44 citations as recorded by crossref.

1. Identifying Potential Landslides in Steep Mountainous Areas Based on Improved Seasonal Interferometry Stacking-InSAR Z. Li et al. https://doi.org/10.3390/rs15133278
2. The key to improving the beauty of the giant retaining wall in valleys: Increasing visual extension J. Song et al. https://doi.org/10.1371/journal.pone.0287251
3. Late Pleistocene landslide-dammed events in the Panzhihua-Wudongde reach of the Jinsha River in southeastern Tibetan: Implications for the origin of the Longjie Formation F. Liu et al. https://doi.org/10.1016/j.geomorph.2026.110431
4. A Deep-Learning-Based Algorithm for Landslide Detection over Wide Areas Using InSAR Images Considering Topographic Features N. Li et al. https://doi.org/10.3390/s24144583
5. Distribution Pattern of Landslides Triggered by the 2014 Ludian Earthquake of China: Implications for Regional Threshold Topography and the Seismogenic Fault Identification S. Zhou et al. https://doi.org/10.3390/ijgi5040046
6. Probabilistic seismic source inversion from regional landslide evidence R. Rasanen & B. Maurer https://doi.org/10.1007/s10346-021-01780-9
7. Susceptibility assessment of landslides triggered by earthquakes in the Western Sichuan Plateau J. Cao et al. https://doi.org/10.1016/j.catena.2018.12.013
8. Landslide susceptibility assessment in the Central Yunnan Plateau by assembling optimized statistical and machine learning models J. Chen et al. https://doi.org/10.1186/s40677-026-00380-w
9. Protecting highway bridges against debris flows using lateral berms: a case study of the 2008 and 2011 Cheyang debris flow events, China F. Qiu et al. https://doi.org/10.1080/19475705.2017.1414718
10. Landslide Identification in Human-Modified Alpine and Canyon Area of the Niulan River Basin Based on SBAS-InSAR and Optical Images S. Yang et al. https://doi.org/10.3390/rs15081998
11. Dynamic response and failure evolution of sandy slopes under ground motion before and after rainfall infiltration J. Han et al. https://doi.org/10.1007/s10346-026-02757-2
12. Numerical investigation on seismic response characteristics and deformation mechanism of high-steep rock slopes containing weak structural planes using time-frequency joint analysis D. Xu et al. https://doi.org/10.1007/s10064-025-04143-z
13. Assessment of attenuation regressions for earthquake-triggered landslides in the Italian Apennines: insights from recent and historical events F. Livio & M. Ferrario https://doi.org/10.1007/s10346-020-01464-w
14. Landslides triggered by the 22 July 2013 Minxian–Zhangxian, China, Mw 5.9 earthquake: Inventory compiling and spatial distribution analysis C. Xu et al. https://doi.org/10.1016/j.jseaes.2014.06.014
15. Deep-seated zonal damage in anti-dip layered rock slope: A case study in southwest China G. Yang et al. https://doi.org/10.1016/j.jrmge.2025.08.012
16. Evaluation of factors controlling large earthquake-induced landslides by the Wenchuan earthquake X. Chen et al. https://doi.org/10.5194/nhess-12-3645-2012
17. Simulation of a long-runout rock avalanche triggered by the Lushan earthquake in the Tangjia Valley, Tianquan, Sichuan, China B. Li et al. https://doi.org/10.1016/j.enggeo.2017.01.007
18. Predicting landslide scenes under potential earthquake scenarios in the Xianshuihe fault zone, Southwest China Y. Zhang et al. https://doi.org/10.1007/s11629-017-4363-6
19. Landslides and other geomorphologic and hydrologic effects induced by earthquakes in Portugal T. Vaz & J. Zêzere https://doi.org/10.1007/s11069-015-2071-5
20. Displacement Characterization and Spatial-Temporal Evolution of the 2020 Aniangzhai Landslide in Danba County Using Time-Series InSAR and Multi-Temporal Optical Dataset J. Kuang et al. https://doi.org/10.3390/rs14010068
21. The Mdesign for engineering applications of Neo-Deterministic Seismic Hazard Assessment (NDSHA) within the China Seismic Experimental Site (CSES) Y. Zhang et al. https://doi.org/10.1016/j.enggeo.2025.108415
22. Joint Use of Optical and Radar Remote Sensing Data for Characterizing the 2020 Aniangzhai Landslide Post-Failure Displacement J. Kuang et al. https://doi.org/10.3390/rs15020369
23. Earthquake-Triggered Landslides in Greece from Antiquity to the Present: Temporal, Spatial and Statistical GIS-Based Analysis S. Mavroulis et al. https://doi.org/10.3390/land14020307
24. Accurate Measurement of Creep-Induced Degradation in High-Steep Rock Slopes Using Multi-source Monitoring Data: A Case Study of the Lianghekou Pumped Storage Power Station J. Jin et al. https://doi.org/10.1007/s00603-025-05143-x
25. Fusion of numerical simulation and on-site monitoring for full-life-cycle stability regulation and reinforcement optimization of karst region large-span aqueduct slopes: a case study of the Longchang Aqueduct in the Qianzhong Water Hub, China Z. Xu et al. https://doi.org/10.1080/27669645.2025.2586261
26. Research on the Evolution Network Model of the Landslide Disaster Chain: A Case Study of the Baige Landslide F. Gao et al. https://doi.org/10.3390/app14020499
27. Strong-Motion Attenuation Characteristics in Sichuan Basin Derived from Densely Distributed Records and Its Implications for Ground-Motion Modeling R. Hou et al. https://doi.org/10.1785/0120250279
28. Sustainable Fruition of Cultural Heritage in Areas Affected by Rockfalls S. Mineo & G. Pappalardo https://doi.org/10.3390/su12010296
29. Quantification of model uncertainty and variability for landslide displacement prediction based on Monte Carlo simulation L. Wang et al. https://doi.org/10.1016/j.gr.2023.03.006
30. Distribution features and formation mechanism of landslides along the middle segment of the Yalong River, China C. Li et al. https://doi.org/10.1007/s10064-024-03953-x
31. Seismic response of steep slopes inferred from ambient noise and accelerometer recordings: the case of Dadu River valley, China V. Del Gaudio et al. https://doi.org/10.1016/j.enggeo.2019.105197
32. Control of style-of-faulting on spatial pattern of earthquake-triggered landslides T. Gorum & E. Carranza https://doi.org/10.1007/s13762-015-0752-y
33. Network-Based Earthquake Magnitude Determination via Deep Learning W. Kuang et al. https://doi.org/10.1785/0220200317
34. Study on the stability of bedding rock slopes with weak structural surfaces under multiple parametric influences J. Chen et al. https://doi.org/10.1088/2631-8695/ae4cf0
35. Evaluating completeness and consistency in earthquake-induced ground effects inventorying: insights from the last release of the Italian CEDIT catalogue M. Fiorucci et al. https://doi.org/10.1007/s10064-026-05022-x
36. Insights into some large-scale landslides in southeastern margin of Qinghai-Tibet Plateau B. Zhao et al. https://doi.org/10.1016/j.jrmge.2022.09.005
37. Identifying Potential Landslides by Stacking-InSAR in Southwestern China and Its Performance Comparison with SBAS-InSAR L. Zhang et al. https://doi.org/10.3390/rs13183662
38. Co-seismic stress changes and triggering mechanism of earthquake-induced landslides: a case of 2005 Kashmir earthquake Z. Kazmi et al. https://doi.org/10.1007/s12517-021-08514-0
39. An Automatic Identification Method for Large-Scale Landslide Hazard Potential Integrating InSAR and CRF-Faster RCNN: A Case Study of Ahai Reservoir Area in Jinsha River Basin Y. Dong et al. https://doi.org/10.3390/rs18020283
40. Topographic Controls on the Distribution of Coseismic Landslides: A Case Study Using the Coefficient of Variation of the 2014 Ludian, Yunnan, China, Ms6.5 Earthquake X. Chen et al. https://doi.org/10.2113/2022/6678652
41. Brief Communication: Landslides triggered by the Ms = 7.0 Lushan earthquake, China X. Chen et al. https://doi.org/10.5194/nhess-14-1257-2014
42. Dynamic process analysis of large-scale landslides triggered by the Wenchuan earthquake via the discrete element method X. Huang et al. https://doi.org/10.1007/s11069-025-07114-5
43. Coupling InSAR and numerical modeling for characterizing landslide movements under complex loads in urbanized hillslopes P. Ma et al. https://doi.org/10.1007/s10346-020-01604-2
44. Crustal response to water loads and expansion of triggered seismicity around the Xiluodu Reservoir, Southwest China X. Shi et al. https://doi.org/10.59717/j.xinn-geo.2024.100047