摘要：The new generation of high resolution imaging satellites acquires huge amounts of data which are stored
in large archives. The state-of-the-art Systems for data
access allow only queries by geographical location,
time of acquisition or type of sensor. This information
is often less important than the content of the scene,
i.e. structures, objects or scattering properties. Meanwhile,
many new applications of remote sensing data
are closer to Computer vision and require the knowledge of complicated spatial and structural relationships
among image objects.
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We are creating an intelligent satellite information
mining system, a next generation architecture to help
users to rapidly collect information, a tool to enhance
and to manage the huge amount of historical and
newly acquired satellite data-sets by giving experts
access to relevant information in an understandable
and directly usable form and to provide friendly interfaces for information query and browsing.
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Research topics are within the frame of Bayesian
learning, content-based querying, data modelling and
adaptation to user conjecture.
