Articles | Volume 13, issue 4
https://doi.org/10.5194/esurf-13-705-2025
https://doi.org/10.5194/esurf-13-705-2025
Research article
 | 
08 Aug 2025
Research article |  | 08 Aug 2025

AI-based tracking of fast-moving alpine landforms using high-frequency monoscopic time-lapse imagery

Hanne Hendrickx, Melanie Elias, Xabier Blanch, Reynald Delaloye, and Anette Eltner

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Cited articles

Altmann, M., Piermattei, L., Haas, F., Heckmann, T., Fleischer, F., Rom, J., Betz-Nutz, S., Knoflach, B., Müller, S., Ramskogler, K., Pfeiffer, M., Hofmeister, F., Ressl, C., and Becht, M.: Long-Term Changes of Morphodynamics on Little Ice Age Lateral Moraines and the Resulting Sediment Transfer into Mountain Streams in the Upper Kauner Valley, Austria, Water, 12, 3375, https://doi.org/10.3390/W12123375, 2020. 
Barsch, D.: Rockglaciers, Springer Berlin Heidelberg, Berlin, Heidelberg, https://doi.org/10.1007/978-3-642-80093-1, 1996. 
Blanch, X., Guinau, M., Eltner, A., and Abellan, A.: Fixed photogrammetric systems for natural hazard monitoring with high spatio-temporal resolution, Nat. Hazards Earth Syst. Sci., 23, 3285–3303, https://doi.org/10.5194/nhess-23-3285-2023, 2023. 
Cicoira, A., Marcer, M., Gärtner-Roer, I., Bodin, X., Arenson, L. U., and Vieli, A.: A general theory of rock glacier creep based on in-situ and remote sensing observations, Permafrost Periglac., 32, 139–153, https://doi.org/10.1002/ppp.2090, 2021. 
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Short summary
This study presents a novel AI-based method for tracking and analysing the movement of rock glaciers and landslides, key landforms in high mountain regions. By utilising time-lapse images, our approach generates detailed velocity data, uncovering movement patterns often missed by traditional methods. This cost-effective tool enhances geohazard monitoring, providing insights into environmental drivers, improving process understanding, and contributing to better safety in alpine areas.
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