality indicators and outliers. Assessment of a photograph

of a dataset concerning Quercus robur of a central European team. The x-axis represents the

median assessment of a photograph by all teams. In contrast, the y-axis shows the variability

of the teams' assessment of the respective photographs. The linear regression and a confidence

interval of 95% denote the individual teams' assessment. The photoset result of team 402 0

6006 is shown in red as an example. Assessments are classed as outliers if they are outside the

practical limit of error.

For a graphic consideration of the assessment quality in the following figures of a team the

following scale is used:

scale 1 (very good; dark green): 0 outliers.

scale 2: (good, light green) 1 - 5 outliers.

scale 3: (average: yellow) 6-10 outliers.

scsale 4 (bad; orange) 11-15 outliers.

scale 5 (very bad): more than 15 outliers.

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5. Results

The photographic assessment quality for the countries in the three European regions are

shown below.

5.1 Team assessment quality: frequencies of outliers of photo assessments

.

Fig. 5: Assessment quality of the individual teams in northern Europe. Estonia, Lithuania,

Norway, Finland and Sweden belong to this region as far as the two tree species Picea abies

and Pinus sylvestris are concerned. The numbers on the left margin are the identification

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codes for each team. In all, most teams lie within scale 1 and 2 for both tree species. For Picea

abies between 30 and 35 teams can be classed as "very good" or "good" , while for Pinus

sylvestris all 35 teams are "very good" or "good".

Fig. 6: Assessment quality of individual teams in central Europe. Slovenia, the Czech

Republic, the Slovak Republic, Romania, Hungary, Denmark, Germany and Belgium belong

to this region. Denmark assessed both the photosets for northern Europe and for central

Europe. Altogether, most teams can be classed for four tree species as scale 1 and 2 (very

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good and good): Fagus sylvatica: 64/69; Picea abies: 66/69, Pinus sylvestris: 65/69 and

Quercus robur: 63/69.

Fig. 7: Assessment quality of individual teams in Mediterranean Europe. Cyprus, Spain,

Greece and Italy belong to this region. Altogether, most teams can be classed for three tree

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species as scale 1 and 2 (very good and good): Pinus pinaster (32/38); Pinus sylvestris

(36/38), and Quercus ilex (35/38).

Altogether, the classifications very good to good (dark green to light green colour codes)

clearly predominate in all three regions. Scale "good" can contain up to 5 outliers in 30

photographs.

One should make sure that photographs present an absolutely clear view of tree crowns.

These must not be partially covered and the lighting has to be very good. Photographs,

however, only present a two dimensional and not a three-dimensional view. Detailed

observation, as can be done in the field with binoculars, is not possible.

As with all ratings, the knowledge and experience of the operators is important. By judging

the results, one must bear in mind the different experience levels of individual teams

concerning the various tree species.

5.2 Team assessment quality: variation of photo assessments. Assessments in

different countries of the same region

5.21 Region: Northern Europe

20

25

30

35

40

45

50

55

defo

liatio

n_nat_

mean

Picea abies Pinus sylvestris

Fig. 8: Variation of means per photo set of teams defoliation assessment in participating

countries (Region: Northern Europe, use of national assessable crown) Photosets of the tree species Picea abies and Pinus sylvestris were assessed for the northern

European region. With a mean of 37.9, Picea abies shows a variation of mean values of 1.003,

Pinus sylvestris (average: 34.1) of 1.017. The different values are due to photosets showing

varying degrees of defoliation. The variation of the mean values and therefore also the

assessment quality of both tree species is comparable.

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20

25

30

35

40

45

50

55

defo

liatio

n_nat_

mean

Picea abies Pinus sylvestris

59

56

55

15

13

Fig. 9: Variation of means per photo set of teams defoliation assessment per participating

countries (13: Sweden n = 15; 15: Finland n = 9; 55: Norway n = 2; 56: Lithuania n = 3; 59:

Estonia n = 1) Region: Northern Europe, use of national definition of assessable crown)

As is shown in fig. 9, variance in the different countries of one region has a bearing on

assessment quality. Thus, Swedish teams assess on average the same photos of Picea abies

nearly 7%-points more severely than Finnish teams do. Similar results are observed when

both countries are compared regarding Pinus sylvestris.

.

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Fig.10: Sum of team defoliation assessment outliers per photo set. Defoliation assessments of

Picea abies and Pinus sylvestris; numbers and signatures on the right side represent

participating countries (Region: Northern Europe, use of national assessable crown). Left

column: classification of assessment quality according to the scale shown in fig. 4. Countries:

Sweden (13), Finland (15), Norway (55), Lithuania (56), Estonia (59).

In fig. 9 the frequency of outliers in the same collective is compared. The frequency of

outliers can vary even when average assessment level is comparable. The left boxplot for

Sweden shows that individual teams assess 9, respectively 11 of 30 photographs clearly

differently.

The reasons for this differing assessment tendency cannot be established with the help of the

Photo-ICC. This is rather a job for the Field-ICCs and Expert Panel meetings.

-2

0

2

4

6

8

10

12

sum

_nat

27,5 30 32,5 35 37,5 40 42,5 45 47,5 50 52,5

defoliation_nat_mean

59

56

55

15

13

Fig. 11: Picea abies (Region: Northern Europe, use of national assessable crown). Variation

of team defoliation means (axis of abscissae) and outliers from 95 % confidence interval per

photo set per team and participating countries (ordinate); (13: Sweden n = 15; 15: Finland n =

9; 55: Norway n = 2; 56: Lithuania n = 3; 59: Slovenia n = 1).

Figure 11 shows the frequency of outliers in relation to the mean of 37.9. The 15 Swedish

teams lie partly above the total mean. However, the teams' mean values show a large margin

ranging from 32% to 50% (difference: 18 percentage points). In comparison, the Finnish

values languish in the lower range of the group. Results range from 31% up to 43%

(difference: 12 percentage points). The further a team moves from the mean value, the higher

the number of outliers generally is. Thus, for example, the Swedish team that made the

strictest assessments had 11 outliers, which means that every third assessment the team made

lies outside the 95% distribution interval.

http://dict.leo.org/ende?lp=ende&p=Ci4HO3kMAA&search=axis&trestr=0x8001

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-,5

0

,5

1

1,5

2

2,5

3

3,5

4

4,5sum

_nat

20 22,5 25 27,5 30 32,5 35 37,5 40 42,5 45 47,5


59

56

55

15

13

Fig. 12: Pinus sylvestris (Region: Northern Europe, use of national assessable crown).

Variation of team means and outliers from 95 % confidence interval per photo set per teams

and participating countries (13: Sweden n = 15; 15: Finland n = 9 ; 55: Norway n = 2 ; 56:

Lithuania n = 3 ; 59: Slovenia n = 1). Axis of abscissae from 20 to 47,5

Crown assessment of Pinus sylvestris produces no more than four outliers. This suggests that

assessment is more competent than with spruce. The difference between minimal and

maximum ranking of the countries are of a comparable size where the tree species spruce is

concerned.

22,5

25

27,5

30

32,5

35

37,5

40

42,5

45

47,5

defo

liatio

n_eu_m

ean

20 22,5 25 27,5 30 32,5 35 37,5 40 42,5 45 47,5


defoliation_eu_mean = 5,626 + ,854 * defoliation_nat_mean; R^2 = ,91

Fig. 13: Pinus sylvestris (Region: Northern Europe). Comparison between the use of the

European definition (ordinate) and the national definition (axis of abscissae) of assessable

crown. Variation of team means per photo set








20

27,5

30

32,5

35

37,5

40

42,5

45

47,5

50

defo

liatio

n_eu_m

ean

27,5 30 32,5 35 37,5 40 42,5 45 47,5 50 52,5



Fig. 14: Picea abies (Region: Northern Europe). Comparison between the use of the European

definition (ordinate) and the national definition (axis of abscissae) and the national definition

of assessable crown. Variation of team means per photo set. On all photographs both definitions of the assessable crown were used. The mean values of

the photoset assessments related to the national definition of the assessable crown are closely

correlated for both tree species with assessments using the European definition. In both cases

R2 reaches values above 0.9. Deviations from the compensatory linear slope do not show a

bias towards a certain direction. Assessment teams that over or under estimate defoliation

using the national definition do this also when using the European definition. In this region,

use of a standard definition for tree crown assessment for all of Europe does not lead to

markedly improved assessment quality.

5.22 Region: Central Europe

65 team assessments are available for central Europe for the main tree species of this region

(Fagus sylvatica, Picea abies, Pinus sylvestris as well as Quercus robur). The mean defoliation

values range from 31% with Pinus sylvestris up to 45% with Fagus sylvatica. The differences

can be traced back to differing choice of example photographs of the photosets.

The standard deviations of the main tree species are all within a similar range. They vary from

4.3 with Pinus sylvestris right up to 6.1 with the tree species Fagus sylvatica.

The results show a comparably good assessment quality of the main tree species in central

Europe.





21

15

20

25

30

35

40

45

50

55

60

65defo

liatio

n_nat_

mean

Fagus s

ylv

atic

a

Pic

ea a

bie

s

Pin

us s

ylv

estr

is

Querc

us r

obur

Fig. 15: Variation of means per photo set of teams defoliation assessment in participating

countries (Region: Central Europe, use of national assessable crown)

10

20

30

40

50

60

70

defo

liatio

n_nat_

mean

Fagus s

ylv

atic

a

Pic

ea a

bie

s

Pin

us s

ylv

estr

is

Querc

us r

obur

60

58

54

52

51

4

2


countries (2: Belgium; 4: Germany; 51: Hungary; 52: Romania; 54: Slovak Republic; 58:

Czech Republic; 60: Slovenia) Region: Central Europe, use of national assessable crown)

22

In central Europe there are also difference between countries both in the level of the

assessment and the variation within a species.

For example using the same set o photographs the assessment levelling Hungary was

somewhat higher than in Germany or Rumania.

Fagus sylvatica

-2

0

2

4

6

8

10

12

14

16

18

20

sum

_nat

15 20 25 30 35 40 45 50 55 60 65


60

58

54

52

51

4

2

Fig. 17: Fagus sylvatica (Region: Central Europe, use of national assessable crown).

Variation of team means (axis of abscissae) and outliers from 95 % confidence interval per

photo set per teams and participating countries (ordinate) Axis of abscissae from 20 to 47,5

Figure 17 shows for Fagus sylvatica the mean values determined by each team in relation to

the pooled mean of 37.9. Generally, this shows a high degree of certainty in the assessment.

For single species the assessment of the teams shows clear variation. The reason for these

differences will be discussed before the next inventory. For example, in central Europe beech

was assessed by the team from Saxony-Anhalt (Germany) as poor. In reality, this tree species

does not even occur in the area of the assessing team.








23

Picea abies

-2

0

2

4

6

8

10

12

14

16

18

sum

_nat

25 27,5 30 32,5 35 37,5 40 42,5 45 47,5 50 52,5


60

58

54

52

51

4

2

Fig. 18: Picea abies (Region: Central Europe, use of national assessable crown). Variation of

team means (axis of abscissae) and outliers from 95 % confidence interval per photo set per

teams and participating countries (ordinate)

Spruce shows a larger variation of defolkiation mean per photoset compared to beech.

However, frequency of outliers remains low, only single teams show a larger variation of

assessments.

In general, assessments of pine crowns show a similar good quality compared to spruce.

Pinus sylvestris

-2

0

2

4

6

8

10

12

14

sum

_nat

15 17,5 20 22,5 25 27,5 30 32,5 35 37,5 40


60

58

54

52

51

4

2

Fig. 19: Pinus sylvestris (Region: Central Europe, use of national assessable crown).


photo set per teams and participating countries (ordinate)









24

Quercus robur:

-2

0

2

4

6

8

10

12

14

sum

_nat

20 25 30 35 40 45 50 55


60

58

54

52

51

4

2

Fig. 20: Quercus robur (Region: Central Europe, use of national assessable crown). Variation

of team means (axis of abscissae) and outliers from 95 % confidence interval per photo set

per teams and participating countries (ordinate)

In a comparison of the most important species in central Europe, the assessment of oaks

shows a higher uncertainty than the assessment of beech. This could be due to the complex

branching structure, and branch dynamics in oak, but also the large range of appearance of

crowns in the different regions.

30

35

40

45

50

55

60

65

defo

liatio

n_eu_m

ean

30 35 40 45 50 55 60 65



Fig. 21: Fagus sylvatica (Region: Central Europe; not Germany because its use of the

European definition). Comparison between the use of the European definition (ordinate) and

the national definition (axis of abscissae) and the national definition of assessable crown.

Variation of team means per photo set.

In all photographs, by definition only the assessable crown was used. The mean value of the

assessment of the sets of photographs in relation to the national definition of the assessable









25

crown are for beech, spruce and oak strongly correlated to the assessment using a European

agreed definition.

With exception of pine the R2 values are usually between 0.8 and 0.9. There is no obvious

tendency for the differences between the degrees of fit for the slope.

Using the tow definitions, only for pine was a large variation in the values found. This could

be due to the large variation found in the shape of pine crowns, and the consequent variation

in the level of experience in the participating countries.

25

27,5

30

32,5

35

37,5

40

42,5

45

47,5

50

defo

liatio

n_eu_m

ean

25 27,5 30 32,5 35 37,5 40 42,5 45 47,5 50



Fig. 22: Picea abies (Region: Central Europe; not Germany). Comparison between the use of

the European definition (ordinate) and the national definition (axis of abscissae) and the

national definition of assessable crown. Variation of team means per photo set.

24

26

28

30

32

34

36

38

40

defo

liatio

n_eu_m

ean

20 22 24 26 28 30 32 34 36 38 40



Fig. 23: Pinus sylvestris (Region: Central Europe; not Germany). Comparison between the

use of the European definition (ordinate) and the national definition (axis of abscissae) and

the national definition of assessable crown. Variation of team means per photo set.









26

25

27,5

30

32,5

35

37,5

40

42,5

45

47,5

50

52,5

defo

liatio

n_eu_m

ean

27,5 30 32,5 35 37,5 40 42,5 45 47,5 50 52,5


defoliation_eu_mean = -1,724 + 1,053 * defoliation_nat_mean; R^2 = ,965

Fig. 24: Quercus robur (Region: Central Europe; not Germany). Comparison between the use

of the European definition (ordinate) and the national definition (axis of abscissae) and the

national definition of assessable crown. Variation of team means per photo set.

5.23 Region: Mediterranean Europe

In Mediterranean Europe, 33 team assessments are available for the photosets of the trees in

this region (Quercus ilex, Pinus pinaster and Pinus sylvestris). The average defoliation value

for the 3 species are comparatively similar between 25.4 and 30.9%.

The standard error for the species is similar to other tree species and regions. This ranges

from 3.8 for Quercus ilex to 5.9 for Pinus sylvestris.

The results show a high degree of quality in the assessment of trees in Mediterranean Europe.

Despite the narrow framework given by the 25% and 75% percentiles in Pinus sylvestris

single teams show a large variation both above and below the mean.

Even when the data set is separated by tree species and country (Fig 26) similar mean values

for a photoset are found for a tree species, but there is considerable variation between the

single teams.





27

10

15

20

25

30

35

40

45

defo

liatio

n_nat_

mean

Pinus pinaster Pinus sylvestris Quercus ilex

66

11

9

5


countries (5: Italy; 9: Greece; 11: Spain; 66: Cyprus) Region: Mediterranean Europe, use of

national assessable crown)

Figures 26 to 28 show the occurrence of outliers in relation to the pooled mean of the

Mediterranean species. In comparison to the graphs used to present the values from North and

central Europe the x-axis has a wider scale. For example, the x-axis in Fig 19 is from 22 to 55,

in comparison in Fig 26 only from 18-36. The loosely distributed cloud of points should

however not give the impression that the assessment in southern Europe does not provide a

good assessment of the mean value of the respective photosets. The outliers are generally low,

even if single teams show clear differences to the mean assessment value.

Quercus ilex

-1

0

1

2

3

4

5

6

7

8

9

sum

_nat

18 20 22 24 26 28 30 32 34 36


66

11

9

5

Fig. 26: Quercus ilex (Region: Mediterranean Europe, use of national assessable crown).


photo set per teams and participating countries (ordinate)





28

Pinus pinaster

-2

0

2

4

6

8

10

12

sum

_nat

17,5 20 22,5 25 27,5 30 32,5 35 37,5 40 42,5


66

11

9

5

Fig. 27 : Pinus pinaster (Region: Mediterranean Europe, use of national assessable crown).


photo set per teams and participating countries (ordinate) Pinus sylvestris

-2

0

2

4

6

8

10

12

sum

_nat

10 15 20 25 30 35 40 45


66

11

9

5

Fig. 28: Pinus pinaster (Region: Mediterranean Europe, use of national assessable crown).


photo set per teams and participating countries (ordinate), use of national assessable crown).

In Mediterranean Europe on all photographs both definitions of the assessable crown were

used. The mean values of the photosets assessment based on the national definition of the

assessable crown compared the European definition are for southern Europe less closely

correlated compared to central or northern Europe. The R2 values are 0.41 for Pinus sylvestris

and 0.65 for Pinus pinaster. Quercus ilex has a good value of 0.65. Again the variation in









29

values is greater for Pinus sylvestris than for the other species. There is also a great variability

in the crown forms of pine in Mediterranean Europe.

16

18

20

22

24

26

28

30

32

34

36

defo

liatio

n_eu_m

ean

18 20 22 24 26 28 30 32 34 36



Fig. 29: Quercus ilex (Region: Mediterranean Europe). Comparison between the use of the

European definition (ordinate) and the national definition (axis of abscissae) and the national

definition of assessable crown. Variation of team means per photo set.

17,5

20

22,5

25

27,5

30

32,5

35

37,5

40

42,5

defo

liatio

n_eu_m

ean

17,5 20 22,5 25 27,5 30 32,5 35 37,5 40 42,5



Fig. 30: Pinus pinaster (Region: Mediterranean Europe). Comparison between the use of the











30

22

24

26

28

30

32

34

36

38

40

defo

liatio

n_eu_m

ean

10 15 20 25 30 35 40 45



Fig. 31: Pinus sylvestris (Region: Mediterranean Europe). Comparison between the use of the



6. Conclusions

The co-ordination office of the new photo ICC method at the Northwest Germany Forest

Research Institute (NW FVA) Göttingen has been supported by experts. Arthur Bauer, Inge

Dammann, Jörg Weymar, (Germany), Ludmilla Bohacova (Czech Republic), Paloma Garcia

P.(Spain) and Sören Wulff (Sweden) by acting as experts have greatly contributed to the

acceptance of the method, and have been available to give advice. Continued use of this

method greatly depends on the support of experts for the whole EU.

The newly developed method, first applied in 2010, was initially used on the most

economically important and common tree species. For each of the species a forest scientist

assessed a photoset which documented the differing vitality of the tree crowns. Care was

taken to ensure that all types of crown were represented, for very well leaved or needled

crowns to very poorly.

The photoset from each region and species was composed of 30 photographs. The 30

photographs were taken from a larger data set, and can vary for assessment to assessment.

This is used to prevent any memory-effects of the photographs of the assessment teams.

To remove errors created by poor quality images of the crowns, only the best visible trees and

the best quality photographs were used. As such, the use of these photosets does not reflect

reality, where often in closed forests such easily visible trees are rare. To make the images of

the photosets comparable, the images were printed and sent to the assessment teams. After the

assessment the photographs were returned to the co-ordination office.

The good acceptance of the photo ICC concept, the active participation, the high quality

results, as well as the database of results and images developed at the NW FVA can be used

as evidence that the quality assurance programme should continue.

To show the strengths and weakness of the quality control of the two methods, field ICC, and

photo ICC, a comparison is summarised below.





31

Advantages of the photo ICC concept.

A large number of photographs in the database ensure that for north, central and

southern Europe a sufficient number of samples for all of the most important tree

species in all degrees of defoliation are available.

The definition of the assessable crown varies greatly between different European

countries. Using the low cost photo ICC method it is possible for the first time to

compare the country specific definitions with a European definition.

Especially for pine using the European definition of the assessable crown greatly

improved the comparability of the assessment of crown condition across Europe.

The photosets used in 2010 can be used in the coming years. A comparison to these

photographs provides a control to maintain a constant baseline for investigations

carried out over many years.

Easy access to the photographs ensures that many teams can take part in the

assessment. Quality control can be carried out by a country team leader on

assessments carried out by regional or temporary teams within that country.

The use of photographs makes the quality control independent form plot and tree

selection. It allows assessment of quality for both the classical Level 1 method using a

16 x16 grid, and for national inventories or intensive measurements. The method is

even flexible enough to accommodate changes in methodology during the observation

period.

The databank developed contains the photographs, but also metadata of site, tree and

assessment date. The assessment values are thus safely stored for a long duration.

The photographic method is de-centralised, requires little time, and is high value for

money.

Disadvantages of the photo ICC concept.

The photographs are only two dimensional images of trees and forests

The photographs are unable to provide an assessment of the crown combined with

other relevant symptoms such as abiotic and biotic parameters. A holist assessment of

tree vitality is lost.

Up to now only the parameter defoliation is considered. The first advances are being

made in a method that includes biotic indicators such as fungi and insects. In the

future these will be included in the manual.

The photographs do not allow the observer to include the status of the tree. Up till now

no information about region, climatic conditions or position in the forest are given.

The images abstract the crown condition taken under field conditions to an ideal

image, which does not occur in real inventories. Any assessment carried out in the

forest requires a translation of the photographs to reality.

The photographs for the whole of Europe represent possibly only a small section of the

real extent. For example, the Alps and the Netherlands are grouped into central

Europe. In both the areas the same tree species can be found, but with certainty they

differ in appearance.

Until now mainly mature trees were used. Under real conditions tree are of all ages.

The photosets should be further developed to represent all ages classes.

The photograph concept is de-centralised, and does not provide a European platform

for the exchange of experts. The essential exchange of ideas does not take place.

32

7. Recommendations

From the evaluation of the advantages and disadvantages of the new photo ICC concept, the

following recommendations have been reached.

The photo ICC and field ICC methods should in the future be temporally linked.

The field ICC method should be repeated annually in all 3 European regions.

The photo ICC method should be repeated in 2 yearly intervals

The photo ICC should become an independent assessment using the common

definition of the assessable crown.

In future the photosets should be supported by further indicators of crown vitality

The photosets should be further developed to increase the number of different age

classes

33

ANNEX

Annex 1: Frequency distribution of tree species (number of trees) and EEA forest

types according to Level 1 net of ICP Forests.

Picea

abies Pinus sylvestris

Fagus sylvatica

Quercus ilex and Q. rotundifolia

Pinus pinaster

Quercus suber

Quercus robur, Q. petraea

Abies alba

Picea sitchensis

All species

BOREAL 3987 5772 11209

HEMIBOREAL 4219 6371 108 109 11547

NEMORAL

ALPINE CONIFEROUS

2314 958 290 1135 5805

ACIDOPH. 143 787 1012

OAK

MESOPHY. DECIDUOUS

258 3174 5285

BEECH 3536 306 4498

MONTANE BEECH

143 2871 3490

THERMOPH. 201 6306

DECIDUOUS

EVERGREEN BROAD-LEAVED

3462 389 4289

MEDITERR. CONIFEROUS

1300 99 1736 7680

MIRE 483 652

SWAMP

FLOODPL. 303 613

FORESTS

ALDER. BIRCH. ASPEN

176 3781

PLANTATIONS 1295 676 378 140 104 246 6601

NOT YET CLASSIFIED

4712 8737 1641 122 1550 398 21117

ALL FOREST TYPES

17027 24585 8897 3725 2300 460 6714 1828 327 93887

34

Pictures in the database

Region name species numbers preassessed

Min Max mean

Northern

Europe

Picea

abies

30 5 95 43,3

Northern

Europe

Pinus

sylvestris

30 5 95 36,8

Central

Europe

Fagus

sylvatica

53 0 95 43,9

Central

Europe

Picea

abies

41 10 90 40,4

Central

Europe

Pinus

sylvestris

60 0 95 25,8

Central

Europe

Quercus

robur

30 15 90 47,6

Mediterranean

Europe

Pinus

pinaster

50 5 75 20,5

Mediterranean

Europe

Pinus

sylvestris

72 5 95 23,75

Mediterranean

Europe

Quercus

ilex

43 5 85 27,4

Submission form of the participants’ assessments in 2010

Nation Team number

Name teamleader

Date of assessment

Coordinator Name (given) Email (given)

Organization

Address (organization):

Tree Species

Photo ID (Code).

Assessed crown (EU) Defoliation Assessed crown (national)

Defoliation comment

Left scale Right scale

Left scale Right scale

#001

#002

#003

…

#029

#030

Comments (Problems, photo, quality,…

35

Photographic meta data

i) mandatory data of the basic photo form

photo identity (code printed on each photo and identity in the data base).

date

ownership

location (country, region)

agreement by photo delivering institution that printed photos may be used for the purpose

of Photo ICCs

tree species

EU wide definition of assessable crown regarding the respective photo. Definition should

be given as scale values left and right, e.g. see fig. 3

preassessed defoliation (EU), assessment done by reference team (eco region coordinator)

to get an overview of the defoliation range of the stored photos

ii) mandatory data of the assessors photo form

given: ID Code printed on the photo

nation

team leader

given: name coordinator

team number

given: tree species

used national definition of assessable crown scale values left and right, e.g. national: (4/6)

2010 only: given: used EU def of assessable crown, scale values left and right, e.g. (6/6)

defoliation (national)

2010 only: defoliation (EU)

Comments (problems...)

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