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Towards Harmonization for Monitoring Key
Forest Variables in Europe Using Earth
Observation Data 1
Sten Folving2
Pam Kenned y 2
Niall McCormick2
Abstract-The Member States ofthe European Union established
the European Forest Information and Communication (EFICS)
Program in 1989 with the aim to improve forest information in
Europe and to facilitate the availability of the information. In 1994
the Space Applications Institute ofthe European Commission set up
the Forest Information from Remote Sensing (FIRS) Project in order
to support EFICS by developing methods for deriving forest information from earth qbservation data, principally mapped, geo-referenced
information but also statistical data. Two studies carried out in the
frame of these two activities clearly revealed the need for harmonization of the nomenclature and the defInitions and methods used for
assessing the forest variables within the Pan-European area.
As mapped forest information is lacking for most of Europe it has
been considered practical to combine the provision of harmonized
key variables with the development of methods for, eventually,
providing the information in geo-referenced mapped format as
derived from remotely sensed data. The use of earth observation
data furthermore provides a continuous monitoring capability of
some ofthe key variables which can be assessed by remote sensing
at an acceptable degree of precision and accuracy. Therefore, several development studies on application of remote sensing for PanEuropean forest monitoring have been launched, e.g. forest area,
species composition, structural diversity and change. These development studies are being supported by research projects under the
so-called Framework Program of the European Commission.
The member states of the European Union (EU) have not
agreed upon a common forestry policy. Wood products were
not among the commodities included in the original treaty,
and forestry as such has not been included in the EU
common agricultural policy (CAP). However, the European
nongovernmental and governmental forest organizations
have expressed their need for close cooperation, not least due
to the fact thatEUROSTAT, (the statistical office of the EU),
is obliged to collect reliable statistics on the EU forest sector.
Thus, the Standing Forestry Committee (SFC), an advisory
body to the European Commission (EC) was established in
1989. The SFC, assisted by the Working Party on Forestry
Statistics under the Agricultural Statistics Committee of
EUROSTAT, is the main player in EU forestry matters.
Ipaper presented at the North American Science Symposium: Toward a
Unified Framework for Inventorying and Monitoring Forest Ecosystem
Resources, Guadalajara, Mexico, November 1-6,1998.
2Forest and Catchment Sector, Environmental Mapping and Modeling
Unit, Space Applications Institute, Joint Research Center of the European
Commission, 21020 Ispra (VA), Italy. e-mail: sten.folving@jrc.it
USDA Forest Service Proceedings RMRS-P-12. 1999
Major decisions can only be taken by the Council, the
assembly of EU ministers responsible for forestry in their
respective countries.
In 1989 the SFC had the so-called EFICS (European
Forest Information and Communication System) regulation
approved by the Council. The EFICS regulation requests the
EC to provide a frame for collecting, coordinating and processing data concerning the forestry sector and its development. The EFICS is planned to take account of existing data,
and in particular statistics compiled by EUROSTAT. It will
make use of information available in the Member States,
and in particular data contained in national forest inventories and any other relevant databases accessible at community and international level. But, still it is the SFC that has
the mandate to decide on both the actual content and the
implementation. The EFICS regulation has been extended
until the year 2002.
Concurrently with the preparation of the EFICS regulation the Joint Research Centre (JRC) of the EC initialized
and implemented a European program (the European Collaborative Program for the use of high resolution Second
Generation Earth Observation Satellites iIi the Management of the Less Favoured Areas) ECP. The ECP had the
main objective to test the applicability of remotely sensed
data in local management, e.g. land use planning and forestry, and to assist local users in the application of earth
observation (EO) data for their own specific purposes (Folving
and Megier, 1992). The idea was to create a link between
practical local management and a centralized information
system.
The ECP clearly revealed wide interest from the forestry
community in using remotely sensed data in daily management. Via the ECP it became evident that the main obstacles
for using EO data were found in the cost of the data and the
lack of cheap, user friendly software. Due to the principle of
subsidiarity the program was stopped in 1992, and the
development of methods for application of remotely sensed
data for local forest management was suspended accordingly.
In 1994, the FIRS (Forest Information from Remote Sensing) Project was launched in support to EFICS. The idea was
to utilize the results from the ECP to implement the practical application of EO data in the monitoring of European
forest areas (Kennedy et. aI., 1994).
The main objective of the FIRS Project is to contribute to
the development of a unified European forest information
system (i.e., EFICS), by developing methods for providing
both sectorial (i.e. production- related) and environmental
(i.e. ecology-related) forest information in the form of both
371
statistical and mapped data - with emphasis on mapped data
(Folving et. aI., 1995; Kennedy et. aI., 1995). The methods are
based on the application of EO data and GIS techniques.
Three basic inputs had to be created before the actual
method development and their applications at a Pan-European scale could be fully embarked upon. Firstly,
regionalization of the Pan-European area into major forest
ecosystems had to be produced because it was foreseen that
the methods had to be adjusted to "local" forest characteristics. This work was finished in 1995 and the results have
been published (e.g., SAl, 1995) and are illustrated on the
WWW (http://www.jrc.sai.egeo.firs). Secondly, a system of
nomenclature had to be defined which could be applied to the
Pan-European area using EO data. This work was finished in
1996 (Kohl and Paivinen, 1996) and is available at the same
UTL address given above. Thirdly, a network of common test
areas had to be selected, and so-called 'ground truth' for each
site had to be provided. Due to a number of constraints, not
least costs and the lack of harmonized information, such a
network could not be established per se. It was therefore
decided that test areas, and the data from these would be
compiled in an ongoing manner through the various subprojects or application modules of the FIRS Project.
Three major applications modules will be described in §3.
Studies on nomenclature are dealt with in the next section
which will also looks at new requirements in the ED for
forest monitoring, in terms of the development of the Common Agricultural Policy (CAP). Section 4 presents the very
preliminary work being done to address the challenges for the
newest environmental trend in requiring sustainable development, preservation and enhancement of bio-diversity.
Harmonization of Nomenclature and
Information Priorities
For many years organizations like EUROSTAT and UNFAO (United Nations - Food and Agriculture Organization)
have compiled and published statistics on forests and forest
products. This statistical information is based on national
statistics. However, recent international conventions such
as the Convention on Biological Diversity, the Ministerial
Conference on the Protection of Forests in Europe require
new types of information and new data to be collected.
When the FIRS Project was launched, high priority was
given to studies dealing with the definition of the European
user needs concerning forestry and how the existing variations in assessment methods, nomenclature and definitions
could be dealt with. The aim was to provide a proposal for a
common nomenclature to be used for the EO data applications. The first study was very much directed towards
spatial, geo-referenced information.
In parallel, the EFICS Program launched a more general
study on the same theme, but which was not restricted to the
application of EO data. The study reviewed the majority of
NFl systems currently in existence in Europe. The results
are published in - European Commission, 1997.
The FIRS Project's Nomenclature Study
This study was carried out by a working group lead by the
EFI (European Forest Institute) and the Swiss Federal
372
Institute for Forest, Snow and Landscape Research (Kohl
and Paivinen, 1996). Three main "user" groups were asked
which forest attributes were of most interest to them, and
then to rank these attributes according to importance. The
result is summarized in Table 1. AI though, as expected, most
attributes are common to the three user groups, as expected,
their priorities are somewhat complementary. 'Forest area'
is ranked as a high priority by all groups, 'bio-diversity' and
'landscape-related' attributes are ranked very low by foresters engaged in forest productivity. Foresters mainly working with environmental protection and landscape management, however, put little emphasize on productivity
information.
Interestingly, several of the attributes requested are not
included in many existing National Forests Inventories.
This is especially true for many of the newly requested
environmental attributes. Some of these parameters are,
however, available from other sources or organiza tions, such
as information on soil and water.
The last column in Table 1 reveals that several attributes
need to be harmonized because currently no common nomenclature or assessment method exists in Europe. This is
somewhat worrying as it also clearly indicates that international statistics compiled from national statistics may not
always produce comparable data.
The feasibility of using EO data (from high, medium and
low-resolution sensors), for assessing the attributes at various scales was also investigated. The outcome, summarized
in Table 2, shows that high resolution EO data are potentially
very important for assessing and mapping forest attributes
but that data from instruments with medium to low spatial
resolution are of little interest in European forestry.
The feasibility of using EO data for forestry was also
discussed in working groups set up as part of two international workshops initiated by the FIRS Project. One in
J oensuu, Finland, (Kennedy et. al., 1995) and one in Vienna,
Austria, (Kennedy, 1997). The groups discussed and evaluated the potential of using remote sensing for the assessment of key forest attributes. On the first occasion the group
was also asked to evaluate the potential for using remote
sensing operationally for mapping of the forest attributes at
the European scale (Table 3).
The interesting point is that foresters in academic research have rather low expectations ofthe application of EO
data, whereas foresters dealing with practical inventory
problems seem to have larger expectations of remote sensing
technology (Tables 1 and 2). It is also interesting to note that
there has been very Ii ttle change in expecta tions of academic
foresters over a 2-year period. However, the launch of several SAR (Synthetic Aperture Radar) instruments seems to
have created at least a small improvement in the expectation towards the use of microwave data in this field.
The EFICS Information Needs Assessment
In 1996, the European Commission decided to launch a
detailed study on information needs, data acquisition methods etc., in Europe to support the EFICS. The European
Forest Institute led the consortium carrying out the work.
The Study is unique in providing a full overview, and
comparison of forest surveys and inventory systems in 22
European countries (European Commission, 1997b).
USDA Forest Service Proceedings RMRS-P-12. 1999
Again the difference in priorities between "production"
foresters and "environment" foresters is evident. The ranking of attributes in Table 4 has been carried out using
questionnaires. A total of 500 questionnaires were sent out,
a little less than half, 43%, were returned. The organizations
or persons contacted were asked to list and rank the 15 most
important attributes. The rankings of 'important' and 'very
important' are used for the total ranking in shown in Table
4. The study revealed slight differences in regional interests
in Europe. Northern European countries seem to be a little
more interested in forest volume and in costs, whilst in
central Europe the protection function of the forests seem to
be of greater concern, than in the other parts of Europe.
Northern European countries are unique in listing timber
quality, the Atlantic countries in afforestation and central
Europe in woody biomass, recreation and non-wood goods.
In general, forest area (83% ofthe replies) and tree-species
composition (79%) are the most important attributes, followed by protection functions (77%) and nature conservation
area, volume of annual increment and cut (76%) and, finally,
the attribute biological richness (75%) and diversity (7%).
Growing stock volume (71%) and Health (69% of the replies) are also considered of high interest.
Putting the Nomenclature System Into Use
The interest of having a common nomenclature and common assessment methods is not just due to the need for
comparable statistical information. It is also linked to needs
created by the Common Agricultural Policy of the ED, and to
a strong political need for rural development, especially in
the so-called less favoured areas. The less favoured areas of
the ED are of course defined in economic terms, but, more
often than not they correspond to the mountainous and hilly
regions, and are frequently characterized by forested or
other wooded land. Such areas are also the most important
sources for fresh water.
Table 1.-The ran kings of the forest attributes according to the FIRS Project's information needs assessment.
Attributes
Land cover (type, density etc.)
Actual forest area
Other wooded area
Potential forest area 1
Stand structure (Species composition, layers, density.)
Age
Diameter
Height
Q~~
Health
Defoliation
Damage (fire, storm, ins., diseases, game, pollution)
V~~e
Assortments
Timber value
Woody biomass 1
Herb biomass 1
Growth/Increment
Drain/removals
Soil types 1
Site factors
Vegetation types
Topography
Climate1
Productivity
Regeneration
Stand history
Ownership
Management objective
Value of protected infrastructure 1
Water resources 1
Protection status 1
Naturalness 1
Threats to species diversity 1
Environmental impact1
Non-wood goods and services1
Scenic beauty1
Ranks for information groups
Land use
Production
Environment
5
1
12
6
2
4
2
2
2
3
3
6
3
9
12
8
1
1
~
11
2
8
8
2
4
1
3
3
11
13
3
13
13
12
6
4
11
5
13
13
9
11
12
7
7
14
~
5
4
10
9
8
3
6
10
7
4
9
8
14
13
9
9
16
3
5
1
6
5
7
7
7
14
9
5
3
4
2
minor
required
existing
required
required
required
required
2
2
2
1
1
1
1
required
8
4
6
10
3
required
required
required
7
6
12
15
14
10
2
3
2
Need for
harmonization
minor
required
required
5
8
5
2
6
9
4
6
required
required
required
~
1Attributes not assessed by most of the national forest resource assessments.
1 highest rank - 5 lowest rank.
USDA Forest Service Proceedings RMRS-P-12. 1999
373
Rural development and a Common Agricultural Policy are
synonymous with the payment of subsidies. Within the EU,
this means subsidies for taking land out of agricultural
production, subsidies for afforestation on these so-called set
aside land, and subsidies to the farmer until the point in time
when the newly forested areas provide an income. Harmoni-
zation at the European level is therefore a necessity to aid
the implementation of tools to control the expenditure of the
subsidies which are allocated and implemented on the basis
of 'local' or regional conditions.
The most recent EC regulation on the Common Agricultural Policy and Rural Development is not yet available.
Table 2-Feasibility of using Earth Observation data at various resolutions.
Attribute
Ha
Forest area
0.5
1
10
100
0.5
1
10
100
0.5
1
10
100
0.5
1
10
100
0.5
1
10
100
Tree
stand
Tree
stand
0.5
Other wooded land
Land cover
Stand structure
Vegetation type
Diameter
Height
Volume
Woody biomass
Drain/removals
Damage
Health
Increment
Topography
10
1QO
0.5
1
10
100
0.5
1
10
100
0.5
1
10
100
tree
0.5
1
10
100
0.5
1
Spatial patch arrangement 0.5
1
10
100
374
Nomenclature
Definition
High
Forest cover 21 -100 %
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Open forest, forest cover 5 - 20 %,
species able to grow> 7m
Open forest, forest cover 5 - 20 %,
shrubland 21 - 100 %
Crown density in 5 % classes
Crown density in 20 % classes
Crown density in 40 % classes
Crown density in 40 % classes
Species spp.
Stand mean diameter,
1.3 m diameter
Height of single tree,
Mean height in 5 m classes
Above ground volume of standing trees
50 cubic meter pr ha classes
Dry weight of woody plants
50 t pr ha classes
Over bark volume of trees
In 50 cubic meter pr ha classes
Two classes:
>50 cubic meter pr ha
no damage
Crown thinning characteristics
like: shape and color
Increment between two
successive assessments
50 cubic meter pr ha pr 5 years
No
?
Yes
Yes
No
?
Yes
Yes
No
?
Yes
Yes
No
?
Yes
Yes
?
?
Yes
Yes
No
?
?
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Elevation in 100 m classes,
Aspects in 8 categories and slope in 10% classes,
Relies in plane, convex and concave
Dominance, contagion, fractal dimension etc.
Feasibility
Medium
?
?
Yes
Yes
Yes
Yes
?
No
No
?
Yes
No
No
?
Yes
No
?
?
Yes
Yes
?
?
Yes
No
No
No
?
Yes
No
?
No
?
Yes
Yes
Low
No
No
No
?
No
No
No
?
No
No
No
?
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
USDA Forest Service Proceedings RMRS-P-12. 1999
Table 3.-Potential of Remote Sensing for mapping forest attributes.
Potential of using EO-data1
O~tical data
Active microwave data
Attribute
Forest / non-forest
Coniferous / broad-leaved
Broad-leaved genus
Coniferous genus
Biomass and volume
Closure
Stage of forest development
Spatial diversity - fragmentation
Hydrological conditions
Infrastructure .
Topography
Drastic & rapid changes
Slow & gradual changes
1994
1996
1994
2
2
4
2
2
4
3
3
3
3
4
4
4
4
4
4
4
4
2
2
3
3
2
4
2
4
3
3
1
1
2
1
1
2
3
4
2
4
4
1996
Operatlonallty2
3
1
1
4
4
4
4
4
3
3
3
4
2
3
3
3
2
2
2
2
3
3
2
2
2
3
1Potential: 1 = very high; 2 = high; 3 = moderate; 4 = poor.
20perationality (at a European scale): 1 =operational; 2 = semi-operational; 3 = research.
What is well known however, is that the conventions on biodiversity and sustainable development of forests in the
context of rural landscape will be included. This means that
there will be a need for much stronger links between the
forestry sector and the environmental organizations on the
requirements for maintenance of ecological values. These
links will undoubtedly benefit from having a harmonized set
of definitions when dealing with the forest ecosystems.
As a consequence, in order to incorporate these shifts in
policy, the FIRS Project was partly re-focussed at the beginning of 1997 (E.C., 1997). The aim is to accommodate, as far
as possible, the new requirements, and to integrate the new
needs emerging from EU regulations. The key attributes
needed by environmentalists and ecologists had to be incorporated and more efforts are being placed on the mapping
and monitoring forests rather than on statistics. Six attributes were selected as prime foci of the FIRS Project.
These are, in order of present'priority: 1) forest area; 2) other
wooded land; 3) structure and composition; 4) volume, biomass and fuel; 5) bio-diversity; and, 6) environmental indicators. Special emphasis should be given to change in these
attributes. Some of the major on-going projects dealing with
the provision of information on these attributes at the
European level are described in §3.
One result of adopting these new developments has been
that new challenges come to the surface. There is an urgent
need for example, to be able to assess the precision and
accuracy of spatial data, and to study Europe, less as a
continent of countless administrative divisions, as is done
for the more traditional statistical reporting, but more as a
geographic entity divided into facets governed both by natural environmental features and socio-economic activities.
There is a shift therefore, to utilize natural watersheds in
order to allow holistic approaches to studying and understanding entire forest ecosystems and their functions.
On-Going Projects
The research and development (R&D) activities being
coordinated, monitored and undertaken within the FIRS
USDA Forest Service Proceedings RMRS-P-12. 1999
Project are outlined in Table 5. Only a small part of the RID
is carried out in-house as the policy of the EC is to involve the
Member State institutions as much as possible. The contracted R&D is competitive and to a large extent being
financed by other EC services which have specific interests
in the results or methods developed. The FIRS Project is also
engaged in third party work and participates in Share Cost
Actions, whereby studies are selected and 50% funded by the
EC. The FIRS Project also assists the Directorate General in
the coordination of the forest R&D projects which include
components utilizing remote sensing techniques. Two major
projects, a "Pilot study in the field of monitoring forested
areas" and the "Forest Monitoring in Europ~ using Remote
Sensing (FMERS) Project" deal with assessing the forest
attributes identified as priority variables in Europe. These
are mapping forest and other wooded land the identification
and monitoring of criteria and indicators of structural biodiversity and biomass estimation.
A project entitled "An AVHRR-based probability map"
aims at the provision of a tool for probabilistic mapping of
forest areas in Europe using statistics from EUROSTAT.
The project with Regione dell'Umbria is a support study to
the Share Cost Action entitled MARIE-F (Monitoring and
Assessment of Resources in Europe - Forest) in which the
FIRS project is a partner. All these projects supply input for
the in-house R&D (primarily software development and
modelling), and assist in providing the necessary background information for the definition of new R&D actions.
Changes in Forest Lands
The objective of the project "Pilot study in the fields of
monitoring forested areas" is to develop standardized
methods for using remotely sensed data and GIS techniques for the provision of statistical and mapped data on
European forest resources. The developments are based on
existing experiences and will provide cost-effective tools, for
long term monitoring of the structural bio-diversity and
major changes of the forested areas of Europe.
375
Table 4.-The final ranking of the most important attributes
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Decrease of forest land
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8
4
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2
11
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1
4
8
3
3
4
5
1
8
4
6
5
9
5
Protective function and natural conservation
5
Volume of annual cut
6
8
3
Volume of annual increment
7
10
3
Biological richness and diversity
8
6
3
Changes in growing stock volume
9
9
10
2
11
10
Growing stock! stem volume
11
8
Transfer of 'exploitable forest' to other use
13
13
Exploitable forest
14
13
17
18
Timber quality/ assortments
19
Forest damage (excluding fire)
19
Woody biomass
21
Productivity/ site quality
22
Recreation! nwgs
23
Wildlife habitat
24
Potential land for afforestation
25
Vegetation type
26
5
27
11
28
23
Changes in above-ground biomass
3J
Total biomass
31
13
4
9
2
11
10
6
9
11
1
5
13
12
5
32
11
11
Stand structure (density, layers)
33
Accessibility
35
~
9
9
3
33
~
9
4
10
13
9
14
9
Landscape/ scenic beauty
Soil
6
4
5
12
Recreation! forest area
Forest damage by fire
5
8
Silvicultural treatment
"Naturalness"
6
11
9
6
10
5
11
Ia
a:
3
2
9
11
m
3
11
Ownership
Volume of mortality (natural losses)
5
3
Health condition! vitality of standing trees
~
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Increase of forest land
Protection function
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Tree species composition
15
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Plantations
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USDA Forest Service Proceedings RMRS-P-12. 1999
Table 5.-The major studies of the FIRS project.
Activities within the FIRS project
Contracted R&D projects
Financed by
Consortium
Pilot study in the field of
monitoring forested areas
Directorate General VI, Agriculture, fisheries
and forestry
GAF mbH, Germany, JOANNEUM Research, Austria,
IVL, Sweden Agence M.T.D.A., France University of
Freiburg, Germany
FMER8-1 Forest mapping
CEO Project
VTT Automation, Finland CESBIO, France European
Forest Institute, Finland SCOT Conseil, France University
of Bologna, Italy (+ nine associates)
FMER8-2 Bio-mass
assessment
CEO Project
SSC, Sweden METLA, Finalnd SLU, Sweden ISA,
Portugal
AVHRR Forest Probability
Map
EGEO
VTT, Finland
MARIE-F- Regione
dell'Umbria
EGEO
Regione dell'Umbria Forest Department, Italy
Share cost projects and third party work
MARIE-F
DG XII-8hare cost action
EARS, Holland FIRS, Joint Research Centre, University
of Freiburg, Germany METLA, Finland University of
Leicester, England CEMAGREF/ENGREF, France
Evaluation of RS data for
classifying and mapping the
forests of Ireland
Irish Department of Agriculture, Food and
Forestry
Coillte Teoranta, Ireland FIRS, Joint Research Centre
NRSC, England
Coordination and technical assistence in support to other services of the European Commission
The study consists of two parts: 1) Forest monitoring:
The objective here, is to develop and demonstrate a system
to identify significant changes in forest cover. The major
focus will be on the detection of changes that differ from the
normal vegetative succession ofthe ecosystems. Such changes
are for example, related to growth conditions, cuttings and
damage. The system will be as independent from ground
data as possible. The performance of the system will be
based on optical satellite data, and facilitate both large and
small-scale monitoring capabilities. 2) Structural diversity: The aim ofthis component is to define, develop and test
a system for monitoring the structural diversity of forested
areas. Pilot studies are being carried out in the main forest
ecosystem regions of Europe. The system will be based on
high and medium spatial resolution satellite data, and will
be able to discriminate forest patches and classify them
according to content and shape. The system is linked to the
change detection system developed in the first part of the
project.
Forest Monitoring in Europe (FMERS-1)
Study
The FMERS project has two parts. Part 1 focuses on the
applications of medium spatial resolution EO data for large
area forest mapping. Part 2 is a research and development
study to evaluate EO data for assessing the above-ground
woody biomass of forest and other wooded land in Europe.
The main objectives of the forest area mapping component
of the FMERS project are: 1) to investigate the utility of
medium spatial resolution satellite data for forest monitoring at a European scale; and 2) to complement the forest data
already being collected by the national forest inventories
using more traditional methods.
USDA Forest Service Proceedings RMRS-P-12. 1999
The project will develop and implement methods for using
both optical and microwave remotely sensed data for the
provision of standardized geo-referenced information (i.e.,
location, size and composition of forested and other wooded
land) and for the provision of statistical information (i.e.,
area estimates) describing the forests and other wooded
lands in Europe. The first part of the study developed the
methodology and tested the applicability of the developed
method in test sites located in the major forest eco-regions of
Europe (Hame et.al., 1998). The second part is focusing on
two large study regions, one comprising the Atlantic and
Mediterranean forest types, the other the boreal and central-western European temperate forest regions. The aim is
to evaluate and quantify the differences both in technical
and financial terms between using medium and high spatial
resolution satellite data for mapping, and for deriving area
estimates of the main forest categories and their composition (groups of main species) of both forest and other wooded
land. It is also the aim to clearly identify the potential and
limitations of these satellite data to complement the more
traditional methods, and to investigate the portability of the
methods to the entire continent of Europe for up-dating on
a 3 to 5-year basis.
Forest Monitoring in Europe (FMERS-2)
Study
The objective of this study is to evaluate remotely sensed
data for assessing the above-ground woody biomass, (and
volume where feasible), of forest and other wooded land of
Europe. The study will develop models which can be used
with remotely sensed data and calibrated using ground
information, for deriving estimates of above-ground woody
biomass for large regions. A boreal and an Atlantic-Mediter-
377
ranean test-area have been selected to test the approach. In
both test areas the model and approach will be investigated
at three different pixel resolutions. These are:- I) very high
(less than 10 m pixel); II) high (less that 100 m pixel), and III)
medium (between 100 and 300m pixel). The very high
resolution data will be simulated from air photographs. The
analyses of the method-performance in the test areas will be
used to evaluate the possibilities of utilizing the approach at
a European level.
MARIE-F Study
The FIRS project is a partner in the project's team, but,
has at the same time contracted a supporting study to one of
the regional forestry authorizations in Italy. The objectives
of the study are:- 1) to investigate and develop an objective
satellite-based methodology for inventory monitoring of
forest timber and forest vitality in Europe using a Forest
Light Interaction Model (FLIM) developed by the leading
partner at EARS in Holland, and 2) to evaluate the potential
of the model to provide uniform and comparable forest
baseline data and statistics, for larger areas and at lover
costs, in support to national and European forest strategies.
The Regione dell'Umbria Forest Department assists the
FIRS Project in assessing and evaluating the performance
and utility of the outputs from the model once applied to
forest land in Umbria.
Evaluation of Remote Sensing Data for
Ireland
The in-house developed software package, SILVICS,
(McCormick, 1998; McCormick and Folving, 1998) which
has been developed under the FIRS project has been improved and adapted to large scale real application within the
frame of a third party contract from the Irish Department on
Agriculture, Food and Forestry. SILVICS is a user-friendly
software package, which runs on most computer platforms,
and which provides advanced techniques for the geometric
and radiometric correction, structural and statistical analysis, and classification of multispectral satellite imagery. The
software is being implemented as part of a national forest
inventory in Ireland.
Figure 1 shows the forest classification of a Landsat TM
imagery of an Irish test site. The Landsat TM data was
classified into eight forest classes, in three main steps: 1)
Prior to classification, a standard clustering algorithm
(Isodata) was applied to the imagery. Each of the resulting
clusters was then assigned a land cover category, based on
a subjective visual comparison with available ground information. 2) The "raw" spectral samples (signatures) for each
forest class of interest were then "purified", by using the
clusters from step 1 to filter out pixels belonging to nonforest categories or to other forest classes. 3) The purified
signatures from step 2 were then divided into two independent data-sets. The first set of purified signatures was used
to train the four SILVICS classification algorithms, and to
classify the image. The second set of purified signatures was
then used to assess classification accuracy.
A comparison of the classification accuracies for the four
SILVICS image classification algorithms is shown in Table 6.
378
As can be seen the mahaianobis distance and maximum
likelihood algorithms gave the highest classification accuracies. It is important to note that the high classification
accuracies shown in Table 6 are due to the subjective
interpretation of image clusters, which were used to purify
the raw signatures (as described in steps 1 and 2 above).
Thus, the classification accuracies in Table 6 primarily
illustrate the relative performances of the four classification algorithms. An assessment of the true classification
accuracy should be determined by ground surveying.
Summary And Outlook _ _ _ __
Other studies on the application of remote sensing in
forestry have been partly, or in total, financed by the EC
under the EUFourth Framework Programme. These Projects
are more directed towards primary research than the ones
under the FIRS Project, described above. However, results
and methods which can be directly, or at least easily implemented and used for practical purposes will be included in
the so-called 'toolbox' being developed for linking the application of EO data into the EFICS. Figure 2 shows this
toolbox concept: EFICS will link users with National Forest
Inventory data from the Member States, and with metadata
bases, Global Forest Networks etc. Most of the data being
supplied to the potential user in this way will be statistical
and will be enumerated for various statistical units, regions,
forest districts and so on. The projects under FIRS and the
Share Cost Action projects will contribute to the toolbox
assisting the users to retrieve, and to combine information
from EO data with statistical information for their various
needs. Publicly available software like the SILVICS package
SILVICS ClASSIFICAnON OF lANDSAT TM IMAGE
FOR IRISH NA1l0NAl FOREST INVENTORY
157000
158000
159000
160000
161000
208000
208000
207000
207000
206000
206000
205000
205000
204000
204000
157000
158000
159000
160000
Class Names
•
Spruce - mature ( 1)
II
Spruce - ma:ure (2)
Spruce - young
•
161000
Class_Names
Spruce - open
•
Broadleai
Pine
•
Mixed conifer
Mixed pine
I
I broadleaf
spruce
Figure 1.-Map from one of the Irish test sites.
USDA Forest Service Proceedings RMRS-P-12. 1999
Table S.-Relative accuracies of SILVICS classification methods.
Forest class
Spruce-mature (1)
Spruce-mature (2)
Spruce-young
Spruce-open
Pine
Mixed pine/spruce
Broadleaf
Mixed conifer/broad leaf
Overall accuracy (%)
Classification accuracy for four selected algorithms (%)
Neural
Minimum
Mahalanobls Maximum
likelihood network
distance
distance
92.5
88.1
97.3
66.5
87.9
90.5
95.2
86.4
87.6
will constitute an important part ofthe toolbox, but the most
important part will consist a of common nomenclature and
definitions providing comparable information.
The main requirements are presently to develop modules
for assessing the diversity of the forest cover. The EU
commitments towards international conventions, such as
the Helsinki Process (Finnish Ministry of Agriculture and
Forestry, 1993) has shifted the priority away from pure
production related indicators towards environmental indicators. This, together with the increasing needs for mapped
information for global, regional and national modeling and
especially the needs from physical planning, have influenced the priorities of the work program for the next 4 year
period.
The forest diversity module follows the outline in figure 3
(McCormick and Folving, 1998). The compositional elements are being supplied through the FMERS Project and
the structure and change elements are supplied from the
"pilot study in the field of monitoring forested areas". The
basic techniques consist of standard image processing procedures, but the processing methods and the nomenclature
and, eventually, the verification will follow the findings in
the mentioned supporting studies.
As environmental issues are slowly becoming more and
more important for the forestry sector, and as this new trend
95.4
94.7
89.8
84.7
94.7
85.7
93.6
92.5
91.3
93.9
94.7
91.3
83.0
89.1
93.9
94.8
89.3
91.0
97.6
90.5
87.4
76.5
91.5
90.2
95.2
91.8
89.8
Figure 3.-The forest diversity components of the toolbox being
developed under the FIRS project in support to the European Forest
Information and Communication System.
is closely linked to environmental planning and modeling,
the challenge for National Forest Inventories are twofold:
Firstly, the new bio-diversity indicators and indicators on
sustainable development have to be defined. Secondly, spatial data sets need to be prepared as it is not sufficient to
know the magnitude of some forest variable or indicators,
but, more - it is necessary to know exactly where to find the
type, its locations, shape and extension. Forest areas are
becoming important as environmental and socio-economic
buffers. The FIRS project is accordingly being changed to
meet these new challenges. The Project is being merged wi th
activities dealing with watershed management.
The next Framework period will thus be concentrated on
the development of criteria and indicators for assessing and
monitoring forest diversity at the landscape scale, and on
the development of new forest-vegetation typologies and
vegetation abundance descriptions suited for run-off and
erosion modeling, and for general watershed management.
References ---------------------------------
Figure 2.-The "toolbox" concept of the FIRS project. The Project is
aSSisting EFICS in providing the necessary methods for extracting
relevant forest information from EO data
USDA Forest Service Proceedings RMRS-P-12. 1999
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USDA Forest Service Proceedings RMRS-P-12. 1999