Glacier Instabilities Identification and Monitoring: Case Studies in the Alps

Authors

  • Daniele Giordan Italian National Research Council, Research Institute for Geo-Hydrological Protection, Turin, Italy Author

DOI:

https://doi.org/10.64862/ajeg.2025.2sp.69.193

Keywords:

Glacier instabilities, Monitoring

Abstract

Monitoring glacier instability is essential for assessing geo-hydrological hazards in mountain regions. This study reviews monitoring systems based on measurement type and data acquisition frequency, emphasizing their role in early warning. Instruments range from single-measurement and multi-temporal methods to near-real-time and real-time networks. Combining topographic, geophysical, and meteorological monitoring enhances reliability through redundancy and cross-validation. Low-cost technologies, including open-access satellite data, webcams, drones, and Raspberry-Pi systems, expand spatial coverage at reduced costs. Integrated, multi-sensor networks represent a scalable and cost-effective approach to detecting instability and improving risk management in rapidly changing alpine environments.

References

Dematteis, N., Giordan, D., and Crippa, B., Monserrat, O. (2022a). Fast local adaptive multiscale image matching algorithm for remote sensing image correlation. Computers and Geosciences, 159, 104984. https://doi.org/10.1016/j.cageo.2021.104988

Dematteis, N., Giordan, D., Perret, P., Grab, M., Maurer, H., and Troilo, F. (2022b). Evidences of bedrock forcing on glacier morphodynamics: A case study in the Italian Alps. Frontiers in Earth Science, 10, 793546. https://doi.org/10.3389/feart.2022.793546

Dematteis, N., Luzi, G., Giordan, D., Zucca, F., and Allasia, P. (2017). Monitoring Alpine glacier surface deformations with GB-SAR. Remote Sensing Letters, (10), 947–956. https://doi.org/10.1080/2150704X.2017.1335905

Giordan, D., Allasia, P., Dematteis, N., Dell’Anese, F., Vagliasindi, M., and Motta, E. (2016). A low-cost optical remote sensing application for glacier deformation monitoring in an Alpine environment. Sensors, 16(10), 1750. https://doi.org/10.3390/s16101750

Ioli, F., Dematteis, N., Giordan, D., Nex, F., and Pinto, L. (2024). Deep learning low-cost photogrammetry for 4D short-term glacier dynamics monitoring. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 92, 657–678. https://doi.org/10.1007/s41064-023-00272-w

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Published

2025-11-27

How to Cite

Glacier Instabilities Identification and Monitoring: Case Studies in the Alps. (2025). Asian Journal of Engineering Geology, 2(Sp Issue), 149-150. https://doi.org/10.64862/ajeg.2025.2sp.69.193

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