Minutes
Projects
EAGL – Eionet working group on data model for land monitoring
Activity
3rd working meeting
Participants
Gergely Maucha, Geir-Harald Strand, Gerard Hazeu, Guillermo Villa, Philippe Dorelon,
Tomas Soukup, Geoff Smith, Stefan Kleeschulte, Michael Bock, Stephan Arnold,
Gebhard Banko, George Buttner, Vasco Nunes, Andreas Littkopf, Antonio Nunes,
Ales Versic, Núria Blanes
Date
10-12/03/2010
Prepared by:
Núria Blanes, Geoff Smith, Andreas Littkopf, Gebhard Banko
Comments:
Geir-Harald Strand, Gerard Hazeu, Philippe Dorelon, George Buttner, Stefan
Kleeschulte, Tomas Soukup, Vasco Nunes, Guillermo Villa, Geoff Smith
1. INTRODUCTION AND OBJECTIVES OF THE MEETING
This meeting intends to continue the work already started in 2009 by the Eionet working
group on data models for land monitoring. This meeting is the first one that is considered
as a NRC meeting and therefore, financial and administrative support have been provided
by EEA.
The main objectives of the meeting were:
(1) to establish the basic classes to be mapped and the attributes defining each of those
classes based on experiences presented by the group and previous know how, in order to
pave the way on how land monitoring in Europe can evolve from the existing CORINE to
a technically more advanced method to produce harmonised land cover and land use
information at European level from existing sources (e.g. national inventories), and
(2) to discuss on GIO.
The workshop has been divided into a general session of presentations concerning the
work done by several members of the group, splinter sessions to discuss
parameterization and attributes to the different elements and finally, a session to develop
recommendations for GIO and based on EEA’s request for the next CLC in 2012. The last
day was dedicated to summarize the outcomes of the splinter sessions, to draw some
conclusions on how to proceed and decide which will be the work to be done by each
partner in the coming months.
2. GENERAL
PRESENTATIONS OF THE WORK COMMITTED TO BE DEVELOPED IN THE LAST THREE
MONTHS
In this session, there were 3 presentations. FAO representative was not able to
participate, so the session directly started with (1) the translation process of the CLC 3rd
level class into FAO nomenclature, (2) the translation of existing CLC into object oriented
data models, based on SIOSE developments, and (3) gaps already identified in the
exercise of CLC 2006 and improvements proposed for the future.
Technical details on the findings presented in the afternoon session can be found as an
Annex to these minutes (information provided by the speakers).
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Due to time constraints, valuable work developed by other members of the group has not
been presented during this meeting, but the information would be provided in the next
EAGL meeting or via a common publication.
2.1 Translation process of the CLC 3rd level class into FAO nomenclature (Vasco
Nunes)
The objective of the work done is the translation of CLC nomenclature into FAO Meta
language in order to test how Corine can be described using FAO tools and nomenclature.
Several items should be taken into account for this translation, and not all of them can
be solved with FAO model (different degrees of translation depending on the CLC class
and it varies from successful translation to a questionable and very questionable one).
Mixed / heterogeneous classes (e.g. 242, 243, 244, 324, etc) were especially difficult to
translate..
It has been discussed the aim of this exercise and the fields in which this work can be
used. It has been agreed that it can explain in a more detailed way the content of the
CLC classes and to really check the comparability among the different national teams.
Based on these types of studies, the variations and differences across Europe regarding
the definition of the land cover classes need to be obtained. What is really important for
the parameterization exercise is that it aims to obtain a “single definition” at European
level.
2.2 Translation of existing CLC into object oriented data models, based on
SIOSE developments (Guillermo Villa)
When doing the exercise, it has been seen that some CLC subclasses already in place
should disappear and the information should be integrated into the corresponding class
as an attribute (e.g. abandonment, under construction, types of forest,…), and
information that should be provided as a percentage instead of a new class detailing the
degree of coverage, for example.
At national level, each user can decide which elements are parts of a land cover or not,
but at European level it should be agreed in order to ensure harmonisation and
comparability.
Several questions arose from the presentation and were discussed, such as a) how two
polygons then can be split if you only have different attributes but the same general
label, or b) the relation of this exercise with the MMU (if you strictly apply MMU, then it
seems that there is no difference between attributes or classes), or c) if Corine polygons
could be described only using statistical data that will be available at European level by
grid cells of 100*100m.
Depending on the purpose of the analysis, there are (at least) 2 options at the CLC
polygon level (explained by Norway):
-
Attribution of CLC dasets using more detailed information at national level in order
to describe (statistically) the content of each CLC polygon in terms of a predefined
set of land cover types (measured as percentage coverage).
-
Substituting the CLC polygon structure with a raster or grid structure: Information
on percentage coverage of various land cover types and other content (eg number
of buildings or length of roads) can be added to the raster/grid cells through
overlay with detailed national databases. Changes within the raster/grid cells can
also be clavculated. The location of features inside raster/grid cells would not be
known.
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2.3 Gaps already identified in the exercise of CLC 2006 and improvements
proposed for the future (George Buttner)
The current status of the CLC 2006 project was presented: 36 out of 39 countries has
finalised their CLC exercise, with a total of 33 months to complete the project. The
majority of the countries used photo interpretation except Nordic countries that used
digital image processing, modeling and other existing databases in their countries to
derive CLC, paving the way for the future of this activity.
It has been also stated that it is possible to derive CLC and CLC changes by combining
existing national datasets and remote sensing / GIS techniques, although for validation
and verification it would be needed visual interpretation as well.
The group discussed that 33 months of time frame for developing such a project is
unacceptable, as it is possible to do it in 5 to 8 months if there is a good pre-organisation
from EEA side and the countries have the possibility to plan in advance the efforts to be
dedicated to it. The experience from CLC2006 is that most of the 30+/- months was used
to decide to join the programme, write proposals, have them approved and find the
sources for the national co-funding. The actual project work was in many (most?)
countries carried out in less than 12 months. If the time frame for developing such a
project is reduced, the verification process done by the technical team to harmonize the
work of national teams has to be redesigned.
Several proposals to work in a more efficient manner were:
-
Concentrate the efforts (and the available budget) on those areas that have a
higher probability of changing.
-
Create a potential change layer with high resolution imagery: it will not be 100%
automatic but it will reduce the efforts by focusing the work on potential areas
where changes are occurring (in Norway, 50% of the efforts where saved by using
this approach, as compared to the EEA original estimate for Norway), although
also looking to the rest of the territory.
-
NRCs need to encourage national institutions responsible for maintaining datasets
of possible use in CLC-change detection to add reference year into their
information and databases to make them useful in CLC context.
3. SPLINTER SESSIONS FOR PARAMETRIZATION / ATTRIBUTING EXERCISE
The group divided into 2 discussion groups, in order to achieve a tentative definition of
the classes to be mapped and describe them through an attributing exercise.
Splinter group 1
This splinter session was initially tasked with reviewing the definition of artificial areas
and how they may be described in terms of physical characteristics (possibly assessed
automatically from EO data) and use / function characteristics (from external sources).
The first step was to define what was meant by ‘artificial’ and the distinction with ‘urban’
which may contain a range of land cover types including water and vegetation. One of
the key characteristics of artificial areas is the degree of sealing caused by buildings and
other surfaces materials (e.g. asphalt and concrete). The GMES Fast Track Service on
Soil Sealing has already delivered a pan-European sealing data set for 2006 and an
update is underway for 2009. It was suggested that once the sealing degree is known it
is important to divide this between buildings and other surfaces and then, extend this
information to include the height of the buildings. The final physical element selected for
describing artificial areas was the pattern or textures of the buildings and surface
features within the area of interest. The land use / functional characteristics of artificial
areas are extremely complex as they are the focus for many different human activities,
including multi-functional features such as buildings which may contain commercial
premises on the ground floor and residential above or areas of asphalt which could be
used as car parks or for recreational activities at different times. A categorisation of land
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uses for artificial areas was attempted along conventional lines using national
experiences.
This splinter session was then asked to include a comprehensive set of features to make
up a land surface nomenclature at the European level. The first step was to develop a
simple land cover classification which would give useful distinctions, but which could also
be realistically delivered by automated or semi-automated analysis of EO data, as
follows:
1.
Artificial (sealed surfaces and buildings)
2.
Water (liquid and frozen)
3.
Bare non-soil (exposed rock and sediment)
4.
Soil (sediment with a high proportion of organic matter)
5.
Herbaceous (vegetated area without wood species, grassland, crops)
6.
Shrubs (short or sparse woody vegetation, heaths and moors)
7.
Trees (dense mature woodland)
An approach, similar to that described above for artificial surfaces, was applied to
associate physical and land use characteristics to each of the land cover classes to allow
further division into more useful levels. An indicator of vegetation amount would be
useful in a similar way to the soil sealing data set. The land use categorisation was
extended to cover additional functions such as agriculture, forestry etc. An example of
how this approach would operate: a herbaceous area which is permanently vegetated
and associated with agricultural land use was labelled as pasture.
A key issue was the delineation of the objects which are to be labelled by the
nomenclature. No MMU had been specified and could therefore range from the 25 ha of
CLC to the 0.25 ha of the Urban Atlas in current pan-European products. As the first is
too coarse for many applications and the second is unmanageable for EU levels, a
compromise would be required. It was suggested that objects should be homogeneous
based on the MMU, but homogenous in terms of which characteristics? Ideas were
proposed for a two level object concept for the land cover and land use components,
maybe with different MMUs, or unrelated features such as a grid or administrative
districts could be used.
Splinter group 2
In the session on agriculture classes the Portuguese approach was further discussed in
order to describe CLC classes with the LCCS Meta language, what was working quite well.
After the discussion on how to structure the main classes, a proposal of a use oriented
description was compared with a strict land cover description. The group decided to
strictly divide land cover and land use components of classes (currently mixed in CLC
definition) and follow the land cover description considering additional attribute(s) on
land use. This would allow more flexibility of linking/comparing CLC classes with other
nomenclatures.
Additionally, it was discussed how to describe (and record) composition inside of an
individual CLC polygons and it was decided that the base land cover elements should be
part of the description as statistical information (percentages). First, it would improve
current information deficiencies caused by 25ha MMU as well as it would allow better
understanding of CLC class content in different MSs/regions.
Further description of the polygon with additional attributes was only considered on the
level of the whole polygon, nevertheless pros and cons were discussed but not closed.
A presentation of the approach followed in Decover was given as an example to take into
consideration for further developments. Going back to the results, it was decided to
discuss the base land cover classes composition and additional attributes needed for all
CLC agriculture classes description. Based on that exercise, the final proposal for base
land cover classes and additional attributes would look like as the lists below. Potential
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data sources to gather these information has been discussed too and satellite image
processing has been identified as one of the effective sources (but not necessary
exclusive) to fill base land cover classes/elements information.
1) Considering base land cover classes:
Vegetated
• Herbaceous
• Woody
o Trees
o shrubs
• Lichen and mooses
None vegetated
• Artificial
o Build up
o Non built up
• Natural
o Rock
o Soil
ƒ Sand
ƒ Mud
ƒ Salt
ƒ
• Water
o Snow and ice
o Water body
2) And considering the attributes, another list was developed:
• Vegetation coverage
• Heterogeneity
• Height
• Management
• Use
• Water content
• Irrigation
• Permanent, non permanent, rotation
• Species
• Vine
• Olive
• Fruit and berries
• Rice
• Others
4. GUIDED DISCUSSION TO DEVELOP RECOMMENDATIONS FOR GIO
A separate document is provided summarizing the session regarding GIO, in order to
communicate the outcomes of the session to the EEA.
The main conclusions of the session are the following ones:
•
General willingness to support another “CLC” update if certain conditions are met.
•
Need for a detailed planning and timing of the exercise before the project start.
•
Timely information to the countries about what is expected from them.
•
A fully funded exercise would be needed to ensure the implementation of the
project in the envisaged time table.
•
Question about the EO data reference date of the update (2009, 2010, 2011).
•
Flexibility of EEA with respect to the final deadline (mid d2012)
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•
Proposal to develop a change indicator map to support land cover change
mapping.
5. CONCLUSIONS AND NEXT STEPS
The splinter sessions as well as the session concerning GIO were resumed to achieve a
common understanding and define the steps forward.
The following points were agreed:
-
CLC exist and it cannot be changed completely (and it is not the purpose for the
time being; results of the work developed should be seen to take such a decision
and currently, the whole process is just in the transition phase), so building upon
what is existing will be to obtain more information about what can be found inside
the Corine polygons: attribution and parameterization
-
Working in this direction will allow an assessment of the variability over CLC
classes among the different countries and check also how CLC is implemented in
the different countries (based on the class content). Backwards comparability will
be also ensured.
-
In the future, it could be developed a more complex model which interlinks land
use and land cover, and also discuss about improving geometry; but this issue will
imply a fundamental change and consequences for backwards comparability, so it
should be discussed in detail in the upcoming meetings.
-
A proposal for geoland2 developments was raised (but not uniformly agreed): to
create a land cover map for Europe with the 7 or 10 exhaustive and mutually
exclusive land cover classes that the group is going to agree on and improve
existing information on soil sealing.
Next steps:
There will be three main activities to be developed in the coming months:
-
-
Populating CLC polygons with fundamental classes. Who has committed to do it?
o
Norway: will do it based on the 2 lists of land cover types being discussed
in the splinter sessions (but adjusting for data availability in Norway) and
producing a Norwegian list of maximum 10 basic land cover categories
o
Austria: will do it for some test sites
o
Hungary: Tokaj region
o
United Kingdom
o
Czech Republic: will do it and will also add possible attributes that could be
derived from satellite images
o
Luxembourg (most probably)
Attribution of the fundamental classes (expected contribution from all the group):
o
The objective of this activity is to develop a whole list of attributes that will
define each of the pure land cover classes decided.
o
A separate document to work on, containing basically the discussed points
in the splinter session, will be distributed to the whole group.
o
By the end of April – mid May 2010, compilation and summary of the
feedback received from all the group:
ƒ
-
Pending discussion once results obtained concerning
applicability to existing Corine and its traceability.
Model the outcomes of both exercises:
o
Portugal is going to work on this item.
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Not explicitly mentioned during the meeting but a crucial item to take into account for
the upcoming activities is to determine, considering the outcomes of the exercises
described above, which is the final purpose of the analysis undertaken and provide
specific reasons concerning why it has done in this way.
It will be also important to decide the subsequent applications of these outcomes (i.e.
comparison of national analysis to define at the end an EU standard of fundamental
classes or comparison of the results obtained in the different countries to check the
homogeneity of CLC between them, among others).
AOB
Next meeting: is going to be scheduled around 20th of September 2010. Ljubljana could
be a candidate place.
Proposal for making a publication with all the results already obtained by the group.
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ANNEX – Technical details of the presentations
Translation process of the CLC 3rd level classes into FAO nomenclature.
Vasco Nunes
The objective of the work done was the translation of the CLC nomenclature into FAO’s
Land Cover Meta language (LCML) in order to test how CLC classes can be described
using FAO’s tools.
This translation was made using FAO’s Land Cover Classification System (LCCS) software
(version 3 – still being tested) and the approach was to input main class descriptors
enough to discriminate between CLC classes, as opposed to inputting all descriptors
included in CLC class definitions.
Several items should be taken into account for this translation, namely the land cover
elements, their characteristics (attributes and properties) and their layering disposition.
Difficulty and ambiguity of translation depend on the CLC class you are working with and
it ranges from a direct translation to a very questionable one.
Some conclusions were:
-
the Land Cover Meta Language is able to describe in a very strighforward way most
of the CLC classes;
-
there is more than one correct form to describe a CLC class using LCCS;
-
its not clear when to stop in detailing class descriptions;
-
most CLC classes could use smaller descriptions;
-
complex classes like (242, 313, 324, etc) are more difficult to translate;
-
some improvements in the LCCS software may resolve several encountered
difficulties;
It has been discussed the aim of this exercise and the fields this work can be used, and it
has been agreed that it can explain in a more detailed way the content of the CLC classes
and to really check the comparability among the different national teams. Based on this
type of studies, the variations and differences across Europe regarding the definition of
the land cover classes, which is really important for the parameterization exercise that
would aim to obtain a “single definition” at European level.
Translation of existing CLC into object oriented data models
Guillermo Villa
Although the best way to represent a data model is a UML diagram, experience in group
discussions in Spain has shown 2 limitations:
- Difficulty to have an overall view of the model when displayed on the screen
- Many domain experts participating in the discussions are not familiar with UML symbols
For this reasons, a “simplified view” of the data model in an Excel sheet was sent to the
group previous to the meeting, and is presented here. In this Excel sheet we can see:
1) The proposed “land cover classes”, arranged in a hierarchical way (a “taxonomy”). The
proposal is to use CLC standard 3 level nomenclature as starting point.
2) The proposed “land cover elements”, real world elements that make up “land cover
classes”, arranged in a hierarchical way. The proposal is to start with terms that appear
in the definitions of CLC classes (buildings, vegetations, etc…)
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3) The proposed “attributes”, important characteristics of land cover classes and land
cover elements. The proposal is to start with terms that appear in the definitions of CLC
classes (height, irrigated, etc…)
4) Which “land cover classes” are part of each “land cover class”
When doing the exercise, it has been seen that some CLC subclasses already in place
should disappear and the information should be integrated into the upper class as an
attribute (e.g. abandonment, under construction, types of forest,…), and information that
should be provided as a percentage instead of a new class detailing the degree of
coverage, for example.
If the group feels the need to add more details, a very long list of “Land cover classes”,
“land cover elements” and attributes for both can be found if the document “CORINE land
cover nomenclature illustrated guide”. Nevertheless, group should take into account that
Inspire is looking for simple data models that can be agreed on by all countries.
At national level, each country can decide to add more classes or attributes in the
“national profile”, but at European level it should be reached an agreement in order to
ensure harmonisation and comparability.
Several questions aroused from the presentation and were discussed, such as a) how two
polygons then can be split if you only have different attributes but the same general
label, or b) the relation of this exercise with the MMU (if you strictly apply MMU, then it
seems that there is no difference between attributes or classes), or c) if Corine polygons
could be described only using statistical data that will be available at European level by
grid cells of 100*100m.
Depending on the purpose of the analysis, there are 2 options (explained by Norway):
-
Overlapping CLC with more detailed information at national level in order to know
what is really inside a CLC polygon (percentage and location).
-
Overlapping the more detailed information with raster or grid structure:
information on percentages and on changes in the percentages will be available,
but the location would not be known (it will be only possible to present a unique
type of information each time you query the database).
Gaps already identified in the exercise of CLC 2006 and improvements
proposed for the future
George Buttner
CLC2006 has officially finished in mid-February 2010 in 36 countries (out of total 39
planned). CH and UK are still working, and plan to finish this year. GR is not
participating. The total duration of technical implementation was 33 months, which is
hardly acceptable for the EEA.
Main problems during implementation were:
1. Long administrative preparation, including financial commitment is some countries
(e.g. DE, IT..).
2. Elongated implementation time in some countries due to difficulties in providing
national contribution (e.g. AT, HU, UK…).
3. Long GIS integration phase (several months) in some countries (e.g. ES, NO..)
There are positive examples of fast (5-8 months) implementation in some larger
countries: FR, PL, TR...
Most countries applied CAPI technology as suggested in the Technical Guidelines.
Especially Scandinavian countries applied different combinations of digital image
processing of satellite images, GIS integration of existing national data sets and
photointerpretation.
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Being already the 3rd CLC exercise, there were no critical problems with the applications
of the nomenclature. Some typical, frequently occurring difficulties: Non-consequent
separation of pastures (231) and natural grasslands (321); non-consequent separation of
arable land (211), pastures (231) and complex cultivation (242); irrigated land (212)
was an used inconsistently (not only arable land is irrigated..).
The 100 m positional accuracy was kept rather well (lower accuracy in some countries /
regions).
Verification of national CLC-Changes datasets was as important issue:
•
to achieve harmonised application of mapping rules and nomenclature,
•
to provide comparable datasets by the countries,
•
and to assure thematic quality of database.
No conceptual problems in change mapping were observed. The „overall 5 ha rule” was
applied properly and did not overload the national teams. Technical change was used
according to purpose to compensate the effect of two different MMUs. In some countries
technical change was used also to take care of mistakes in CLC2000. Some typical
problems:
•
Not always the „real change” was mapped.
•
Considering the frequent change types mapping forest growth was the most
difficult and subjective.
The magnitude of total changes (yearly percent total change) is below 1 % except PT.
Considering the experiences of Scandinavian countries the future of European land
monitoring can include:
•
Combination of existing national datasets and RS/GIS; generalisation for the
purposes of EEA
•
RS-based visual quality control
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