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  Information - NH11.04 Prediction and real-time mapping for natural hazards and environmental monitoring

Event Information
Spatial analysis of environmental data linked to natural hazards is
getting popular to monitor our environment and delineate risk areas.
These areas can be affected by natural processes including volcanic
activity, extreme meteorological events, earthquake, and landslides, to
name a few only. Advances in spatial modelling and statistics allow not
only to identify and delineate such risk areas but also to assess the
uncertainties associated to these risk maps.

Because there is nothing such as a universal mapping algorithm, this
session will address two key issues in the field which are the
combination of mathematical theories and expert's knowledge and the
development of real-time mapping algorithms that are, by definition,
independent from the expert's input.

In particular, this session will deal with spatial prediction models for
both mathematical idea-base and expert's knowledge-base not limited to a
specific natural process. In addition, socio-economic impacts of the
prediction models are also included the session. On the other hand,
since many environmental monitoring systems are expected to generate
maps of the monitored variable in real-time, this session will also
explore spatio-temporal models running without expert-knowledge and
nevertheless able to cope with unforeseen events ("hot spots" or extreme

This session will address these fundamental issues by inviting authors
to present modern spatio-temporal methods, concepts, case-studies and
applications. In order to allow a fruitful discussion and exchange
between the different disciplines we encourage a particular focus on the
demonstration of the employed methodology for respective research or

Preliminary List of Solicited Speakers


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