112 citations as recorded by crossref.

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14. Geospatial modelling of drought patterns in Oman: GIS-based and machine learning approach S. Mansour 10.1007/s40808-024-01958-9
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24. Assessing landslide susceptibility using Bayesian probability-based weight of evidence model E. Sujatha et al. 10.1007/s10064-013-0537-9
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26. Landslide Susceptibility Assessment Tools v1.0.0b – Project Manager Suite: a new modular toolkit for landslide susceptibility assessment J. Torizin et al. 10.5194/gmd-15-2791-2022
27. Improving Soil Property Mapping Using Support Vector Machines, Neural Networks, Gradient Boosted Trees and Random Forests Over Soils in Sub-Saharan Africa G. Akande et al. 10.2139/ssrn.4093599
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29. Weights-of-evidence model applied to landslide susceptibility mapping in a tropical hilly area B. Pradhan et al. 10.1080/19475705.2010.498151
30. An artificial intelligence-based approach to predicting seismic hillslope stability under extreme rainfall events in the vicinity of Wolsong nuclear power plant, South Korea A. Pradhan & Y. Kim 10.1007/s10064-021-02138-0
31. Comparison and evaluation of landslide susceptibility maps obtained from weight of evidence, logistic regression, and artificial neural network models C. Polykretis & C. Chalkias 10.1007/s11069-018-3299-7
32. Slope unit-based distribution analysis of landslides triggered by the April 20, 2013, Ms 7.0 Lushan earthquake S. Zhou et al. 10.1007/s12517-015-1835-2
33. Experimental Study on Deformation and Failure Characteristics of Interbedded Anti-inclined Rock Slopes Induced by Rainfall B. Zhang et al. 10.1007/s00603-023-03633-4
34. Advanced integration of ensemble learning and MT-InSAR for enhanced slow-moving landslide susceptibility zoning T. Zeng et al. 10.1016/j.enggeo.2024.107436
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36. Manifestation of an advanced fuzzy logic model coupled with Geo-information techniques to landslide susceptibility mapping and their comparison with logistic regression modelling B. Pradhan 10.1007/s10651-010-0147-7
37. Detection of landslides using web-based aerial photographs and landslide susceptibility mapping using geospatial analysis S. Lee et al. 10.1080/01431161.2011.649862
38. Predicting landslide scenes under potential earthquake scenarios in the Xianshuihe fault zone, Southwest China Y. Zhang et al. 10.1007/s11629-017-4363-6
39. Landslide susceptibility assessment at Wadi Jawrah Basin, Jizan region, Saudi Arabia using two bivariate models in GIS A. Youssef et al. 10.1007/s12303-014-0065-z
40. Landslide detection and susceptibility mapping using LiDAR and an artificial neural network approach: a case study in the Cuyahoga Valley National Park, Ohio P. Gorsevski et al. 10.1007/s10346-015-0587-0
41. Assessment of deep catastrophic landslides susceptibility to earthquake N. TAKEZAWA et al. 10.13101/ijece.5.27
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45. Back analysis of landslide susceptibility zonation mapping for the 2005 Kashmir earthquake: an assessment of the reliability of susceptibility zoning maps U. Kamp et al. 10.1007/s11069-009-9451-7
46. Identification of concrete aggregates using K-means clustering and level set method L. Chen et al. 10.1016/j.istruc.2021.08.048
47. Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland K. Pawluszek & A. Borkowski 10.1007/s11069-016-2725-y
48. Statistical landslide susceptibility assessment in a dynamic environment: A case study for Lanzhou City, Gansu Province, NW China J. Torizin et al. 10.1007/s11629-017-4717-0
49. GIS based landslide susceptibility mapping of Tevankarai Ar sub-watershed, Kodaikkanal, India using binary logistic regression analysis S. Ramani et al. 10.1007/s11629-011-2157-9
50. Rainfall-based criteria for assessing slump rate of mountainous highway slopes: A case study of slopes along Highway 18 in Alishan, Taiwan S. Chang et al. 10.1016/j.enggeo.2011.01.001
51. Regional Rainfall-Induced Landslide Risk Assessment Using Susceptibility Mapping and Unexpected High-Intensity Rainfall M. Anees et al. 10.1051/bioconf/202413104020
52. Evaluation of prediction capability, robustness, and sensitivity in non-linear landslide susceptibility models, Guantánamo, Cuba C. Melchiorre et al. 10.1016/j.cageo.2010.10.004
53. Use of GIS-based fuzzy logic relations and its cross application to produce landslide susceptibility maps in three test areas in Malaysia B. Pradhan 10.1007/s12665-010-0705-1
54. Assessing spatial distribution of Coffea arabica L. in Ethiopia's highlands using species distribution models and geospatial analysis methods B. Hailu et al. 10.1016/j.ecoinf.2017.10.001
55. Medium-scale hazard mapping for shallow landslide initiation: the Buyukkoy catchment area (Cayeli, Rize, Turkey) H. Nefeslioglu et al. 10.1007/s10346-011-0267-7
56. OR models with stochastic components in disaster operations management: A literature survey M. Hoyos et al. 10.1016/j.cie.2014.11.025
57. Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea S. Lee et al. 10.1007/s10346-007-0088-x
58. Review of study on post-earthquake stability of soil slopes J. Chen et al. 10.1088/1755-1315/304/4/042007
59. Mechanism of Root Reinforcement Involved in Rainfall-Induced Shallow Landslide Mitigation: A Review D. Mahima et al. 10.1007/s40098-023-00836-y
60. Random Cross-Validation Produces Biased Assessment of Machine Learning Performance in Regional Landslide Susceptibility Prediction C. Kumar et al. 10.3390/rs17020213
61. Development of a statistics-based nowcasting model for earthquake-triggered landslides in Taiwan R. Chuang et al. 10.1016/j.enggeo.2021.106177
62. Selection of optimal pixel resolution for landslide susceptibility analysis within the Bukit Antarabangsa, Kuala Lumpur, by using image processing and multivariate statistical tools I. Quraishi et al. 10.1186/s13640-017-0169-2
63. Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area H. Oh & B. Pradhan 10.1016/j.cageo.2010.10.012
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65. Earthquake-induced landslides susceptibility assessment: A review of the state-of-the-art X. Shao & C. Xu 10.1016/j.nhres.2022.03.002
66. Landslide susceptibility mapping at Zonouz Plain, Iran using genetic programming and comparison with frequency ratio, logistic regression, and artificial neural network models V. Nourani et al. 10.1007/s11069-013-0932-3
67. A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape K. Were et al. 10.1016/j.ecolind.2014.12.028
68. Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria Y. Achour et al. 10.1007/s12517-017-2980-6
69. Prediction of landslides using ASTER imagery and data mining models K. Song et al. 10.1016/j.asr.2011.11.035
70. Settlements and slides: a large landslide case study from the Central Cordillera of the Philippines G. Hearn & J. Roy Hart 10.1144/qjegh2019-050
71. Coseismic Stability Assessment of a Damaged Underground Ammunition Storage Chamber Through Ambient Vibration Recordings and Numerical Modelling F. Glueer et al. 10.3389/feart.2021.773155
72. Landslide susceptibility maps using different probabilistic and bivariate statistical models and comparison of their performance at Wadi Itwad Basin, Asir Region, Saudi Arabia A. Youssef et al. 10.1007/s10064-015-0734-9
73. Landslide susceptibility mapping of Tevankarai Ar sub-watershed, Kodaikkanal taluk, India, using weighted similar choice fuzzy model E. Sujatha & V. Rajamanickam 10.1007/s11069-011-9763-2
74. GIS-based landslide susceptibility mapping with logistic regression, analytical hierarchy process, and combined fuzzy and support vector machine methods: a case study from Wolong Giant Panda Natural Reserve, China Q. Meng et al. 10.1007/s10064-015-0786-x
75. Cyclic Behaviour of Uniform Sand in Drained and Undrained Conditions at Low Confining Stress in Small-Scale Landslide Model V. Jagodnik & Ž. Arbanas 10.3390/su141912797
76. Downscaling Satellite Precipitation Estimates With Multiple Linear Regression, Artificial Neural Networks, and Spline Interpolation Techniques E. Sharifi et al. 10.1029/2018JD028795
77. Influence of seismic acceleration on landslide susceptibility maps: a case study from NE Turkey (the Kelkit Valley) H. Das et al. 10.1007/s10346-012-0342-8
78. Rainfall-induced landslide susceptibility assessment using random forest weight at basin scale C. Lai et al. 10.2166/nh.2017.044
79. Hazard zonation mapping of earthquake-induced secondary effects using spatial multi-criteria analysis M. Karpouza et al. 10.1007/s11069-021-04852-0
80. An integrative approach for regional landslide susceptibility assessment using weight of evidence method: a case study of Yom River Basin, Phrae Province, Northern Thailand S. Teerarungsigul et al. 10.1007/s10346-015-0659-1
81. Landslide susceptibility mapping along PLUS expressways in Malaysia using probabilistic based model in GIS N. Yusof & B. Pradhan 10.1088/1755-1315/20/1/012031
82. Application and comparison of logistic regression model and neural network model in earthquake-induced landslides susceptibility mapping at mountainous region, China P. Xie et al. 10.1080/19475705.2018.1451399
83. Elimination of informational redundancy in the weight of evidence method: an application to landslide susceptibility assessment J. Torizin 10.1007/s00477-015-1077-6
84. Landslide Susceptibility Mapping in Vertical Distribution Law of Precipitation Area: Case of the Xulong Hydropower Station Reservoir, Southwestern China C. Cao et al. 10.3390/w8070270
85. A benchmark dataset and workflow for landslide susceptibility zonation M. Alvioli et al. 10.1016/j.earscirev.2024.104927
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92. Comparison of landslide susceptibility maps generated through multiple logistic regression for three test areas in Korea S. Lee 10.1002/esp.1517
93. Failure rate analysis of jaw crusher using Weibull model R. Sinha & A. Mukhopadhyay 10.1177/0954408916636922
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95. Cross-application used to validate landslide susceptibility maps using a probabilistic model from Korea H. Oh & S. Lee 10.1007/s12665-010-0864-0
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109. A comparative study of landslide susceptibility mapping using landslide susceptibility index and artificial neural networks in the Krios River and Krathis River catchments (northern Peloponnesus, Greece) C. Polykretis et al. 10.1007/s10064-014-0607-7
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112. Integrated analysis of landslide susceptibility: geotechnical insights, frequency ratio method, and hazard mitigation strategies in a volcanic terrain B. Momene Tuwa et al. 10.1007/s12517-025-12221-5