Research on the method of determining landslide threshold based on accelerating point dynamic identification
Author:
Funder
Key Research and Development Projects of Shaanxi Province
Department of Transport of Shaanxi Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10346-024-02305-w.pdf
Reference64 articles.
1. Bayer B, Simoni A, Mulas M et al (2018) Deformation responses of slow moving landslides to seasonal rainfall in the Northern Apennines, measured by InSAR. Geomorphology 308(MAY1):293–306. https://doi.org/10.1016/j.geomorph.2018.02.020
2. Bernardie S, Desramaut N, Malet JP et al (2015) Prediction of changes in landslide rates induced by rainfall. Landslides 12(3):481–494. https://doi.org/10.1007/s10346-014-0495-8
3. Bozzano F, Cipriani I, Mazzanti P et al (2014) A field experiment for calibrating landslide time-of-failure prediction functions. Int J Rock Mech Min Sci 67:69–77. https://doi.org/10.1016/j.ijrmms.2013.12.006
4. Brown I, Hittinger M, Goodman R (1980) Finite element study of the Nevis Bluff (New Zealand) rock slope failure. Rock Mech 12(3):231–245. https://doi.org/10.1007/BF01251027
5. Carla T, Intrieri E, di Traglia F et al (2017) Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses. Landslides 14(2):517–534. https://doi.org/10.1007/s10346-016-0731-5
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