Articles | Volume 23, issue 12
https://doi.org/10.5194/nhess-23-3723-2023
https://doi.org/10.5194/nhess-23-3723-2023
Research article
 | 
01 Dec 2023
Research article |  | 01 Dec 2023

Machine-learning-based nowcasting of the Vögelsberg deep-seated landslide: why predicting slow deformation is not so easy

Adriaan L. van Natijne, Thom A. Bogaard, Thomas Zieher, Jan Pfeiffer, and Roderik C. Lindenbergh

Related authors

PROBABILISTIC VEGETATION TRANSITIONS IN DUNES BY COMBINING SPECTRAL AND LIDAR DATA
H. S. Kathmann, A. L. van Natijne, and R. C. Lindenbergh
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 1033–1040, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1033-2022,https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1033-2022, 2022

Related subject area

Databases, GIS, Remote Sensing, Early Warning Systems and Monitoring Technologies
AscDAMs: advanced SLAM-based channel detection and mapping system
Tengfei Wang, Fucheng Lu, Jintao Qin, Taosheng Huang, Hui Kong, and Ping Shen
Nat. Hazards Earth Syst. Sci., 24, 3075–3094, https://doi.org/10.5194/nhess-24-3075-2024,https://doi.org/10.5194/nhess-24-3075-2024, 2024
Short summary
Shoreline and land use–land cover changes along the 2004-tsunami-affected South Andaman coast: understanding changing hazard susceptibility
Vikas Ghadamode, Aruna Kumari Kondarathi, Anand K. Pandey, and Kirti Srivastava
Nat. Hazards Earth Syst. Sci., 24, 3013–3033, https://doi.org/10.5194/nhess-24-3013-2024,https://doi.org/10.5194/nhess-24-3013-2024, 2024
Short summary
Dynamical changes of seismic properties prior to, during, and after 2014–2015 Holuhraun Eruption, Iceland
Maria R.P. Sudibyo, Eva P. S. Eibl, Sebastian Hainzl, and Matthias Ohrnberger
EGUsphere, https://doi.org/10.5194/egusphere-2024-1445,https://doi.org/10.5194/egusphere-2024-1445, 2024
Short summary
Insights into the development of a landslide early warning system prototype in an informal settlement: the case of Bello Oriente in Medellín, Colombia
Christian Werthmann, Marta Sapena, Marlene Kühnl, John Singer, Carolina Garcia, Tamara Breuninger, Moritz Gamperl, Bettina Menschik, Heike Schäfer, Sebastian Schröck, Lisa Seiler, Kurosch Thuro, and Hannes Taubenböck
Nat. Hazards Earth Syst. Sci., 24, 1843–1870, https://doi.org/10.5194/nhess-24-1843-2024,https://doi.org/10.5194/nhess-24-1843-2024, 2024
Short summary
Exploring drought hazard, vulnerability, and related impacts to agriculture in Brandenburg
Fabio Brill, Pedro Henrique Lima Alencar, Huihui Zhang, Friedrich Boeing, Silke Hüttel, and Tobia Lakes
EGUsphere, https://doi.org/10.5194/egusphere-2024-1149,https://doi.org/10.5194/egusphere-2024-1149, 2024
Short summary

Cited articles

Belward, A. S. and Skøien, J. O.: Who Launched What, When and Why; Trends in Global Land-Cover Observation Capacity from Civilian Earth Observation Satellites, ISPRS J. Photogramm., 103, 115–128, https://doi.org/10.1016/j.isprsjprs.2014.03.009, 2015. a
Bengio, Y., Simard, P., and Frasconi, P.: Learning Long-Term Dependencies with Gradient Descent Is Difficult, IEEE T. Neural Networ., 5, 157–166, https://doi.org/10.1109/72.279181, 1994. a
Bogaard, T. A. and Greco, R.: Landslide Hydrology: From Hydrology to Pore Pressure, WIRES Water, 3, 439–459, https://doi.org/10.1002/wat2.1126, 2015. a, b
Bossi, G. and Marcato, G.: Planning Landslide Countermeasure Works through Long Term Monitoring and Grey Box Modelling, Geosciences, 9, 185, https://doi.org/10.3390/geosciences9040185, 2019. a
Cai, Z., Xu, W., Meng, Y., Shi, C., and Wang, R.: Prediction of Landslide Displacement Based on GA-LSSVM with Multiple Factors, B. Eng. Geol. Environ., 75, 637–646, https://doi.org/10.1007/s10064-015-0804-z, 2016. a
Download
Short summary
Landslides are one of the major weather-related geohazards. To assess their potential impact and design mitigation solutions, a detailed understanding of the slope is required. We tested if the use of machine learning, combined with satellite remote sensing data, would allow us to forecast deformation. Our results on the Vögelsberg landslide, a deep-seated landslide near Innsbruck, Austria, show that the formulation of such a machine learning system is not as straightforward as often hoped for.
Altmetrics
Final-revised paper
Preprint