62 citations as recorded by crossref.

1. Integral Method of Stability Analysis and Maintenance of Slope M. Park et al. https://doi.org/10.14481/jkges.2016.17.3.27
2. Assessment of Landslide Pre-Failure Monitoring and Forecasting Using Satellite SAR Interferometry S. Moretto et al. https://doi.org/10.3390/geosciences7020036
3. Forecasting the time of failure of landslides at slope-scale: A literature review E. Intrieri et al. https://doi.org/10.1016/j.earscirev.2019.03.019
4. Acoustic and Microseismic Characterization in Steep Bedrock Permafrost on Matterhorn (CH) S. Weber et al. https://doi.org/10.1029/2018JF004615
5. Estimation of the lower boundary and development of a sliding surface in a gradually deforming slope by comparing LiDAR data taken in different years R. NISHII et al. https://doi.org/10.3313/jls.56.87
6. On prediction of slope failure time with the inverse velocity method J. Zhang et al. https://doi.org/10.1080/17499518.2022.2132263
7. Failure Mechanism and Mitigation Measures of the G1002 Electricity Pylon Landslide at the Jinping I Hydropower Station G. Luo et al. https://doi.org/10.1155/2020/8820315
8. Analysis of In-Situ Creep Behavior of Coal Mine Waste Dumps Using GBInSAR for Landslide Failure Prediction A. Tiwari et al. https://doi.org/10.1007/s42461-024-01077-0
9. Monitoring systems for warning impending failures in slopes and open pit mines A. Vaziri et al. https://doi.org/10.1007/s11069-010-9542-5
10. A comparative study of different kinematics - based methods to predict the time of slope failure S. Philip et al. https://doi.org/10.1088/1757-899X/1116/1/012158
11. Creep of clayey soil induced by elevated pore-water pressure: Implication for forecasting the time of failure of rainfall-triggered landslides C. Chang & G. Wang https://doi.org/10.1016/j.enggeo.2021.106461
12. Coevolution of Rock Slope Instability Damage and Resonance Frequencies From Distinct‐Element Modeling E. Jensen & J. Moore https://doi.org/10.1029/2023JF007305
13. Shear band propagation and mechanical behaviours of landslides under top loading L. Wei et al. https://doi.org/10.1016/j.trgeo.2022.100882
14. Landslide displacement prediction using kinematics-based random forests method: A case study in Jinping Reservoir Area, China X. Hu et al. https://doi.org/10.1016/j.enggeo.2020.105975
15. Analyzing the formation mechanism of the Xuyong landslide, Sichuan province, China, and emergency monitoring based on multiple remote sensing platform techniques Y. Luo et al. https://doi.org/10.1080/19475705.2020.1745903
16. Patterns of precursory rockfall prior to slope failure N. Rosser et al. https://doi.org/10.1029/2006JF000642
17. Soil slope monitoring with Distributed Acoustic Sensing under wetting and drying cycles J. Kang et al. https://doi.org/10.5194/esurf-13-1133-2025
18. A framework for identifying the onset of landslide acceleration based on the exponential moving average (EMA) J. Wang et al. https://doi.org/10.1007/s11629-023-7905-0
19. Development of an Algorithm for the Prediction of Slope Failure in Surface Mines M. Masood et al. https://doi.org/10.1007/s40033-023-00513-7
20. Dynamic response of the Chamousset rock column (Western Alps, France) C. Lévy et al. https://doi.org/10.1029/2009JF001606
21. Landslide kinematics inferred from in situ measurements: the Cliets rock-slide (Savoie, French Alps) M. Desrues et al. https://doi.org/10.1007/s10346-021-01726-1
22. Landslides caught on seismic networks and satellite radars A. Manconi & A. Mondini https://doi.org/10.5194/nhess-22-1655-2022
23. Formation phases and structural failure of a landslide compartment at Brienz/Brinzauls, Switzerland R. Kenner et al. https://doi.org/10.1016/j.enggeo.2025.108343
24. A new forecasting method for failure time of creep landslide based on nonlinear creep behavior and new pre-warning criterion S. Zhang et al. https://doi.org/10.3389/feart.2022.1018432
25. Environmental Controls and Transition of the Baige Landslide Deformation Revealed by Time-Series Remote Sensing Observations S. Huang et al. https://doi.org/10.3390/rs18132169
26. Critical assessment of landslide failure forecasting methods with case histories: a comparative study of INV, MINV, SLO, and VOA S. Sharifi et al. https://doi.org/10.1007/s10346-024-02237-5
27. An approach for prospective forecasting of rock slope failure time J. Leinauer et al. https://doi.org/10.1038/s43247-023-00909-z
28. Definition and application of a multi-criteria algorithm to identify landslide acceleration phases A. Valletta et al. https://doi.org/10.1080/17499518.2021.1952610
29. A Novel Predictive Framework for the Determination of the Threshold Limit Velocity of Open-Cast Mine Slopes M. Masood et al. https://doi.org/10.1007/s40033-024-00770-0
30. Kinematics and geological constraints of the slow-moving Pisciotta rock slide (southern Italy) P. De Vita et al. https://doi.org/10.1016/j.geomorph.2013.07.015
31. A new data-driven approach for dynamic landslide life expectancy prediction based on kinematic features J. Zhang et al. https://doi.org/10.1007/s11440-025-02702-y
32. A Comparison Study between Traditional and Finite Element Methods for Slope Stability Evaluations F. Göktepe & I. Keskin https://doi.org/10.1007/s12594-018-0864-3
33. Built to last: Long-term stability of steep deglaciated slopes of alpine karst plateaus (Northern Calcareous Alps, Austria) J. Szczygieł et al. https://doi.org/10.1016/j.enggeo.2026.108924
34. Le glissement du Chambon : évolution du phénomène et gestion de crise L. Dubois et al. https://doi.org/10.1051/geotech/2016010
35. Multistage 54,000 m3 rockfall (Stampa, Western Norway): Insights from comprehensive monitoring and failure analysis A. Maschler et al. https://doi.org/10.1007/s10346-025-02620-w
36. Identifying rock slope failure precursors using LiDAR for transportation corridor hazard management R. Kromer et al. https://doi.org/10.1016/j.enggeo.2015.05.012
37. The use of pore pressure reinflation testing in landslide management in Hong Kong K. Ng & D. Petley https://doi.org/10.1144/1470-9236/08-008
38. Development of progressive landslide failure in cohesive materials D. Petley et al. https://doi.org/10.1130/G21147.1
39. Prediction of landslide failure time based on moving average convergence and divergence coupling with Bayesian updating method X. Zhou et al. https://doi.org/10.1016/j.enggeo.2024.107781
40. Probabilistic prediction of slope failure time J. Zhang et al. https://doi.org/10.1016/j.enggeo.2020.105586
41. Automatic approach for increasing the location accuracy of slow-moving landslide endogenous seismicity: the APOLoc method F. Provost et al. https://doi.org/10.1093/gji/ggy330
42. How water, temperature, and seismicity control the preconditioning of massive rock slope failure (Hochvogel) J. Leinauer et al. https://doi.org/10.5194/esurf-12-1027-2024
43. Dynamic intelligent prediction approach for landslide displacement based on biological growth models and CNN-LSTM Z. Wang et al. https://doi.org/10.1007/s11629-024-9113-y
44. Deformation pattern of a creeping slope revealed by continuous GNSS monitoring in northern Taiwan C. Tseng et al. https://doi.org/10.1016/j.enggeo.2025.108491
45. An extrapolation technique for subsurface geomorphology in active natural slopes using limited borehole deformation data R. Kaunda https://doi.org/10.1016/j.geomorph.2011.06.035
46. Forward simulation and sensitivity analysis of run-out scenarios using MassMov2D at the Trafoi rockslide (South Tyrol, Italy) J. Iannacone et al. https://doi.org/10.1080/17499518.2013.773816
47. A linear regression framework for predicting subsurface geometries and displacement rates in deep-seated, slow-moving landslides R. Kaunda https://doi.org/10.1016/j.enggeo.2010.03.004
48. Influence of environmental parameters on the seismic velocity changes in a clayey mudflow (Pont-Bourquin Landslide, Switzerland) G. Bièvre et al. https://doi.org/10.1016/j.enggeo.2018.08.013
49. Correlation between Acoustic Emission Behaviour and Dynamics Model during Three-Stage Deformation Process of Soil Landslide L. Deng et al. https://doi.org/10.3390/s21072373
50. Prediction of open-pit slope displacement and time-to-failure based on hybrid deep learning S. Wang et al. https://doi.org/10.1007/s10064-026-05048-1
51. Deep learning powered long-term warning systems for reservoir landslides T. Zeng et al. https://doi.org/10.1016/j.ijdrr.2023.103820
52. Optimal Measurement System for Weak Rock Slopes in an Open-Pit Mine C. SunWoo et al. https://doi.org/10.9720/kseg.2012.22.2.157
53. Innovative Monitoring Tools and Early Warning Systems for Risk Management: A Case Study A. Segalini et al. https://doi.org/10.3390/geosciences9020062
54. Combined ambient vibration and surface displacement measurements for improved progressive failure monitoring at a toppling rock slab in Utah, USA E. Jensen et al. https://doi.org/10.3389/feart.2024.1364653
55. Progressive destabilization of a freestanding rock pillar in permafrost on the Matterhorn (Swiss Alps): Hydro-mechanical modeling and analysis S. Weber et al. https://doi.org/10.5194/esurf-13-1157-2025
56. Landslide forecasting and factors influencing predictability E. Intrieri & G. Gigli https://doi.org/10.5194/nhess-16-2501-2016
57. Experimental Test of Theory for the Stability of Partially Saturated Vertical Cut Slopes M. Morse et al. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001119
58. Bayesian machine learning-based method for prediction of slope failure time J. Zhang et al. https://doi.org/10.1016/j.jrmge.2021.09.010
59. Shear Band Propagation and Mechanical Behaviours of Landslides of Slope Under Top Loading L. Wei et al. https://doi.org/10.2139/ssrn.4013334
60. Fiber bundle model for multiscale modeling of hydromechanical triggering of shallow landslides D. Cohen et al. https://doi.org/10.1029/2009WR007889
61. Satellite Pre-Failure Detection and In Situ Monitoring of the Landslide of the Tunnel du Chambon, French Alps M. Desrues et al. https://doi.org/10.3390/geosciences9070313
62. Prediction of time to slope failure based on a new model Z. Li et al. https://doi.org/10.1007/s10064-021-02234-1