EO4Alps – The Alps from Space Workshop

Hi all,

I am currently attending the EO4Alps conference in Innsbruck, Austria. The objectives of this interesting workshop are:

  • Assessing the status and priority interests in the European Alpine Region for Earth Science, geo-information and operational monitoring;
  • Reviewing the main activities, projects and initiatives taking place in the different Alpine application areas, where Earth observation from space can contribute;
  • Evaluating the potential of the increasing observation capacity by satellites to address needs for science, applications and information services in the European Alpine region;
  • Characterising and addressing data collection and analysis gaps and define high-level requirements for supporting ICT solutions to advance EO data infrastructure capabilities in the Alpine region.

The diverse programme features seven different sessions, covering various topics such as atmospheric processes, natural hazards, environmental and climate change, natural resources, economic development and ecological networks, combination of ground-based and satellite systems as well as infrastructure and data analysis.

Further information on EO4Alps can be found at www.eo4alps.info.

Best regards,

(Featured images contain modified Copernicus Sentinel data, processed by ESA)

About This Author

Matthias studied Environmental Information Management at the University of Natural Resources and Life Sciences Vienna and holds a PhD in environmental statistics. The focus of his thesis was on the statistical modelling of rare (extreme) events as a basis for vulnerability assessment of critical infrastructure. He is working at the Austrian national weather and geophysical service (ZAMG) and at the Institute of Mountain Risk Engineering at BOKU University. He currently focuses the (statistical) assessment of adverse weather events and natural hazards, and disaster risk reduction. His main interests are statistical modelling of environmental phenomena as well as open source tools for data science, geoinformation and remote sensing.

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