Articles | Volume 22, issue 1
Nat. Hazards Earth Syst. Sci., 22, 207–212, 2022
https://doi.org/10.5194/nhess-22-207-2022
Nat. Hazards Earth Syst. Sci., 22, 207–212, 2022
https://doi.org/10.5194/nhess-22-207-2022
Brief communication
28 Jan 2022
Brief communication | 28 Jan 2022

Brief communication: Monitoring a soft-rock coastal cliff using webcams and strain sensors

Diego Guenzi et al.

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Cited articles

Adams, P. N., Storlazzi, C. D., and Anderson, R. S.: Nearshore wave-induced cyclical flexing of sea cliffs, J. Geophys. Res., 110, F02002, https://doi.org/10.1029/2004JF000217, 2005. 
Allasia, P., Godone, D., Giordan, D., Guenzi, D., and Lollino, G.: Advances on Measuring Deep-Seated Ground Deformations Using Robotized Inclinometer System, Sensors, 20, 3769, https://doi.org/10.3390/s20133769, 2020. 
Dematteis, N., Giordan, D., Troilo, F., Wrzesniak, A., and Godone, D.: Ten-Year Monitoring of the Grandes Jorasses Glaciers Kinematics. Limits, Potentialities, and Possible Applications of Different Monitoring Systems, Remote Sensing, 13, 15, 3005, https://doi.org/10.3390/rs13153005, 2021. 
Fazio, N. L., Perrotti, M., Andriani, G. F., Mancini, F., Rossi, P., Castagnetti, C., and Lollino, P.: A new methodological approach to assess the stability of discontinuous rocky cliffs using in-situ survey supported by UAV-based techniques and 3-D finite element model: a case study, Eng. Geol., 260, 105205, https://doi.org/10.1016/j.enggeo.2019.105205, 2019. 
Giordan, D., Allasia, P., Dematteis, N., Dell'Anese, F., Vagliasindi, M., and Motta, E.: A Low-Cost Optical Remote Sensing Application for Glacier Deformation Monitoring in an Alpine Environment, Sensors, 16, 1750, https://doi.org/10.3390/s16101750, 2016. 
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Short summary
In the Apulia region (southeastern Italy) we are monitoring a soft-rock coastal cliff using webcams and strain sensors. In this urban and touristic area, coastal recession is extremely rapid and rockfalls are very frequent. In our work we are using low-cost and open-source hardware and software, trying to correlate both meteorological information with measures obtained from crack meters and webcams, aiming to recognize potential precursor signals that could be triggered by instability phenomena.
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