105 citations as recorded by crossref.

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13. Model and criteria for slope monitoring and early warning in open-pit mines using ground-based real aperture radar H. Ding et al. https://doi.org/10.1007/s12665-024-11863-0
14. A Fast Deploying Monitoring and Real-Time Early Warning System for the Baige Landslide in Tibet, China Y. Wu et al. https://doi.org/10.3390/s20226619
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28. Application of the method for prediction of the failure location and time based on monitoring of a slope using synthetic aperture radar Y. Zhang et al. https://doi.org/10.1007/s12665-021-09989-6
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43. Application of advanced geophysical and photogrammetric methods in modeling and monitoring an active landslide: A case study from Podhale (Southern Poland) M. Kamiński https://doi.org/10.1016/j.enggeo.2025.108484
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45. GB-InSAR monitoring of slope deformations in a mountainous area affected by debris flow events W. Frodella et al. https://doi.org/10.5194/nhess-17-1779-2017
46. Application of the terrestrial laser scanner in the monitoring of earth structures J. Kogut & E. Pilecka https://doi.org/10.1515/geo-2020-0033
47. 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
48. Enhancing the reliability of landslide early warning systems by machine learning H. Thirugnanam et al. https://doi.org/10.1007/s10346-020-01453-z
49. Machine Learning: New Potential for Local and Regional Deep-Seated Landslide Nowcasting A. van Natijne et al. https://doi.org/10.3390/s20051425
50. ADVICE: A New Approach for Near-Real-Time Monitoring of Surface Displacements in Landslide Hazard Scenarios P. Allasia et al. https://doi.org/10.3390/s130708285
51. Big data managing in a landslide early warning system: experience from a ground-based interferometric radar application E. Intrieri et al. https://doi.org/10.5194/nhess-17-1713-2017
52. Physically based and distributed rainfall intensity and duration thresholds for shallow landslides R. Marin https://doi.org/10.1007/s10346-020-01481-9
53. Critical threshold mining of landslide deformation and intelligent early-warning methods based on multi-factor fusion D. Liu et al. https://doi.org/10.1007/s10064-024-03841-4
54. Using Complementary Ensemble Empirical Mode Decomposition and Gated Recurrent Unit to Predict Landslide Displacements in Dam Reservoir B. Yang et al. https://doi.org/10.3390/s22041320
55. 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
56. The First International Workshop on Warning Criteria for Active Slides: technical issues, problems and solutions for managing early warning systems C. Cloutier et al. https://doi.org/10.1007/s10346-014-0530-9
57. Safety monitoring and effect analysis of fracturing body on the right bank of Pubugou reservoir head in China based on space-ground-body monitoring mode H. Liang et al. https://doi.org/10.1007/s10346-024-02230-y
58. Double-threshold validation tool (DTVT): From landslide hazard maps to operational early warning systems N. Nocentini et al. https://doi.org/10.1016/j.ijdrr.2025.105786
59. Monitoring strategies for local landslide early warning systems G. Pecoraro et al. https://doi.org/10.1007/s10346-018-1068-z
60. Hydraulic response and stability of a reservoir slope with landslide potential under the combined effect of rainfall and water level fluctuation M. Chen et al. https://doi.org/10.1007/s12665-020-09279-7
61. Systèmes d’alerte précoce pour les aléas naturels et environnementaux : virage ou mirage technologique ? D. Didier et al. https://doi.org/10.7202/1042922ar
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63. A Method for Predicting Landslides Based on Micro-Deformation Monitoring Radar Data W. Tan et al. https://doi.org/10.3390/rs15030826
64. Utilizing crowdsourcing to enhance the mitigation and management of landslides C. Choi et al. https://doi.org/10.1007/s10346-018-1034-9
65. A new early warning criterion for landslides movement assessment: Deformation Standardized Anomaly Index J. Zhang et al. https://doi.org/10.1007/s10064-024-03672-3
66. Quantifying the effectiveness of early warning systems for natural hazards M. Sättele et al. https://doi.org/10.5194/nhess-16-149-2016
67. Geological monitoring networks for risk management close to large rock cliffs: the case history of Gallivaggio and Cataeggio in the italian Alps L. Dei Cas et al. https://doi.org/10.5194/gh-76-85-2021
68. A simple method to help determine landslide susceptibility from spaceborne InSAR data: the Montescaglioso case study T. Carlà et al. https://doi.org/10.1007/s12665-016-6308-8
69. Long-term geoelectrical monitoring of landslides in natural and engineered slopes J. Chambers et al. https://doi.org/10.1190/tle41110768.1
70. Probabilistic landslide ensemble prediction systems: lessons to be learned from hydrology E. Canli et al. https://doi.org/10.5194/nhess-18-2183-2018
71. A statistical-based approach for determining the intensity of unrest phases at Stromboli volcano (Southern Italy) using one-step-ahead forecasts of displacement time series T. Carlà et al. https://doi.org/10.1007/s11069-016-2451-5
72. Development of community-based landslide early warning system in the earthquake-affected areas of Nepal Himalaya P. Thapa & B. Adhikari https://doi.org/10.1007/s11629-019-5586-5
73. 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
74. Displacement residuals reveal landslide regime shifts L. Nava et al. https://doi.org/10.1007/s10346-024-02353-2
75. Towards establishing rainfall thresholds for a real-time landslide early warning system in Sikkim, India G. Harilal et al. https://doi.org/10.1007/s10346-019-01244-1
76. Assessing two methods of defining rainfall intensity and duration thresholds for shallow landslides in data-scarce catchments of the Colombian Andean Mountains R. Marin et al. https://doi.org/10.1016/j.catena.2021.105563
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