67 citations as recorded by crossref.

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20. A WebGIS for the dissemination of information on historical landslides and floods in Umbria, Italy P. Salvati et al. https://doi.org/10.1007/s10707-008-0072-1
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25. Landslide Vulnerability Criteria: A Case Study from Umbria, Central Italy M. Galli & F. Guzzetti https://doi.org/10.1007/s00267-006-0325-4
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30. A millennium-long climate history of erosive storms across the Tiber River Basin, Italy, from 725 to 2019 CE N. Diodato et al. https://doi.org/10.1038/s41598-021-99720-z
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35. Economic landslide susceptibility under a socio-economic perspective: an application to Umbria Region (Central Italy) M. Donnini et al. https://doi.org/10.1007/s10037-020-00143-6
36. A new method to detect changes in displacement rates of slow-moving landslides using InSAR time series A. Urgilez Vinueza et al. https://doi.org/10.1007/s10346-022-01913-8
37. Geo‐hydro‐mechanics for quantitative landslide hazard assessment (QHA) F. COTECCHIA et al. https://doi.org/10.1002/cepa.662
38. Integrating geomorphology, statistic and numerical simulations for landslide invasion hazard scenarios mapping: An example in the Sorrento Peninsula (Italy) F. Lucà et al. https://doi.org/10.1016/j.cageo.2014.01.006
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41. Archaeological evidence for Holocene landslide activity in the Eastern Carpathian lowland M. Niculiţă et al. https://doi.org/10.1016/j.quaint.2015.12.048
42. Characteristics of landslides and assessment of deep-seated landslide susceptibility in Northern Turkey T. Duman & T. Çan https://doi.org/10.1007/s42990-023-00105-3
43. Geomechanics of a snowmelt-induced slope failure in glacial till A. Trandafir et al. https://doi.org/10.1007/s12665-014-3658-y
44. The Felbertauern landslide of 2013 in Austria: Impact on transport networks, regional economy and policy decisions C. Pfurtscheller & E. Genovese https://doi.org/10.1016/j.cstp.2019.05.003
45. An alternative rock mass classification system for rock slopes L. Pantelidis https://doi.org/10.1007/s10064-009-0241-y
46. Satellite stereoscopic pair images of very high resolution: a step forward for the development of landslide inventories F. Murillo-García et al. https://doi.org/10.1007/s10346-014-0473-1
47. Regional assessment of landslide impact in the Three Gorges area, China, using ASTER data: Wushan-Zigui I. Fourniadis et al. https://doi.org/10.1007/s10346-007-0080-5
48. National-scale assessment of railways exposure to rapid flow-like landslides I. Marchesini et al. https://doi.org/10.1016/j.enggeo.2024.107474
49. SUGARFuseNet: Diffusion‑driven domain adaptation and bimodal bitemporal fusion for advancing global landslide segmentation on novel GBMT‑SLID dataset G. Emani et al. https://doi.org/10.1016/j.neucom.2026.134060
50. History of landslide susceptibility and a chorology of landslide-prone areas in the Western Ghats of Kerala, India S. Kuriakose et al. https://doi.org/10.1007/s00254-008-1431-9
51. InSAR-Based Active Landslide Detection and Characterization Along the Upper Reaches of the Yellow River J. Du et al. https://doi.org/10.1109/JSTARS.2023.3263003
52. Landslides triggered by an extraordinary rainfall event in Central Italy on September 15, 2022 M. Donnini et al. https://doi.org/10.1007/s10346-023-02109-4
53. Long-term analysis of rainfall-induced landslides in Umbria, central Italy S. Gariano et al. https://doi.org/10.1007/s11069-021-04539-6
54. Assessing damage data availability in national landslide databases for SFDRR reporting: a case study of Kuala Lumpur as a local-level application T. Bhuiyan et al. https://doi.org/10.1007/s10346-023-02085-9
55. Rainfall Thresholds for Prediction of Landslides in Idukki, India: An Empirical Approach M. Abraham et al. https://doi.org/10.3390/w11102113
56. An examination of controls on debris flow mobility: Evidence from coastal British Columbia R. Guthrie et al. https://doi.org/10.1016/j.geomorph.2009.09.021
57. Anthropic Valorisation of Vulnerable Areas Affected by Deep-Seated Landslides P. Cocean et al. https://doi.org/10.1007/s12371-019-00397-8
58. Capturing rainfall persistence in assessing rainfall induced landslide susceptibility using extreme value analysis A. Shreekant & B. Dodamani https://doi.org/10.1016/j.pdisas.2026.100676
59. Landslide Recognition by Deep Convolutional Neural Network and Change Detection W. Shi et al. https://doi.org/10.1109/TGRS.2020.3015826
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61. The effects of snowmelt on loess landslides in Tian Shan, China Y. Xian et al. https://doi.org/10.1016/j.ejrh.2025.102995
62. Newspaper reporting of the April 2007 eruption of Piton de la Fournaise part 1: useful information or tabloid sensationalism? A. Harris & N. Villeneuve https://doi.org/10.1186/s13617-018-0073-1
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65. Tree-ring reconstruction of reactivation phases of the Schimbrig landslide (Swiss Alps) J. Lopez-Saez et al. https://doi.org/10.4000/geomorphologie.11825
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67. Analysis of a landslide multi-date inventory in a complex mountain landscape: the Ubaye valley case study R. Schlögel et al. https://doi.org/10.5194/nhess-15-2369-2015