Articles | Volume 14, issue 11
Data description paper
18 Nov 2022
Data description paper |  | 18 Nov 2022

In situ observations of the Swiss periglacial environment using GNSS instruments

Alessandro Cicoira, Samuel Weber, Andreas Biri, Ben Buchli, Reynald Delaloye, Reto Da Forno, Isabelle Gärtner-Roer, Stephan Gruber, Tonio Gsell, Andreas Hasler, Roman Lim, Philippe​​​​​​​ Limpach, Raphael Mayoraz, Matthias Meyer, Jeannette Noetzli, Marcia Phillips, Eric Pointner, Hugo Raetzo, Cristian Scapozza​​​​​​​, Tazio Strozzi, Lothar Thiele, Andreas Vieli, Daniel Vonder Mühll, Vanessa Wirz, and Jan Beutel

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Cited articles

Aberer, K., Hauswirth, M., and Salehi, A.: A Middleware for Fast and Flexible Sensor Network Deployment, in: Proceedings of the 32nd International Conference on Very Large Data Bases, VLDB '06, VLDB Endowment, Seoul Korea, 12–15 September 2006, 1199–1202, (last access: 21 October 2022), 2006. 
Arenson, L., Hoelzle, M., and Springman, S.: Borehole deformation measurements and internal structure of some rock glaciers in Switzerland, Permafrost and Periglac., 13, 117–135,, 2002. a
Beutel, J.: Scripts to automatically process GNSS data from using RTKLIB: An Open Source Program Package for GNSS Positioning (1.0), Zenodo [code],, 2022. a, b
Beutel, J., Gruber, S., Hasler, A., Lim, R., Meier, A., Plessl, C., Talzi, I., Thiele, L., Tschudin, C., Woehrle, M., and Yuecel, M.: PermaDAQ: A scientific instrument for precision sensing and data recovery in environmental extremes, in: The 8th ACM/IEEE International Conference on Information Processing in Sensor Networks, San Francisco, CA, USA, 13–16 April 2009, 265–276, (last access: 21 October 2022), 2009. a
Beutel, J., Buchli, B., Ferrari, F., Keller, M., Thiele, L., and Zimmerling, M.: X-Sense: Sensing in Extreme Environments, in: Proceedings of Design, Automation and Test in Europe, Grenoble, France, 14–18 March 2011, 1460–1465,, 2011. a, b
Short summary
This paper documents a monitoring network of 54 positions, located on different periglacial landforms in the Swiss Alps: rock glaciers, landslides, and steep rock walls. The data serve basic research but also decision-making and mitigation of natural hazards. It is the largest dataset of its kind, comprising over 209 000 daily positions and additional weather data.
Final-revised paper