100 citations as recorded by crossref.

1. Coseismic Debris Remains in the Orogen Despite a Decade of Enhanced Landsliding L. Dai et al. https://doi.org/10.1029/2021GL095850
2. Landslide Distribution and Development Characteristics in the Beiluo River Basin F. Liu et al. https://doi.org/10.3390/land13071038
3. A globally distributed dataset of coseismic landslide mapping via multi-source high-resolution remote sensing images C. Fang et al. https://doi.org/10.5194/essd-16-4817-2024
4. Landslide shape, ellipticity and length‐to‐width ratios F. Taylor et al. https://doi.org/10.1002/esp.4479
5. Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes J. Williams et al. https://doi.org/10.5194/nhess-18-185-2018
6. Landslides and fluvial response to landsliding induced by the 1933 Diexi earthquake, Minjiang River, eastern Tibetan Plateau L. Dai et al. https://doi.org/10.1007/s10346-021-01717-2
7. Preservation and transportation of large landslide deposits under decadal and millennial timescales in the Taiwan orogenic belt C. Chen et al. https://doi.org/10.1016/j.geomorph.2022.108402
8. The size, distribution, and mobility of landslides caused by the 2015 Mw7.8 Gorkha earthquake, Nepal K. Roback et al. https://doi.org/10.1016/j.geomorph.2017.01.030
9. Characteristics of landslide path dependency revealed through multiple resolution landslide inventories in the Nepal Himalaya S. Roberts et al. https://doi.org/10.1016/j.geomorph.2021.107868
10. Inventory, Distribution and Geometric Characteristics of Landslides in Baoshan City, Yunnan Province, China X. Shao et al. https://doi.org/10.3390/su12062433
11. Storm-triggered landslides in the Peruvian Andes and implications for topography, carbon cycles, and biodiversity K. Clark et al. https://doi.org/10.5194/esurf-4-47-2016
12. Spatial assessment of sediment production in a badland catchment using repeat LiDAR surveys, Draix, Alpes de Haute-Provence, France Y. Boukhari et al. https://doi.org/10.5194/esurf-13-1205-2025
13. Cumulative damage evolution rule of rock slope based on shaking table test using VMD-HT J. Chen et al. https://doi.org/10.1016/j.enggeo.2023.107003
14. Coseismic landslide mapping in the 2024 MW 7.0 Wushi earthquake using Multi-Source Satellite Data J. Tang et al. https://doi.org/10.1016/j.eqrea.2026.100454
15. An alternative to landslide volume-area scaling relationships: an ensemble approach adopting a difference model to estimate the total volume of landsliding triggered by the 2016 Kaikōura earthquake, New Zealand K. Jones et al. https://doi.org/10.1007/s10346-025-02479-x
16. Seismic and geological controls on earthquake-induced landslide size A. Valagussa et al. https://doi.org/10.1016/j.epsl.2018.11.005
17. Analysis of the fundamental differences between dam-forming landslides and all landslides H. Wu et al. https://doi.org/10.1016/j.geomorph.2025.109665
18. Landslide susceptibility modeling by interpretable neural network K. Youssef et al. https://doi.org/10.1038/s43247-023-00806-5
19. Beyond 2D landslide inventories and their rollover: synoptic 3D inventories and volume from repeat lidar data T. Bernard et al. https://doi.org/10.5194/esurf-9-1013-2021
20. Glacial geomorphological mapping: A review of approaches and frameworks for best practice B. Chandler et al. https://doi.org/10.1016/j.earscirev.2018.07.015
21. Semiautomated object-based classification of rain-induced landslides with VHR multispectral images on Madeira Island S. Heleno et al. https://doi.org/10.5194/nhess-16-1035-2016
22. A hybrid neural network and interpolation framework for volume estimation of submarine landslide scars C. Theden et al. https://doi.org/10.1016/j.geoai.2026.100097
23. Geomorphic and fluvial controls on the distribution and geometry of old landslides in the Nu River Basin, China S. Liu et al. https://doi.org/10.1016/j.geomorph.2026.110361
24. Multiscale Comparison of Regional Rainfall-Induced Landslide Predictive Models: The Example of Hurricane Maria in Puerto Rico M. Kassem et al. https://doi.org/10.1016/j.nhres.2026.03.008
25. Two multi-temporal datasets that track the enhanced landsliding after the 2008 Wenchuan earthquake X. Fan et al. https://doi.org/10.5194/essd-11-35-2019
26. Landslides triggered by the Gorkha earthquake in the Langtang valley, volumes and initiation processes P. Lacroix https://doi.org/10.1186/s40623-016-0423-3
27. A Network for Landslide Detection Using Large-Area Remote Sensing Images with Multiple Spatial Resolutions B. Yu et al. https://doi.org/10.3390/rs14225759
28. Residence Time of Over‐Steepened Rock Masses in an Active Mountain Range G. Li et al. https://doi.org/10.1029/2021GL097319
29. Machine learning techniques on spatio-temporal data for landslide susceptibility assessment at Dieng Mountainous Region, Banjarnegara district, Central Java, Indonesia Y. Susena et al. https://doi.org/10.1007/s11069-025-07136-z
30. Application of Supervised Machine Learning Technique on LiDAR Data for Monitoring Coastal Land Evolution M. Barbarella et al. https://doi.org/10.3390/rs13234782
31. Difference model quantification of coseismic landslide erosion and deposition to improve connectivity metrics after the 2016 Kaikōura earthquake K. Jones et al. https://doi.org/10.1016/j.geomorph.2026.110385
32. Presentation and Analysis of a Worldwide Database of Earthquake‐Induced Landslide Inventories H. Tanyaş et al. https://doi.org/10.1002/2017JF004236
33. Initial insights from a global database of rainfall-induced landslide inventories: the weak influence of slope and strong influence of total storm rainfall O. Marc et al. https://doi.org/10.5194/esurf-6-903-2018
34. Inventory of Vietri-Maiori landslides induced by the storm of October 1954 (southern Italy) F. Fiorillo et al. https://doi.org/10.1080/17445647.2019.1626777
35. Review of landslide inventories for Nepal between 2010 and 2021 reveals data gaps in global landslide hotspot E. Harvey et al. https://doi.org/10.1007/s11069-024-07013-1
36. Mechanistic insights from emergent landslides in physical experiments O. Beaulieu et al. https://doi.org/10.1130/G47875.1
37. Remote Sensing-Based Detection and Statistical Characterization of Large Landslides in the Transylvanian Basin G. Roșian et al. https://doi.org/10.3390/rs18162645
38. Texton-Based Ensemble Classification of Landslide Source and Transport Areas in VHR Imagery M. Silveira et al. https://doi.org/10.1109/LGRS.2016.2610003
39. Volume Estimation of Landslide Affected Soil Moisture Using TRIGRS: A Case Study of Longxi River Small Watershed in Wenchuan Earthquake Zone, China T. Sun et al. https://doi.org/10.3390/w13010071
40. Distribution and Morphometry of Thermocirques in the North of West Siberia, Russia M. Leibman et al. https://doi.org/10.3390/geosciences13060167
41. Role of landslides on the volume balance of the Nepal 2015 earthquake sequence A. Valagussa et al. https://doi.org/10.1038/s41598-021-83037-y
42. Coseismic Uplift of the 1999 Mw7.6 Chi‐Chi Earthquake and Implication to Topographic Change in Frontal Mountain Belts R. Chuang et al. https://doi.org/10.1029/2020GL088947
43. Automatic Extraction of Seismic Landslides in Large Areas with Complex Environments Based on Deep Learning: An Example of the 2018 Iburi Earthquake, Japan P. Zhang et al. https://doi.org/10.3390/rs12233992
44. Landslides triggered by multiple earthquakes: insights from the 2018 Lombok (Indonesia) events M. Ferrario https://doi.org/10.1007/s11069-019-03718-w
45. Exploiting earthquake-induced landslide inventories for macroseismic assessment using the environmental seismic intensity (ESI-07) scale E. Muccignato & M. Ferrario https://doi.org/10.3389/feart.2025.1468787
46. Learnings from rapid response efforts to remotely detect landslides triggered by the August 2021 Nippes earthquake and Tropical Storm Grace in Haiti P. Amatya et al. https://doi.org/10.1007/s11069-023-06096-6
47. Automated determination of landslide locations after large trigger events: advantages and disadvantages compared to manual mapping D. Milledge et al. https://doi.org/10.5194/nhess-22-481-2022
48. Enabling 3D landslide event statistics using satellite and UAV-enabled topographic differencing M. Clark et al. https://doi.org/10.1007/s10346-024-02374-x
49. Sensitivity analysis of automatic landslide mapping: numerical experiments towards the best solution K. Pawluszek et al. https://doi.org/10.1007/s10346-018-0986-0
50. A revised comprehensive inventory of landslides induced by the 2007 Aysén earthquake, Patagonia A. Serey et al. https://doi.org/10.1007/s10064-024-04057-2
51. Evaluating volume of coseismic landslide clusters by flow direction-based partitioning R. Fan et al. https://doi.org/10.1016/j.enggeo.2019.105238
52. Multi-event assessment of typhoon-triggered landslide susceptibility in the Philippines J. Jones et al. https://doi.org/10.5194/nhess-23-1095-2023
53. Characteristics and causes of natural and human-induced landslides in a tropical mountainous region: the rift flank west of Lake Kivu (Democratic Republic of the Congo) J. Maki Mateso et al. https://doi.org/10.5194/nhess-23-643-2023
54. Spatio-temporal evolution of mass wasting after the 2008 Mw 7.9 Wenchuan earthquake revealed by a detailed multi-temporal inventory X. Fan et al. https://doi.org/10.1007/s10346-018-1054-5
55. Noncontact detection of earthquake-induced landslides by an enhanced image binarization method incorporating with Monte-Carlo simulation Z. Han et al. https://doi.org/10.1080/19475705.2018.1520745
56. Quantifying Near‐Surface Rock Strength on a Regional Scale From Hillslope Stability Models K. Townsend et al. https://doi.org/10.1029/2020JF005665
57. Large landslides and deep-seated gravitational slope deformations in the Czech Flysch Carpathians: New LiDAR-based inventory T. Pánek et al. https://doi.org/10.1016/j.geomorph.2019.106852
58. Volume Characteristics of Landslides Triggered by the MW 7.8 2016 Kaikōura Earthquake, New Zealand, Derived From Digital Surface Difference Modeling C. Massey et al. https://doi.org/10.1029/2019JF005163
59. Landslide Processes Involved in Volcano Dismantling From Past to Present: The Remarkable Open‐Air Laboratory of the Cirque de Salazie (Reunion Island) C. Rault et al. https://doi.org/10.1029/2021JF006257
60. Landslide recognition and mapping in a mixed forest environment from airborne LiDAR data T. Görüm https://doi.org/10.1016/j.enggeo.2019.105155
61. Effective prediction of earthquake-induced slope displacements, considering region-specific seismotectonic and climatic conditions D. Djukem et al. https://doi.org/10.1007/s11069-025-07200-8
62. Landslides triggered by the 2015 Mw 6.0 Sabah (Malaysia) earthquake: inventory and ESI-07 intensity assignment M. Ferrario https://doi.org/10.5194/nhess-22-3527-2022
63. Landslide development within 3 years after the 2015 Mw 7.8 Gorkha earthquake, Nepal Y. Tian et al. https://doi.org/10.1007/s10346-020-01366-x
64. Decadal vegetation succession from MODIS reveals the spatio-temporal evolution of post-seismic landsliding after the 2008 Wenchuan earthquake A. Yunus et al. https://doi.org/10.1016/j.rse.2019.111476
65. The Fate of Sediment After a Large Earthquake O. Francis et al. https://doi.org/10.1029/2021JF006352
66. Rapid Mapping of Landslides Induced by Heavy Rainfall in the Emilia-Romagna (Italy) Region in May 2023 M. Ferrario & F. Livio https://doi.org/10.3390/rs16010122
67. Transient changes of landslide rates after earthquakes O. Marc et al. https://doi.org/10.1130/G36961.1
68. Toward an Automatic Pixel-Based Detection of Earthquake-Triggered Landslides in Arid Environments Using Optical Imagery L. Massa et al. https://doi.org/10.3390/geohazards7020066
69. Inventory, Distribution and Geometric Characteristics of Landslides in the Dongchuan District, Yunnan Province, China S. Liu et al. https://doi.org/10.3390/su18083994
70. The influence of frequency and duration of seismic ground motion on the size of triggered landslides—A regional view R. Jibson & H. Tanyaş https://doi.org/10.1016/j.enggeo.2020.105671
71. Constraining landslide timing in a data-scarce context: from recent to very old processes in the tropical environment of the North Tanganyika-Kivu Rift region O. Dewitte et al. https://doi.org/10.1007/s10346-020-01452-0
72. Landslide Geometry Reveals its Trigger K. Rana et al. https://doi.org/10.1029/2020GL090848
73. Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories R. Emberson et al. https://doi.org/10.5194/nhess-22-1129-2022
74. Connectivity of earthquake‐triggered landslides with the fluvial network: Implications for landslide sediment transport after the 2008 Wenchuan earthquake G. Li et al. https://doi.org/10.1002/2015JF003718
75. Identification of Gully-Type Debris Flow Shapes Based on Point Cloud Local Curvature Extrema R. Tan & B. Zhang https://doi.org/10.3390/w17091243
76. Combining remote sensing techniques and field surveys for post-earthquake reconnaissance missions G. Giardina et al. https://doi.org/10.1007/s10518-023-01716-9
77. Landslide Hazard and Exposure Modelling in Data‐Poor Regions: The Example of the Rohingya Refugee Camps in Bangladesh R. Emberson et al. https://doi.org/10.1029/2020EF001666
78. Capturing the complete landslide–debris-rich flood continuum for accurate inventory, susceptibility and exposure mapping – lessons from Cyclone Idai A. Dille et al. https://doi.org/10.5194/nhess-26-2561-2026
79. Prediction of the area affected by earthquake-induced landsliding based on seismological parameters O. Marc et al. https://doi.org/10.5194/nhess-17-1159-2017
80. How size and trigger matter: analyzing rainfall- and earthquake-triggered landslide inventories and their causal relation in the Koshi River basin, central Himalaya J. Zhang et al. https://doi.org/10.5194/nhess-19-1789-2019
81. Field techniques for measuring bedrock erosion and denudation J. Turowski & K. Cook https://doi.org/10.1002/esp.4007
82. Earthquake statistics changed by typhoon-driven erosion P. Steer et al. https://doi.org/10.1038/s41598-020-67865-y
83. 30-year record of Himalaya mass-wasting reveals landscape perturbations by extreme events J. Jones et al. https://doi.org/10.1038/s41467-021-26964-8
84. Landslide mobilization rates: A global analysis and model J. Broeckx et al. https://doi.org/10.1016/j.earscirev.2019.102972
85. Factors controlling landslide frequency–area distributions H. Tanyaş et al. https://doi.org/10.1002/esp.4543
86. Two-phase strategy for rapid and unbiased assessment of earthquake-induced landslides S. Xiao et al. https://doi.org/10.1016/j.enggeo.2024.107562
87. Size scaling of large landslides from incomplete inventories O. Korup et al. https://doi.org/10.5194/nhess-24-3815-2024
88. Long-term erosion of the Nepal Himalayas by bedrock landsliding: the role of monsoons, earthquakes and giant landslides O. Marc et al. https://doi.org/10.5194/esurf-7-107-2019
89. The hazard of large debris flows E. Harvey et al. https://doi.org/10.1126/sciadv.adz4625
90. Automated derivation and spatio-temporal analysis of landslide properties in southern Kyrgyzstan D. Golovko et al. https://doi.org/10.1007/s11069-016-2636-y
91. Simple rules to minimise exposure to coseismic landslide hazard D. Milledge et al. https://doi.org/10.5194/nhess-19-837-2019
92. The influence of study area selection and landslide inventory practices on landslides spatial distribution: an example from Northern Morocco A. Bounab et al. https://doi.org/10.1038/s41598-026-36587-y
93. An updated method for estimating landslide‐event magnitude H. Tanyaş et al. https://doi.org/10.1002/esp.4359
94. A seismologically consistent expression for the total area and volume of earthquake‐triggered landsliding O. Marc et al. https://doi.org/10.1002/2015JF003732
95. Comparison of Earthquake-Triggered Landslide Inventories: A Case Study of the 2015 Gorkha Earthquake, Nepal S. Meena & S. Tavakkoli Piralilou https://doi.org/10.3390/geosciences9100437
96. Oxidation of sulfides and rapid weathering in recent landslides R. Emberson et al. https://doi.org/10.5194/esurf-4-727-2016
97. 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
98. Use of Very High-Resolution Optical Data for Landslide Mapping and Susceptibility Analysis along the Karnali Highway, Nepal P. Amatya et al. https://doi.org/10.3390/rs11192284
99. Investigation of the Effect of the Dataset Size and Type in the Earthquake-Triggered Landslides Mapping: A Case Study for the 2018 Hokkaido Iburu Landslides R. Comert https://doi.org/10.3389/feart.2021.633665
100. Temporal Variations in Landslide Distributions Following Extreme Events: Implications for Landslide Susceptibility Modeling J. Jones et al. https://doi.org/10.1029/2021JF006067