ALPMON FINAL REPORT - ARC systems research

Contract ENV4-CT96-0359 ALPMON
3.3.1 Set-up and harmonisation of parameters
The set-up of the parameters was carried out using a comprehensive list of single parameters and the
respective classes. As the requirements of the national customers were used as input for the
parameter set-up, the used level of detail ensures, that all requirements of the local customers could
be met. The use of single parameters instead of predefined landuse-classes enables the flexible
assignment of parameter classes to user-oriented classes.
The requirements of the Alpine Monitoring System (AMS) of the Alpine Convention were included only
partially in the parameter set-up, because only a first draft of AMS-indicators was available at that time.
Therefore, ALPMON oriented the parameter set-up according to FIRS (EUR 16416). In some cases,
AMS-indicators are fully addressed by ALPMON parameters. Some of the AMS-indicators deal with
topics, which cannot be assessed with remote sensing alone. The AMS-indicators do not include the
ALPMON-parameters 'crown coverage', 'vegetation coverage' and 'natural age class'. These
parameters are of great importance to the protection function of the forest as well as for the planning of
regeneration measures. The AMS-indicators do not address non-forest areas, which are included in
ALPMON.
As the collection of ground truth information in WP 4 proved, the parameter list can be used
successfully. If the AMS-indicators were ready before the start of ALPMON, they would have been
considered completely.
3.3.2 Collecting of ground information and verification of classification results
Work packages WP4 Ground Truthing and WP10 Verification are summarised collectively, as they are
interrelated closely. The verification of classified satellite data is very much dependent on the
reference, with which the verification is done. The classification accuracy, which results from the
verification, is dependent on how the reference is sampled, its spatial distribution and its
representativity of the categories of interest. Since WSL co-ordinated these two packages, they are
evaluated together.
Ground truth information (WP4) was collected by all partners on the basis of infrared aerial
photographs, which were additionally verified with field surveys. This approach was recommended for
supporting the delineation of suitable training areas for the digital classification and for verification. The
parameters set up in WP 3 were applied successfully. It must be stated that the applied sampling
strategies for ground truth information differed from partner to partner, which directly influences the
outcome of the verification. Subjectivity is induced by the choice of reference data sampling size and
strategy (Smits et al., 1999).
The verification (WP10) of classified satellite data varied somewhat from partner to partner. During the
Partner Meetings in Freiburg (December 1998) and Munich (June 1999), it was decided to carry out
pixel- and stand-wise verification. In general, better statistical accuracy measures were produced for
the stand-wise verification method. Exceptions arose due to the selectively small number of stands
available.
3.3.3 Geocoding
The integration of different sensors and the connection of the remote sensing data to ancillary
information of ALPMON put high demands on the geometric accuracy of these data. Thus, the
geometry of the satellite images had to meet extremely strict requirements, firstly, because the data
obtained with different systems were classified multi-sensorally and multi-temporally, and secondly,
because the satellite images and the classifications subsequently derived from them had to be
integrated with additional digital data in a geographical information system.
To optimise the absolute geometric location accuracy of the geocoded image data, displacement
errors caused by topographic relief have to be removed. Obviously, the amount of these errors varies
from sensor to sensor, depending on the actual terrain elevation and on the sensor-specific imaging
model. In the course of geocoding, these errors can be removed through the integration of a digital
elevation model (DEM), i.e., the consideration of terrain relief information. This type of image data georeferencing
is called terrain correction geocoding, which is the general equivalent to ortho-photo
generation in classical photogrammetry.
All the geocoding activities – except for Cordevole test site and partly Engadine test site – were carried
out using the Remote Sensing Software Package Graz (RSG) of JR, implemented in ERDAS TM
Imagine. This software was made available to the project partners. For the Cordevole test site Cartha
JR, RSDE, ALU, LMU, Seibersdorf, WSL 75