ALPMON FINAL REPORT - ARC systems research

Contract ENV4-CT96-0359 ALPMON
100.000 derived from geocoded Landsat TM or SPOT HRV images. The nomenclature for
interpretation consists of three hierarchical levels, of which the third one comprises 44 land-cover
classes (Table 10). The outcome of the project are digital vector layers representing borders of
homogeneous land-cover units.
In 1994 a related land-cover project was started at the Austrian Research Centre Seibersdorf. The
image data used in this project comprise 12 Landsat TM scenes acquired between July and
September 1991. In contrast to the methodology of CORINE it concentrated on the semi-automatic
production of a land-use map of Austria. In order to allow a comparison between this land-use map
and the CORINE data set, the CORINE nomenclature was used in the project.
In general it can be stated that automatic procedures are a valuable alternative to visual interpretation.
Major conclusions to be drawn from the comparison are:
1. The spatial resolution of Landsat TM images limits the recognition of certain classes (in the visual
interpretation approach these classes were recognised by means of ancillary data)
2. per pixel classification and subsequent spatial post-classification of Landsat TM images limits the
precise delineation of certain objects, or even suppresses narrow objects.
3. adequate pre-processing of digital images, such as topographic correction, improves the
classification accuracy in mountainous areas significantly.
This leads to the basic requirement of image data with a higher geometrical resolution in order to solve
for conclusions 1 and 2. At the same time conclusion 3 will still be valid as long as the image data are
digital. Within ALPMON these requirements will be fulfilled, as high spatial resolution image data will be
used for analysis and appropriate pre-processing will be applied. It is therefore expected that for the
ALPMON test areas level III classes will be detectable.
A particular interest of the customer lies in the high alpine regions which are considered the most
crucial areas for visual interpretation. This includes above all the 'Forests and semi-natural areas'
classes of the CORINE nomenclature. A clear distinction of bare rock, sparsely vegetated areas,
natural grassland and different forested areas is of major interest for the customer. In addition
separation of dwarf-pines from other coniferous forests would significantly improve the available
information.
The requirement of the customer is to get land cover maps of the test sites according to level III of the
CORINE nomenclature. If it is possible to increase the thematic subdivision, a level IV nomenclature
will be established. The major motivation of the customer is to estimate the feasibility of an automatic
derivation of CORINE land-cover maps from high resolution satellite imagery for updating the existing
CORINE data base. In order to fulfil this task image data with a high spatial resolution are
indispensable, thus increasing the costs for data acquisition. On the other hand these additional costs
might be compensated by a significant reduction of processing time compared to the visual
interpretation. Therefore the interest of the customer includes an estimation of time and costs of the
ALPMON approach with regard to the derivation of CORINE land-cover maps.
2.1.3 Requirements Fulfilled by ALPMON
Due to the diverse customers and their to some extent very different requirements it would not be
useful to compile a complete list of the parameters to be derived from remote sensing and additional
sources. However, an aggregated list of parameters, which indicates the parameters required for each
feasibility study and test site respectively, is given in Annex 3. This list represents the parameters
which were required by most of the customers and which are also relevant for the Alpine Monitoring
System. The parameters merely distinguish in their further subdivision into subclasses such as number
of age classes or crown closure classes within the forests and their recording accuracy. The
hierarchical nomenclature developed in WP3 (Set up and Harmonisation) can be used as a link
between the different customer requirements and the Alpine Convention. Additionally, a list of classes
(Table 1) was suggested as a minimum standard for all applications within ALPMON. That means,
each partner tried to delineate at least these classes, supplemented by the classes relevant for the
respective application. Some classes have been taken into consideration because they are relevant for
the Alpine Convention (AC), other classes due to their ecological importance.
Table 2 shows the benefits of the national applications to the General Obligations defined in Article 2 of
the Alpine Convention. All subsequent tasks were matched with the requirements investigated within
this work package.
JR, RSDE, ALU, LMU, Seibersdorf, WSL 15