56 citations as recorded by crossref.

1. Interplay between mass movement and fluvial network organization: An example from southern Apennines, Italy M. Santangelo et al.
2. Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data S. Plank et al.
3. Detailed inventory and initial analysis of landslides triggered by extreme rainfall in the northern Huaiji County, Guangdong Province, China, from June 6 to 9, 2020 C. Xie et al.
4. Landslide Detection Using Residual Networks and the Fusion of Spectral and Topographic Information M. Sameen & B. Pradhan
5. Landslide Mapping and Characterization through Infrared Thermography (IRT): Suggestions for a Methodological Approach from Some Case Studies W. Frodella et al.
6. Web data mining for automatic inventory of geohazards at national scale A. Battistini et al.
7. A hybrid model to overcome landslide inventory incompleteness issue for landslide susceptibility prediction J. Tan et al.
8. Mapping of shallow landslides with object-based image analysis from unmanned aerial vehicle data R. Comert et al.
9. Landslide inventory and distribution patterns in Lhasa area, Tibet Plateau S. Ma et al.
10. Exploring a landslide inventory created by automated web data mining: the case of Italy R. Franceschini et al.
11. The research on landslide detection in remote sensing images based on improved DeepLabv3+ method Y. Li
12. Semi-automatic recognition and mapping of rainfall induced shallow landslides using optical satellite images A. Mondini et al.
13. Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives M. Scaioni et al.
14. Comprehensive analysis and assessment of extreme rainfall-induced clustered landslides: a case study of southern Qingyuan city, Guangdong province, China, in June 2020 C. Xie et al.
15. Spatial distribution and susceptibility mapping of landslides in the Rudraprayag to Badrinath Region, North Western Himalayas K. Sarkar et al.
16. Landslide Detection Mapping Employing CNN, ResNet, and DenseNet in the Three Gorges Reservoir, China T. Liu et al.
17. Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management D. Giordan et al.
18. Inventory of landslides triggered by an extreme rainfall event in Marche-Umbria, Italy, on 15 September 2022 M. Santangelo et al.
19. Inventory of shallow landslides triggered by extreme precipitation in July 2023 in Beijing, China H. Ma & F. Wang
20. A Deep-Learning-Based Algorithm for Landslide Detection over Wide Areas Using InSAR Images Considering Topographic Features N. Li et al.
21. Factors controlling the formation and movement of clustered shallow landslides triggered by the extreme rainstorm in July 2023 in Beijing, China H. Ma & F. Wang
22. Recognition of large scale deep-seated landslides in forest areas of Taiwan using high resolution topography C. Lin et al.
23. 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.
24. Generating an optimal DTM from airborne laser scanning data for landslide mapping in a tropical forest environment K. Razak et al.
25. Évaluation de l’aléa glissements de terrain : état de l’art et perspectives pour la cartographie réglementaire en France Y. Thiery & M. Terrier
26. AI-Based Susceptibility Analysis of Shallow Landslides Induced by Heavy Rainfall in Tianshui, China T. Qi et al.
27. Rapid onset hazards, fault-controlled landslides and multi-method emergency decision-making F. Guo et al.
28. Seasonal landslide mapping and estimation of landslide mobilization rates using aerial and satellite images F. Fiorucci et al.
29. Improvement of landslide hazard assessments for regulatory zoning in France: STATE–OF–THE-ART perspectives and considerations Y. Thiery et al.
30. Landslide-prone area retrieval and earthquake-inducing hazard probability assessment based on InSAR analysis L. Zou et al.
31. Automatic identification of active landslides over wide areas from time-series InSAR measurements using Faster RCNN J. Cai et al.
32. Landslide mapping with remote sensing: challenges and opportunities C. Zhong et al.
33. An approach to reduce mapping errors in the production of landslide inventory maps M. Santangelo et al.
34. Landslide Traces Inventory and Spatial Distribution Analysis Along the Hubei Section of the Jinsha River–Hubei Ultra-High-Voltage Transmission Line, China W. Yang et al.
35. Remote Sensing Identification of Benggang Using a Two-Stream Network with Multimodal Feature Enhancement and Sparse Attention X. Rao et al.
36. Identification and Analysis of the Geohazards Located in an Alpine Valley Based on Multi-Source Remote Sensing Data Y. Yang et al.
37. Developmental characteristics of rainfall-induced landslides from 1999 to 2016 in Wenzhou City of China H. Qin et al.
38. A Multi-Channel Convolutional Neural Network Model for Detecting Active Landslides Using Multi-Source Fusion Images J. Wang et al.
39. Integrating Expert Knowledge with Statistical Analysis for Landslide Susceptibility Assessment at Regional Scale C. Chalkias et al.
40. Exploring event landslide mapping using Sentinel-1 SAR backscatter products M. Santangelo et al.
41. Detection and analysis of landslide geomorphology based on UAV vertical photogrammetry R. Bi et al.
42. Landslide inventory map of the upper Sinni River valley, Southern Italy M. Santangelo et al.
43. Mapping forest-covered landslides using Geographic Object-Based Image Analysis (GEOBIA), Jena region, Germany I. Zangana et al.
44. Applications of Terrestrial Laser Scanning in Geomorphology Y. HAYAKAWA & T. OGUCHI
45. A high-precision catalogue of landslide events in China based on news text mining with large language model B. Zhao et al.
46. Evaluating survey instruments and methods in a steep channel D. Scott et al.
47. Spatial prediction of landslide-susceptible zones in El-Qaá area, Egypt, using an integrated approach based on GIS statistical analysis S. Abuzied & H. Alrefaee
48. r.survey: a tool for calculating visibility of variable-size objects based on orientation T. Bornaetxea & I. Marchesini
49. Impact of event landslides on road networks: a statistical analysis of two Italian case studies M. Donnini et al.
50. Criteria for the optimal selection of remote sensing optical images to map event landslides F. Fiorucci et al.
51. Pixel-based classification method for earthquake-induced landslide mapping using remotely sensed imagery, geospatial data and temporal change information A. Asadi et al.
52. Landslide inventory maps: New tools for an old problem F. Guzzetti et al.
53. Geohazard Recognition and Inventory Mapping Using Airborne LiDAR Data in Complex Mountainous Areas C. Guo et al.
54. Preface: Landslide–transport network interactions F. Taylor et al.
55. Effectiveness of visually analyzing LiDAR DTM derivatives for earth and debris slide inventory mapping for statistical susceptibility modeling H. Petschko et al.
56. The Use of High-Resolution Remote Sensing Data in Preparation of Input Data for Large-Scale Landslide Hazard Assessments M. Sinčić et al.