GAMMA REMOTE SENSING: alpine avalanche forecast

All projects, Completed projects

Description

Satellite technology has the potential to close existing information gaps by acquiring data automatically even over inaccessible terrain. In this study, we investigated how existing satellite technology can be combined with ancillary information and joined into a tailored service to support avalanche warning services across Europe as well as other key users that rely on avalanche information.

Snow avalanches kill people and damage infrastructure in mountainous regions throughout Europe and the world. Operational avalanche warning services presently base their products mainly on numerical weather prediction output and networks of automated weather stations and observers in the field. However in many parts of Europe, the networks are not dense enough and observations by people in the field are hindered by bad weather conditions or high avalanche danger, especially during critical time periods.

We brought key users from different user groups together at a workshop in Davos to discuss urgent user needs as well as relevant technologies and their limitations. This user-driven approach ensures that a potential service will not ignore critical constraints given by operational avalanche warnings. The project consortium consisted of four partners: the WSL Institute for Snow and Avalanche Research SLF (CH), the Norwegian Geotechnical Institute NGI (NO), GAMMA Remote Sensing AG (CH) and ENVEO IT GmbH (AT). The investigated technology for detecting avalanche activity has a big potential to improve operational avalanche warning services.

Picture: © M. Bründl, SLF

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Project Features

  • Collecting the users’ needs and identifying the most relevant information gaps of today’s avalanche warning
  • Listing the available technologies to measure snow-related parameters and including their strength and weaknesses
  • Identifying the most promising integrated solution and outlining potential services
  • Evaluating the technical and economic feasibility of the identified service
  • Collecting recommendations for follow-up studies and developing a roadmap