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Since 1994, the European Commission has undertaken various actions
to expand the use of Earth observation (EO) from space in the Union
and to stimulate value-added services based on the use of Earth
observation satellite data.' By supporting research and
technological development activities in this area, DG XII responded
to the need to increase the cost-effectiveness of space derived
environmental information. At the same time, it has contributed to
a better exploitation of this unique technology, which is a key
source of data for environmental monitoring from local to global
scale. MAVIRIC is part of the investment made in the context of the
Environ ment and Climate Programme (1994-1998) to strengthen
applied techniques, based on a better understanding of the link
between the remote sensing signal and the underlying bio-
geo-physical processes. Translation of this scientific know-how
into practical algorithms or methods is a priority in order to con
vert more quickly, effectively and accurately space signals into
geographical information. Now the availability of high spatial
resolution satellite data is rapidly evolving and the fusion of
data from different sensors including radar sensors is progressing
well, the question arises whether existing machine vision
approaches could be advantageously used by the remote sensing
community. Automatic feature/object extraction from remotely sensed
images looks very attractive in terms of processing time,
standardisation and implementation of operational processing
chains, but it remains highly complex when applied to natural
scenes."
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