Articles | Volume 6, issue 4
https://doi.org/10.5194/esurf-6-1219-2018
https://doi.org/10.5194/esurf-6-1219-2018
Short communication
 | 
11 Dec 2018
Short communication |  | 11 Dec 2018

Short Communication: Monitoring rockfalls with the Raspberry Shake

Andrea Manconi, Velio Coviello, Maud Galletti, and Reto Seifert

Related authors

Exploring the use of Sentinel-1 to monitor spatial and temporal evolution of permafrost in the Swiss Alps
Kristina Juliana Reinders, Govert Frederik Verhoeven, Luca Sartorelli, Ramon Hanssen, and Andrea Manconi
EGUsphere, https://doi.org/10.5194/egusphere-2023-2321,https://doi.org/10.5194/egusphere-2023-2321, 2023
Short summary
Landslides caught on seismic networks and satellite radars
Andrea Manconi, Alessandro C. Mondini, and the AlpArray working group
Nat. Hazards Earth Syst. Sci., 22, 1655–1664, https://doi.org/10.5194/nhess-22-1655-2022,https://doi.org/10.5194/nhess-22-1655-2022, 2022
Short summary
Brief Communication: On the rapid and efficient monitoring results dissemination in landslide emergency scenarios: the Mont de La Saxe case study
D. Giordan, A. Manconi, P. Allasia, and D. Bertolo
Nat. Hazards Earth Syst. Sci., 15, 2009–2017, https://doi.org/10.5194/nhess-15-2009-2015,https://doi.org/10.5194/nhess-15-2009-2015, 2015
Short summary
Landslide early warning based on failure forecast models: the example of the Mt. de La Saxe rockslide, northern Italy
A. Manconi and D. Giordan
Nat. Hazards Earth Syst. Sci., 15, 1639–1644, https://doi.org/10.5194/nhess-15-1639-2015,https://doi.org/10.5194/nhess-15-1639-2015, 2015
Brief Communication: The use of an unmanned aerial vehicle in a rockfall emergency scenario
D. Giordan, A. Manconi, A. Facello, M. Baldo, F. dell'Anese, P. Allasia, and F. Dutto
Nat. Hazards Earth Syst. Sci., 15, 163–169, https://doi.org/10.5194/nhess-15-163-2015,https://doi.org/10.5194/nhess-15-163-2015, 2015
Short summary

Related subject area

Physical: Geophysics
3D shear wave velocity imaging of the subsurface structure of granite rocks in the arid climate of Pan de Azúcar, Chile, revealed by Bayesian inversion of HVSR curves
Rahmantara Trichandi, Klaus Bauer, Trond Ryberg, Benjamin Heit, Jaime Araya Vargas, Friedhelm von Blanckenburg, and Charlotte M. Krawczyk
Earth Surf. Dynam., 12, 747–763, https://doi.org/10.5194/esurf-12-747-2024,https://doi.org/10.5194/esurf-12-747-2024, 2024
Short summary
Machine learning prediction of the mass and the velocity of controlled single-block rockfalls from the seismic waves they generate
Clément Hibert, François Noël, David Toe, Miloud Talib, Mathilde Desrues, Emmanuel Wyser, Ombeline Brenguier, Franck Bourrier, Renaud Toussaint, Jean-Philippe Malet, and Michel Jaboyedoff
Earth Surf. Dynam., 12, 641–656, https://doi.org/10.5194/esurf-12-641-2024,https://doi.org/10.5194/esurf-12-641-2024, 2024
Short summary
Subaerial and subglacial seismic characteristics of the largest measured jökulhlaup from the eastern Skaftá cauldron, Iceland
Eva P. S. Eibl, Kristin S. Vogfjörd, Benedikt G. Ófeigsson, Matthew J. Roberts, Christopher J. Bean, Morgan T. Jones, Bergur H. Bergsson, Sebastian Heimann, and Thoralf Dietrich
Earth Surf. Dynam., 11, 933–959, https://doi.org/10.5194/esurf-11-933-2023,https://doi.org/10.5194/esurf-11-933-2023, 2023
Short summary
Short communication: Potential of Sentinel-1 interferometric synthetic aperture radar (InSAR) and offset tracking in monitoring post-cyclonic landslide activities on Réunion
Marcello de Michele, Daniel Raucoules, Claire Rault, Bertrand Aunay, and Michael Foumelis
Earth Surf. Dynam., 11, 451–460, https://doi.org/10.5194/esurf-11-451-2023,https://doi.org/10.5194/esurf-11-451-2023, 2023
Short summary
Automated classification of seismic signals recorded on the Åknes rock slope, Western Norway, using a convolutional neural network
Nadège Langet and Fred Marcus John Silverberg
Earth Surf. Dynam., 11, 89–115, https://doi.org/10.5194/esurf-11-89-2023,https://doi.org/10.5194/esurf-11-89-2023, 2023
Short summary

Cited articles

Amann, F., Kos, A., Phillips, M. Kenner, R.: The Piz Cengalo Bergsturz and subsequent debris flows, Geophys. Res. Abstr., 20, EGU2018-14700, EGU General Assembly 2018, Vienna, Austria, 2018. 
Anthony, R. E., Ringler, A. T., Wilson, D. C., and Wolin, E.: Do Low-Cost Seismographs Perform Well Enough for Your Network? An Overview of Laboratory Tests and Field Observations of the OSOP Raspberry Shake 4D, Seismol. Res. Lett., https://doi.org/10.1785/0220180251, online first, 2018. 
Arosio, D., Longoni, L., Papini, M., Scaioni, M., Zanzi, L., and Alba, M.: Towards rockfall forecasting through observing deformations and listening to microseismic emissions, Nat. Hazards Earth Syst. Sci., 9, 1119–1131, https://doi.org/10.5194/nhess-9-1119-2009, 2009. 
Burtin, A., Hovius, N., McArdell, B. W., Turowski, J. M., and Vergne, J.: Seismic constraints on dynamic links between geomorphic processes and routing of sediment in a steep mountain catchment, Earth Surf. Dynam., 2, 21–33, https://doi.org/10.5194/esurf-2-21-2014, 2014. 
Cochran, E. S.: To catch a quake, Nat. Commun., 9, 2508, https://doi.org/10.1038/s41467-018-04790-9, 2018. 
Download
Short summary
We evaluated the performance of the low-cost seismic Raspberry Shake (RS) sensors to identify and monitor rockfall activity in alpine environments. The sensors have been tested for a 1-year period in a high alpine environment, recording numerous rock failure events as well as local and distant earthquakes. This study demonstrates that the RS instruments provide a good option to build low seismic monitoring networks to monitor different kinds of geophysical phenomena.