49 citations as recorded by crossref.

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7. A hybrid model to overcome landslide inventory incompleteness issue for landslide susceptibility prediction J. Tan et al. 10.1080/10106049.2024.2322066
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13. Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives M. Scaioni et al. 10.3390/rs6109600
14. Landslide Detection Mapping Employing CNN, ResNet, and DenseNet in the Three Gorges Reservoir, China T. Liu et al. 10.1109/JSTARS.2021.3117975
15. Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management D. Giordan et al. 10.5194/nhess-18-1079-2018
16. Inventory of landslides triggered by an extreme rainfall event in Marche-Umbria, Italy, on 15 September 2022 M. Santangelo et al. 10.1038/s41597-023-02336-3
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18. A Deep-Learning-Based Algorithm for Landslide Detection over Wide Areas Using InSAR Images Considering Topographic Features N. Li et al. 10.3390/s24144583
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20. Recognition of large scale deep-seated landslides in forest areas of Taiwan using high resolution topography C. Lin et al. 10.1016/j.jseaes.2012.10.022
21. Data Fusion Technique Using Wavelet Transform and Taguchi Methods for Automatic Landslide Detection From Airborne Laser Scanning Data and QuickBird Satellite Imagery B. Pradhan et al. 10.1109/TGRS.2015.2484325
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23. Évaluation de l’aléa glissements de terrain : état de l’art et perspectives pour la cartographie réglementaire en France Y. Thiery & M. Terrier 10.1051/geotech/2019003
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26. Seasonal landslide mapping and estimation of landslide mobilization rates using aerial and satellite images F. Fiorucci et al. 10.1016/j.geomorph.2011.01.013
27. Improvement of landslide hazard assessments for regulatory zoning in France: STATE–OF–THE-ART perspectives and considerations Y. Thiery et al. 10.1016/j.ijdrr.2020.101562
28. Landslide-prone area retrieval and earthquake-inducing hazard probability assessment based on InSAR analysis L. Zou et al. 10.1007/s10346-023-02079-7
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32. Identification and Analysis of the Geohazards Located in an Alpine Valley Based on Multi-Source Remote Sensing Data Y. Yang et al. 10.3390/s24134057
33. Developmental characteristics of rainfall-induced landslides from 1999 to 2016 in Wenzhou City of China H. Qin et al. 10.3389/feart.2022.1005199
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37. Landslide inventory map of the upper Sinni River valley, Southern Italy M. Santangelo et al. 10.1080/17445647.2014.949313
38. Applications of Terrestrial Laser Scanning in Geomorphology Y. HAYAKAWA & T. OGUCHI 10.5026/jgeography.125.299
39. Evaluating survey instruments and methods in a steep channel D. Scott et al. 10.1016/j.geomorph.2016.08.020
40. Spatial prediction of landslide-susceptible zones in El-Qaá area, Egypt, using an integrated approach based on GIS statistical analysis S. Abuzied & H. Alrefaee 10.1007/s10064-018-1302-x
41. r.survey: a tool for calculating visibility of variable-size objects based on orientation T. Bornaetxea & I. Marchesini 10.1080/13658816.2021.1942476
42. Impact of event landslides on road networks: a statistical analysis of two Italian case studies M. Donnini et al. 10.1007/s10346-017-0829-4
43. Criteria for the optimal selection of remote sensing optical images to map event landslides F. Fiorucci et al. 10.5194/nhess-18-405-2018
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46. Geohazard Recognition and Inventory Mapping Using Airborne LiDAR Data in Complex Mountainous Areas C. Guo et al. 10.1007/s12583-021-1467-2
47. Preface: Landslide–transport network interactions F. Taylor et al. 10.5194/nhess-20-2585-2020
48. Effectiveness of visually analyzing LiDAR DTM derivatives for earth and debris slide inventory mapping for statistical susceptibility modeling H. Petschko et al. 10.1007/s10346-015-0622-1
49. The Use of High-Resolution Remote Sensing Data in Preparation of Input Data for Large-Scale Landslide Hazard Assessments M. Sinčić et al. 10.3390/land11081360