54 citations as recorded by crossref.

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3. Relationship between river bank stability and hydrological processes using in situ measurement data G. Mentes https://doi.org/10.1556/24.62.2019.01
4. A reliability evaluation of four landslide failure forecasting methods in real-time monitoring applications S. Sharifi et al. https://doi.org/10.1007/s10346-024-02293-x
5. Landslide-prone areas in Makale Selatan with the analytical hierarchy process method Y. Sarma et al. https://doi.org/10.1088/1755-1315/1230/1/012083
6. An analytical solution for critical sliding surface of stepped rock slope: a case study of Xinjing coal mine landslide X. Huang et al. https://doi.org/10.1007/s10064-024-04079-w
7. A cellular automaton integrating spatial case-based reasoning for predicting local landslide hazards J. Chen et al. https://doi.org/10.1080/13658816.2023.2273877
8. Evolution mechanism of pore structures in sandstone under coupled effect of hygrothermal cycles and Na2SO4 solution J. Geng et al. https://doi.org/10.1038/s41598-026-46746-w
9. 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
10. Prediction of landslide displacement using multi-kernel extreme learning machine and maximum information coefficient based on variational mode decomposition: a case study in Shaanxi, China Q. Ling et al. https://doi.org/10.1007/s11069-021-04713-w
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12. Satellite Interferometry as a Tool for Early Warning and Aiding Decision Making in an Open-Pit Mine E. Intrieri et al. https://doi.org/10.1109/JSTARS.2019.2953339
13. When hazard avoidance is not an option: lessons learned from monitoring the postdisaster Oso landslide, USA M. Reid et al. https://doi.org/10.1007/s10346-021-01686-6
14. Formation mechanism and dynamic process of open-pit coal mine landslides: a case study of the Xinjing landslide in Inner Mongolia, China Q. Wang et al. https://doi.org/10.1007/s10346-023-02193-6
15. AI-Enhanced Image Processing for Real-Time Brittle Rock Failure Forecasting: Development and Validation Using a Large Experimental Dataset F. Gao et al. https://doi.org/10.1007/s00603-025-05137-9
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18. 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
19. A robust discretization method of factor screening for landslide susceptibility mapping using convolution neural network, random forest, and logistic regression models Z. Zhao & J. Chen https://doi.org/10.1080/17538947.2023.2174192
20. Kinematics and Controlling Factors of Slow-Moving Landslides in Central Texas: A Multisource Data Fusion Approach E. Gebremichael et al. https://doi.org/10.3390/geosciences14050133
21. Indeterminacy of displacement and stress of geologic rock mass system in the critically non-stationary state: implication on prediction of geo-hazards Z. Feng et al. https://doi.org/10.1007/s11069-021-04611-1
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23. Applications of UAV in landslide research: a review B. Chen et al. https://doi.org/10.1007/s10346-025-02547-2
24. Displacement prediction of step-like landslide by applying a novel kernel extreme learning machine method C. Zhou et al. https://doi.org/10.1007/s10346-018-1022-0
25. On the monitoring and early-warning of brittle slope failures in hard rock masses: Examples from an open-pit mine T. Carlà et al. https://doi.org/10.1016/j.enggeo.2017.08.007
26. Online accelerating precursor identification and dynamic probabilistic prediction for rock slope failures using Bayesian inference M. Chen et al. https://doi.org/10.1016/j.jrmge.2025.08.048
27. Deep learning powered long-term warning systems for reservoir landslides T. Zeng et al. https://doi.org/10.1016/j.ijdrr.2023.103820
28. Development of Smart Wired Module for real-time slope failure tracking S. Banne et al. https://doi.org/10.1080/17486025.2026.2674155
29. 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
30. Landslide detection, monitoring and prediction with remote-sensing techniques N. Casagli et al. https://doi.org/10.1038/s43017-022-00373-x
31. Can satellite InSAR innovate the way of large landslide early warning? P. Zeng et al. https://doi.org/10.1016/j.enggeo.2024.107771
32. Microseismic monitoring-based stability analysis of high rock slopes in deep open-pit mines C. Zhao et al. https://doi.org/10.1016/j.jrmge.2026.02.028
33. Algorithms to enhance detection of landslide acceleration moment and time-to-failure forecast using time-series displacements S. Sharifi et al. https://doi.org/10.1016/j.enggeo.2022.106832
34. Landslide displacement prediction by using Bayesian optimization–temporal convolutional networks J. Yang et al. https://doi.org/10.1007/s11440-023-02205-8
35. 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
36. Pinpointing Early Signs of Impending Slope Failures From Space S. Zhou et al. https://doi.org/10.1029/2021JB022957
37. Reply to discussion on “Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses” by F. Bozzano, P. Mazzanti, and S. Moretto T. Carlà et al. https://doi.org/10.1007/s10346-018-0991-3
38. A new prediction method for the occurrence of landslides based on the time history of tilting of the slope surface J. Xie et al. https://doi.org/10.1007/s10346-019-01283-8
39. Landslide susceptibility and building exposure assessment using machine learning models and geospatial analysis techniques C. Luu et al. https://doi.org/10.1016/j.asr.2024.08.046
40. Acceleration stage detection and dynamic model selection for real-time landslide time-of-failure predictions B. Feng et al. https://doi.org/10.1007/s11440-025-02878-3
41. Monitoring the risk of a tailings dam collapse through spectral analysis of satellite InSAR time-series data S. Das et al. https://doi.org/10.1007/s00477-024-02713-3
42. KLC2020 implementation: challenges for the development of satellite landslide early warning systems E. Intrieri et al. https://doi.org/10.1007/s10346-021-01721-6
43. 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
44. Experimental Study on the Relationship between the Velocity of Surface Movements and Tilting Rate in Pre-Failure Stage of Rainfall-Induced Landslides J. Xie et al. https://doi.org/10.3390/s21185988
45. An approach for prospective forecasting of rock slope failure time J. Leinauer et al. https://doi.org/10.1038/s43247-023-00909-z
46. A spatial case-based reasoning method for regional landslide risk assessment Z. Zhao et al. https://doi.org/10.1016/j.jag.2021.102381
47. A generalized phenomenological approach for real-time automatic time of failure forecasting of landslides J. Zhang et al. https://doi.org/10.1016/j.enggeo.2025.108303
48. Lateral edifice collapse and volcanic debris avalanches: a post-1980 Mount St. Helens perspective L. Siebert & M. Reid https://doi.org/10.1007/s00445-023-01662-z
49. Alert threshold assessment based on equivalent displacements for the identification of potentially critical landslide events A. Valletta et al. https://doi.org/10.1007/s11069-022-05606-2
50. A Stochastic Dynamical Model of Slope Creep and Failure Q. Lei & D. Sornette https://doi.org/10.1029/2022GL102587
51. Time-series-analysis-based detection of critical transitions in real-world non-autonomous systems K. Lehnertz https://doi.org/10.1063/5.0214733
52. Integration of ground-based radar and satellite InSAR data for the analysis of an unexpected slope failure in an open-pit mine T. Carlà et al. https://doi.org/10.1016/j.enggeo.2018.01.021
53. 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
54. Landslide failure time prediction with a new model: case studies in Fushun west open pit mine, China J. Hu et al. https://doi.org/10.1007/s10064-024-03902-8