Environmental Measurement and Spatio-Temporal Modelling

Quality and amount of environmental sensors, power of computers, and
quality of environmental data analysis and modelling approaches have all
drastically improved over the last decades. Still, deciding rationally
how to react to environmental problems has not become easier. Initially
environmental questions mainly focused on single compartments such as
outdoor air, soil, or surface water. Today, comparison of policy measures
integrates through compartments, and takes place from perspectives like
health, economics, or biodiversity. How can we, as a society, choose
between enforcing particle filters on cars to decrease human exposure to
fine particles, and putting restrictions on building materials to decrease
indoor exposure to radon? How and when should we, as individuals,
choose between bike or car, or between burning gas or wood?

A common aspect in these questions is the analysis and modelling of sensor
data, and the spatial and temporal component. Do we want a general yes/no
for e.g. the whole of Europe, or specified by country, or by larger city?
Should this be on a day-to-day basis, yearly, or averaged over the
next ten years? Given the same amount of information, the less specific
questions are usually easier to answer, and the more spatio-temporal
explicit ones are subject to larger uncertainties. Rational decision
making benefits from quantified uncertainties, and varying the spatial or
spatio-temporal scale may help finding answers that make sense. In case
we do not have enough information, which additional information should
we collect to enable informed decision making?

The topics considered by this working group are
- analysis of spatial and spatio-temporal data
- error propagation, monte carlo sampling
- real-time statistical analysis and modelling for disaster preparedness
- spatio-temporal monitoring network design and optimization
- environmental health assessment and decision support
- open source software development
- deployment and development of open standards

Further, the working group is involved in the R project for statistical analysis,
and is committed to open source software and open publishing of teaching material.