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Supporting the Forecast of Snow Avalanches in the Canton of Glarus in Eastern Switzerland: A Case Study

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Man–Machine Interactions 4

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 391))

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Abstract

Snow avalanches pose a serious threat in alpine regions. They may cause significant damage and fatal accidents. Assessing the local avalanche hazard is therefore of vital importance. This assessment is based, amongst others, on daily collected meteorological data as well as expert knowledge concerning avalanche activity. To a data set comprising meteorological and avalanche data collected for the Canton of Glarus in Eastern Switzerland over a period of 40 years, we applied different machine learning strategies aiming at modeling a decision support system in avalanche forecasting.

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Acknowledgments

The authors wish to thank the avalanche service of the Canton of Glarus, Switzerland, and the WSL Institute for Snow and Avalanche Research SLF in Davos, Switzerland, for providing the data on which this work is based.

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Authors and Affiliations

  1. International Center for Computational Logic, TU Dresden, Dresden, Germany

    Sibylle Möhle

  2. Department of Computer Science, University of Hagen, Hagen, Germany

    Sibylle Möhle & Christoph Beierle

Authors
  1. Sibylle Möhle
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  2. Christoph Beierle
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Corresponding author

Correspondence to Sibylle Möhle .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Aleksandra Gruca

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Agnieszka Brachman

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Tadeusz Czachórski

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Möhle, S., Beierle, C. (2016). Supporting the Forecast of Snow Avalanches in the Canton of Glarus in Eastern Switzerland: A Case Study. In: Gruca, A., Brachman, A., Kozielski, S., Czachórski, T. (eds) Man–Machine Interactions 4. Advances in Intelligent Systems and Computing, vol 391. Springer, Cham. https://doi.org/10.1007/978-3-319-23437-3_38

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  • DOI: https://doi.org/10.1007/978-3-319-23437-3_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23436-6

  • Online ISBN: 978-3-319-23437-3

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