106 citations as recorded by crossref.

1. QDC-2D: A Semi-Automatic Tool for 2D Analysis of Discontinuities for Rock Mass Characterization L. Loiotine et al. https://doi.org/10.3390/rs13245086
2. Effect of the Normalized Difference Vegetation Index (NDVI) on GIS-Enabled Bivariate and Multivariate Statistical Models for Landslide Susceptibility Mapping K. Niraj et al. https://doi.org/10.1007/s12524-023-01738-5
3. World-wide InSAR sensitivity index for landslide deformation tracking A. van Natijne et al. https://doi.org/10.1016/j.jag.2022.102829
4. UAV Application for Short-Time Evolution Detection of the Vomice Landslide (South Italy) M. Mercuri et al. https://doi.org/10.3390/geosciences13020029
5. Subsidence mapping at regional scale using persistent scatters interferometry (PSI): The case of Tuscany region (Italy) A. Rosi et al. https://doi.org/10.1016/j.jag.2016.07.003
6. Understanding of landslide risk through learning by doing: case study of Koroška Bela community, Slovenia M. Jemec Auflič et al. https://doi.org/10.1007/s10346-018-1110-1
7. Comparison between U-shaped structural deep learning models to detect landslide traces K. Dang et al. https://doi.org/10.1016/j.scitotenv.2023.169113
8. Optimization of UAV Flight Missions in Steep Terrain K. Kozmus Trajkovski et al. https://doi.org/10.3390/rs12081293
9. Evaluating the Impact of Seismic Activity on the Slope Stability of the Western Coast of Lefkada Island Using Remote Sensing Techniques, Geographical Information Systems, and Field Data K. Nikolakopoulos et al. https://doi.org/10.3390/app13169434
10. Landslide mapping from aerial photographs using change detection-based Markov random field Z. Li et al. https://doi.org/10.1016/j.rse.2016.10.008
11. Integration of Remote Sensing Techniques for Intensity Zonation within a Landslide Area: A Case Study in the Northern Apennines, Italy V. Tofani et al. https://doi.org/10.3390/rs6020907
12. A multi-hazard map-based flooding, gully erosion, forest fires, and earthquakes in Iran S. Pouyan et al. https://doi.org/10.1038/s41598-021-94266-6
13. Integrated Methodology for Potential Landslide Identification in Highly Vegetation-Covered Areas L. Yan et al. https://doi.org/10.3390/rs15061518
14. Review of Satellite Interferometry for Landslide Detection in Italy L. Solari et al. https://doi.org/10.3390/rs12081351
15. Detecting and monitoring of landslides using persistent scattering synthetic aperture radar interferometry K. Shirani & M. Pasandi https://doi.org/10.1007/s12665-018-8042-x
16. Object‐based classification of terrestrial laser scanning point clouds for landslide monitoring A. Mayr et al. https://doi.org/10.1111/phor.12215
17. A review of the recent literature on rainfall thresholds for landslide occurrence S. Segoni et al. https://doi.org/10.1007/s10346-018-0966-4
18. Landslide susceptibility assessment incorporating sample optimization: A case study of Liujiaxia Reservoir area X. Liu et al. https://doi.org/10.1016/j.rsase.2026.102173
19. Shalstab mathematical model and WorldView-2 satellite images to identification of landslide-susceptible areas T. König et al. https://doi.org/10.1007/s11069-019-03691-4
20. Transfer learning-based deep learning models for flood and erosion detection in coastal area of Algeria Y. Hasnaoui et al. https://doi.org/10.1007/s12145-025-01866-1
21. Analysis about technology requirements for Development of Disaster Detecting Satellite Sensor H. Woo et al. https://doi.org/10.13067/JKIECS.2015.10.11.1205
22. Physically Based Susceptibility Assessment of Rainfall-Induced Shallow Landslides Using a Fuzzy Point Estimate Method H. Park et al. https://doi.org/10.3390/rs9050487
23. Integration of satellite SAR and optical acquisitions for the characterization of the Lake Sarez landslides in Tajikistan O. Nardini et al. https://doi.org/10.1007/s10346-024-02214-y
24. Integrated geospatial, rainfall threshold and physical based modelling for landslides in parts of upper bhagirathi basin, Uttarakhand P. Mohan et al. https://doi.org/10.1016/j.qsa.2024.100172
25. Combined use of statistical and DInSAR data analyses to define the state of activity of slow-moving landslides M. Calvello et al. https://doi.org/10.1007/s10346-016-0722-6
26. Integration of persistent scatterer interferometry and ground data for landslide monitoring: the Pianello landslide (Bovino, Southern Italy) A. Refice et al. https://doi.org/10.1007/s10346-018-01124-0
27. Landslides triggered by the 1970 Ms 7.7 Tonghai earthquake in Yunnan, China: an inventory, distribution characteristics, and tectonic significance Y. Cui et al. https://doi.org/10.1007/s11629-022-7321-x
28. Operative Monographies: Development of a New Tool for the Effective Management of Landslide Risks D. Giordan et al. https://doi.org/10.3390/geosciences8120485
29. HIRESSS: a physically based slope stability simulator for HPC applications G. Rossi et al. https://doi.org/10.5194/nhess-13-151-2013
30. Fault motion reversals predating the M w 6.3 2009 L'Aquila earthquake: insights from synthetic aperture radar data S. Mazzoli et al. https://doi.org/10.1144/jgs2020-016
31. Susceptibility of slopes to earthquake-induced landslides: a new index derived from helicopter-borne electromagnetic resistivity and digital elevation data sets A. Nonomura & S. Hasegawa https://doi.org/10.1007/s10346-017-0873-0
32. Earthquake-Induced Landslide Mapping for the 2018 Hokkaido Eastern Iburi Earthquake Using PALSAR-2 Data Y. Aimaiti et al. https://doi.org/10.3390/rs11202351
33. A Sentinel-1-based clustering analysis for geo-hazards mitigation at regional scale: a case study in Central Italy R. Montalti et al. https://doi.org/10.1080/19475705.2019.1690058
34. Quantitative Land-Use and Landslide Assessment: A Case Study in Rize, Türkiye N. Kasahara et al. https://doi.org/10.3390/w14111811
35. Geoscientists in the Sky: Unmanned Aerial Vehicles Responding to Geohazards R. Antoine et al. https://doi.org/10.1007/s10712-020-09611-7
36. The Use of TERRA-ASTER Satellite for Landslide Detection F. Vecchiotti et al. https://doi.org/10.3390/geosciences11060258
37. Databases in geohazard science: An introduction M. Klose et al. https://doi.org/10.1016/j.geomorph.2015.06.029
38. Landslide Susceptibility Assessment Using Frequency Ratio Technique with Iterative Random Sampling H. Oh et al. https://doi.org/10.1155/2017/3730913
39. Application of UAV and GB-SAR in Mechanism Research and Monitoring of Zhonghaicun Landslide in Southwest China B. Liu et al. https://doi.org/10.3390/rs13091653
40. Landslide prediction, monitoring and early warning: a concise review of state-of-the-art B. Chae et al. https://doi.org/10.1007/s12303-017-0034-4
41. Multi-year, three-dimensional landslide surface deformation from repeat lidar and response to precipitation:  Mill Gulch earthflow, California A. Booth et al. https://doi.org/10.1007/s10346-020-01364-z
42. Experiences from site-specific landslide early warning systems C. Michoud et al. https://doi.org/10.5194/nhess-13-2659-2013
43. Deep learning models integrating multi-sensor and -temporal remote sensing to monitor landslide traces in Vietnam K. Dang et al. https://doi.org/10.1016/j.ijdrr.2024.104391
44. Landslide observation and volume estimation in central Georgia based on L-band InSAR E. Nikolaeva et al. https://doi.org/10.5194/nhess-14-675-2014
45. Landslide Susceptibility Mapping Using Feature Fusion-Based CPCNN-ML in Lantau Island, Hong Kong Y. Chen et al. https://doi.org/10.1109/JSTARS.2021.3066378
46. Prediction of the location of future rupture surfaces of a slowly moving loess landslide by electrical resistivity tomography S. Szalai et al. https://doi.org/10.1111/1365-2478.12421
47. Integrated approach for landslide characterization in Northern Tunisia using electric resistivity tomography, geotechnical analysis and GIS tools I. Hamdi Nasr et al. https://doi.org/10.1080/10106049.2025.2596973
48. Use of multi-source remote sensing images to describe the sudden Shanshucao landslide in the Three Gorges Reservoir, China H. Huang et al. https://doi.org/10.1007/s10064-018-1261-2
49. Characterisation of a landslide by its fracture system using Electric Resistivity Tomography and Pressure Probe methods K. Szokoli et al. https://doi.org/10.1007/s40328-017-0199-3
50. Effective and Accelerated Forewarning of Landslides Using Wireless Sensor Networks and Machine Learning T. Hemalatha et al. https://doi.org/10.1109/JSEN.2019.2928358
51. Multitemporal UAV surveys for landslide mapping and characterization G. Rossi et al. https://doi.org/10.1007/s10346-018-0978-0
52. Web data mining for automatic inventory of geohazards at national scale A. Battistini et al. https://doi.org/10.1016/j.apgeog.2013.06.012
53. Delineation of landslide endangered areas and mapping their fracture systems by the pressure probe method S. Szalai et al. https://doi.org/10.1007/s10346-014-0509-6
54. Integrated use of GIS and remote sensing for monitoring landslides in transportation pavements: the case study of Paphos area in Cyprus D. Alexakis et al. https://doi.org/10.1007/s11069-013-0770-3
55. An integrated framework for wide-area active landslide detection with InSAR observations and SAR pixel offsets C. Zhang et al. https://doi.org/10.1007/s10346-022-01954-z
56. Multi-Sensor Satellite Analysis for Landslide Characterization: A Case of Study from Baipaza, Tajikistan F. Poggi et al. https://doi.org/10.3390/rs17122003
57. Geometric and kinematic characterization of landslides affecting urban areas: the Lungro case study (Calabria, Southern Italy) G. Gullà et al. https://doi.org/10.1007/s10346-015-0676-0
58. Slope stability evolution of a deep‐seated landslide considering a constantly deforming topography J. Pfeiffer et al. https://doi.org/10.1002/esp.5527
59. An assessment of Dungale landslide using remotely piloted aircraft system (RPAS), ground penetration radar (GPR), and Slide & RS2 Softwares R. Tandon et al. https://doi.org/10.1007/s11069-022-05334-7
60. TSM—Tracing Surface Motion: A Generic Toolbox for Analyzing Ground-Based Image Time Series of Slope Deformation M. Desrues et al. https://doi.org/10.3390/rs11192189
61. Multi-scale framework for landslide evolution K. Fang et al. https://doi.org/10.1016/j.jrmge.2026.09.001
62. Validation of landslide hazard models using a semantic engine on online news A. Battistini et al. https://doi.org/10.1016/j.apgeog.2017.03.003
63. Adapting sudden landslide identification product (SLIP) and detecting real-time increased precipitation (DRIP) algorithms to map rainfall-triggered landslides in Western Cameroon highlands (Central-Africa) A. Ngandam Mfondoum et al. https://doi.org/10.1186/s40677-021-00189-9
64. Remote Sensing for Assessing Landslides and Associated Hazards C. Lissak et al. https://doi.org/10.1007/s10712-020-09609-1
65. A study on the monitoring of landslide deformation disasters in Wenxian County, Longnan City based on different time-series InSAR techniques J. Zhang et al. https://doi.org/10.1007/s11069-024-06663-5
66. Landslide hazard assessment: recent trends and techniques S. Pardeshi et al. https://doi.org/10.1186/2193-1801-2-523
67. Over 100,000 landslides triggered by typhoon-induced rainfall in North China in July 2023 C. Xie et al. https://doi.org/10.1007/s10346-026-02698-w
68. Using lightweight method to detect landslide from satellite imagery J. Dai et al. https://doi.org/10.1016/j.jag.2024.104303
69. Spaceborne, UAV and ground-based remote sensing techniques for landslide mapping, monitoring and early warning N. Casagli et al. https://doi.org/10.1186/s40677-017-0073-1
70. A photographic method to identify reservoir geohazards induced by rock mass deterioration of hydro-fluctuation belt Z. Dai et al. https://doi.org/10.3389/feart.2024.1365272
71. Landslide hazard assessment in parts of upper Bhagirathi Basin: a comparative study using earth observation and machine learning based initiatives in perspective of slope instability P. Mohan et al. https://doi.org/10.1007/s10064-025-04544-0
72. Spatial Analysis of Agricultural Land Damage Caused by the July 2025 Extreme Rainfall in the Sindeungcheon Basin, South Korea K. Cho et al. https://doi.org/10.22761/GD.2025.0054
73. Combining Spatial Models for Shallow Landslides and Debris-Flows Prediction R. Gomes et al. https://doi.org/10.3390/rs5052219
74. The contribution of PSInSAR interferometry to landslide hazard in weak rock-dominated areas S. Oliveira et al. https://doi.org/10.1007/s10346-014-0522-9
75. Persistent Scatterer Interferometry (PSI) Technique for Landslide Characterization and Monitoring V. Tofani et al. https://doi.org/10.3390/rs5031045
76. Assessment of landslide-induced damage to structures: the Agnone landslide case study (southern Italy) M. Del Soldato et al. https://doi.org/10.1007/s10064-018-1303-9
77. Geomorphic indexing of landslide dams evolution C. Tacconi Stefanelli et al. https://doi.org/10.1016/j.enggeo.2016.04.024
78. Landslide Hazards Identification and Evaluation along the Vakhsh River in Tajikistan based on InSAR Time Series and the MassMov2D Model Y. SUN et al. https://doi.org/10.1111/1755-6724.15350
79. Post-failure evolution analysis of a rainfall-triggered landslide by multi-temporal interferometry SAR approaches integrated with geotechnical analysis P. Confuorto et al. https://doi.org/10.1016/j.rse.2016.11.002
80. Comparison of Remote Sensing Techniques for Geostructural Analysis and Cliff Monitoring in Coastal Areas of High Tourist Attraction: The Case Study of Polignano a Mare (Southern Italy) L. Loiotine et al. https://doi.org/10.3390/rs13245045
81. Removing InSAR Topography-Dependent Atmospheric Effect Based on Deep Learning C. Chen et al. https://doi.org/10.3390/rs14174171
82. Unmanned aerial vehicle based remote sensing method for monitoring a steep mountainous slope in the Three Gorges Reservoir, China H. Huang et al. https://doi.org/10.1007/s12145-017-0291-9
83. Monitoring of geohazards using differential interferometric satellite aperture radar in Australia B. Teodosio et al. https://doi.org/10.1080/01431161.2022.2106457
84. Review of Landslide Monitoring Techniques With IoT Integration Opportunities H. Thirugnanam et al. https://doi.org/10.1109/JSTARS.2022.3183684
85. Landslide monitoring techniques in the Geological Surveys of Europe M. Auflič et al. https://doi.org/10.1007/s10346-022-02007-1
86. Application and reliability of techniques for landslide site investigation, monitoring and early warning – outcomes from a questionnaire study I. Baroň & R. Supper https://doi.org/10.5194/nhess-13-3157-2013
87. Airborne geophysical mapping as an innovative methodology for landslide investigation: evaluation of results from the Gschliefgraben landslide, Austria R. Supper et al. https://doi.org/10.5194/nhess-13-3313-2013
88. Review of glacier velocity and facies characterization techniques using multi-sensor approach A. Mohanty et al. https://doi.org/10.1007/s10668-024-04604-7
89. Transpiration-Driven Electrokinetic Power Generator for Early Warning and Forecast of Geological Seepage P. Wen et al. https://doi.org/10.1021/acsaelm.2c01747
90. Landslide Hazard Analysis using Landsat-8 OLI and AHP Technique in Tanjung Bungah, Penang N. Saad et al. https://doi.org/10.1088/1755-1315/767/1/012023
91. LADI: Landslide displacement interpolation through a spatial-temporal Kalman filter A. Senogles et al. https://doi.org/10.1016/j.cageo.2023.105451
92. Landslide detection, monitoring and prediction with remote-sensing techniques N. Casagli et al. https://doi.org/10.1038/s43017-022-00373-x
93. Research on Early Warning Technology for Highway Geological Disasters Induced by Precipitation Conditions in Changbai Mountains R. Song et al. https://doi.org/10.62517/jcte.202406206
94. IntelliSense Bio-Ionotronics Battery for Early Warning of Geological Seepage J. Zhu et al. https://doi.org/10.1021/acssensors.3c00579
95. Accuracy Analysis of a New Data Processing Method for Landslide Monitoring Based on Unmanned Aerial System Photogrammetry I. Jakopec et al. https://doi.org/10.3390/s23063097
96. Airborne geophysical survey of the catastrophic landslide at Stože, Log pod Mangrtom, as a test of an innovative approach for landslide mapping in steep alpine terrains I. Baroň et al. https://doi.org/10.5194/nhess-13-2543-2013
97. Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives M. Scaioni et al. https://doi.org/10.3390/rs6109600
98. Rapid landslide mapping during the 2023 Emilia-Romagna disaster: assessing automated approaches with limited training data N. Dal Seno et al. https://doi.org/10.5194/nhess-26-4101-2026
99. Risk analysis for the Ancona landslide—I: characterization of landslide kinematics M. Uzielli et al. https://doi.org/10.1007/s10346-014-0474-0
100. Extraction of road blockage information for the Jiuzhaigou earthquake based on a convolution neural network and very-high-resolution satellite images B. Yang et al. https://doi.org/10.1007/s12145-019-00413-z
101. Image and data fusion in remote sensing of urban areas: status issues and research trends P. Gamba https://doi.org/10.1080/19479832.2013.848477
102. Landslide deformation monitoring with ALOS/PALSAR imagery: A D-InSAR geomorphological interpretation method R. Schlögel et al. https://doi.org/10.1016/j.geomorph.2014.11.031
103. Rapid landslide detection from free optical satellite imagery using a robust change detection technique R. Coluzzi et al. https://doi.org/10.1038/s41598-025-89542-8
104. The combination of DInSAR and facility damage data for the updating of slow-moving landslide inventory maps at medium scale L. Cascini et al. https://doi.org/10.5194/nhess-13-1527-2013
105. On the Use of Interferometric Synthetic Aperture Radar Data for Monitoring and Forecasting Natural Hazards M. Bernardi et al. https://doi.org/10.1007/s11004-021-09948-8
106. Landslides on dry badlands: UAV images to identify the drivers controlling their unexpected occurrence on vegetated hillslopes E. Rodriguez-Caballero et al. https://doi.org/10.1016/j.jaridenv.2020.104434