90 citations as recorded by crossref.

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3. Is multi-hazard mapping effective in assessing natural hazards and integrated watershed management? H. Pourghasemi et al. 10.1016/j.gsf.2019.10.008
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17. A hybrid feature selection algorithm integrating an extreme learning machine for landslide susceptibility modeling of Mt. Woomyeon, South Korea N. Vasu & S. Lee 10.1016/j.geomorph.2016.03.023
18. A Tool for Classification and Regression Using Random Forest Methodology: Applications to Landslide Susceptibility Mapping and Soil Thickness Modeling D. Lagomarsino et al. 10.1007/s10666-016-9538-y
19. Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata, Japan J. Dou et al. 10.1371/journal.pone.0133262
20. The (f)utility to account for pre-failure topography in data-driven landslide susceptibility modelling S. Steger et al. 10.1016/j.geomorph.2020.107041
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23. Landslide-hazard mapping through multi-technique activity assessment: an example from the Betic Cordillera (southern Spain) J. Jiménez-Perálvarez et al. 10.1007/s10346-017-0851-6
24. A novel fuzzy K-nearest neighbor inference model with differential evolution for spatial prediction of rainfall-induced shallow landslides in a tropical hilly area using GIS D. Tien Bui et al. 10.1007/s10346-016-0708-4
25. A Novel Hybrid Approach Based on Instance Based Learning Classifier and Rotation Forest Ensemble for Spatial Prediction of Rainfall-Induced Shallow Landslides using GIS Q. Nguyen et al. 10.3390/su9050813
26. A novel hybrid approach of Bayesian Logistic Regression and its ensembles for landslide susceptibility assessment M. Abedini et al. 10.1080/10106049.2018.1499820
27. Comparison of a logistic regression and Naïve Bayes classifier in landslide susceptibility assessments: The influence of models complexity and training dataset size P. Tsangaratos & I. Ilia 10.1016/j.catena.2016.06.004
28. Innovative landslide susceptibility mapping supported by geomorphon and geographical detector methods W. Luo & C. Liu 10.1007/s10346-017-0893-9
29. Exploring the effect of absence selection on landslide susceptibility models: A case study in Sicily, Italy C. Conoscenti et al. 10.1016/j.geomorph.2016.03.006
30. Spatial prediction of rainfall-induced shallow landslides using hybrid integration approach of Least-Squares Support Vector Machines and differential evolution optimization: a case study in Central Vietnam D. Tien Bui et al. 10.1080/17538947.2016.1169561
31. Landslide susceptibility modeling assisted by Persistent Scatterers Interferometry (PSI): an example from the northwestern coast of Malta D. Piacentini et al. 10.1007/s11069-015-1740-8
32. Landslide Hazard and Exposure Modelling in Data‐Poor Regions: The Example of the Rohingya Refugee Camps in Bangladesh R. Emberson et al. 10.1029/2020EF001666
33. Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines H. Hong et al. 10.1016/j.catena.2015.05.019
34. Landslide-risk mapping in a developing hilly area with limited information on landslide occurrence J. Jiménez-Perálvarez 10.1007/s10346-017-0903-y
35. Parameters Derived from and/or Used with Digital Elevation Models (DEMs) for Landslide Susceptibility Mapping and Landslide Risk Assessment: A Review N. Saleem et al. 10.3390/ijgi8120545
36. Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues F. Catani et al. 10.5194/nhess-13-2815-2013
37. The performance of landslide susceptibility models critically depends on the quality of digital elevation models J. Brock et al. 10.1080/19475705.2020.1776403
38. Flash-Flood Potential assessment in the upper and middle sector of Prahova river catchment (Romania). A comparative approach between four hybrid models R. Costache 10.1016/j.scitotenv.2018.12.397
39. Landslide susceptibility mapping using hybridized block modular intelligence model A. Abbaszadeh Shahri & F. Maghsoudi Moud 10.1007/s10064-020-01922-8
40. Digital Elevation Models of Rockfalls and Landslides: A Review and Meta-Analysis M. Kakavas & K. Nikolakopoulos 10.3390/geosciences11060256
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42. Landslide Detection Using Densely Connected Convolutional Networks and Environmental Conditions H. Cai et al. 10.1109/JSTARS.2021.3079196
43. Comparative analysis of gradient boosting algorithms for landslide susceptibility mapping E. Sahin 10.1080/10106049.2020.1831623
44. The assessment of landslide susceptibility mapping using random forest and decision tree methods in the Three Gorges Reservoir area, China K. Zhang et al. 10.1007/s12665-017-6731-5
45. Assessment of susceptibility to earth-flow landslide using logistic regression and multivariate adaptive regression splines: A case of the Belice River basin (western Sicily, Italy) C. Conoscenti et al. 10.1016/j.geomorph.2014.09.020
46. A Novel Relevance Vector Machine Classifier with Cuckoo Search Optimization for Spatial Prediction of Landslides N. Hoang & D. Tien Bui 10.1061/(ASCE)CP.1943-5487.0000557
47. Mapping Susceptibility to Debris Flows Triggered by Tropical Storms: A Case Study of the San Vicente Volcano Area (El Salvador, CA) C. Mercurio et al. 10.3390/earth2010005
48. Feature-based model for landslide susceptibility mapping using a multi-parametric decision-making technique and the analytic hierarchy process L. Bopche & P. Rege 10.1007/s12046-021-01648-7
49. Applying Information Theory and GIS-based quantitative methods to produce landslide susceptibility maps in Nancheng County, China P. Tsangaratos et al. 10.1007/s10346-016-0769-4
50. Introducing a novel multi-layer perceptron network based on stochastic gradient descent optimized by a meta-heuristic algorithm for landslide susceptibility mapping H. Hong et al. 10.1016/j.scitotenv.2020.140549
51. An Event-Based Inventory Approach in Landslide Hazard Assessment: The Case of the Skolis Mountain, Northwest Peloponnese, Greece A. Litoseliti et al. 10.3390/ijgi9070457
52. Forward logistic regression for earth-flow landslide susceptibility assessment in the Platani river basin (southern Sicily, Italy) D. Costanzo et al. 10.1007/s10346-013-0415-3
53. Automated derivation and spatio-temporal analysis of landslide properties in southern Kyrgyzstan D. Golovko et al. 10.1007/s11069-016-2636-y
54. An assessment of multivariate and bivariate approaches in landslide susceptibility mapping: a case study of Duzkoy district T. Kavzoglu et al. 10.1007/s11069-014-1506-8
55. GIS-based landslide spatial modeling in Ganzhou City, China H. Hong et al. 10.1007/s12517-015-2094-y
56. Application of geographically weighted principal component analysis and fuzzy approach for unsupervised landslide susceptibility mapping on Gish River Basin, India T. Basu et al. 10.1080/10106049.2020.1778105
57. Debris flow susceptibility mapping using frequency ratio and seed cells, in a portion of a mountain international route, Dry Central Andes of Argentina M. Esper Angillieri 10.1016/j.catena.2020.104504
58. A comparative study of support vector machine and logistic model tree classifiers for shallow landslide susceptibility modeling M. Abedini et al. 10.1007/s12665-019-8562-z
59. Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree D. Tien Bui et al. 10.1007/s10346-015-0557-6
60. GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran, Iran) H. Pourghasemi et al. 10.1007/s12517-012-0825-x
61. Improving landslide susceptibility mapping using morphometric features in the Mawat area, Kurdistan Region, NE Iraq: Comparison of different statistical models A. Othman et al. 10.1016/j.geomorph.2018.07.018
62. A modified frequency ratio method for landslide susceptibility assessment L. Li et al. 10.1007/s10346-016-0771-x
63. Coupled model for simulation of landslides and debris flows at local scale D. Park et al. 10.1007/s11069-016-2150-2
64. Comparing Forward Conditional Analysis and Forward Logistic Regression Methods in a Landslide Susceptibility Assessment: A Case Study in Sicily D. Costanzo & C. Irigaray 10.3390/hydrology7030037
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69. An integrative approach of the physical-based stability index mapping with the maximum entropy stochastic model for risk analysis of mass movements H. Memarian et al. 10.1007/s10668-022-02165-1
70. Landslide susceptibility assessment in Lianhua County (China): A comparison between a random forest data mining technique and bivariate and multivariate statistical models H. Hong et al. 10.1016/j.geomorph.2016.02.012
71. Predicting the landslides triggered by the 2009 96E/Ida tropical storms in the Ilopango caldera area (El Salvador, CA): optimizing MARS-based model building and validation strategies E. Rotigliano et al. 10.1007/s12665-019-8214-3
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76. Exploring relationships between grid cell size and accuracy for debris-flow susceptibility models: a test in the Giampilieri catchment (Sicily, Italy) M. Cama et al. 10.1007/s12665-015-5047-6
77. Comparative Assessment of Three Nonlinear Approaches for Landslide Susceptibility Mapping in a Coal Mine Area Q. Su et al. 10.3390/ijgi6070228
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79. Modelling terrain erosion susceptibility of logged and regenerated forested region in northern Borneo through the Analytical Hierarchy Process (AHP) and GIS techniques H. Vijith & D. Dodge-Wan 10.1186/s40677-019-0124-x
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82. Development of a region-partitioning method for debris flow susceptibility mapping S. Qiao et al. 10.1007/s11629-020-6497-1
83. Landslide risk assessment considering socionatural factors: methodology and application to Cubatão municipality, São Paulo, Brazil P. Hader et al. 10.1007/s11069-021-04991-4
84. Expert judgement criteria for mapping landslide susceptibility in Tangse Sub-District, Pidie District, Aceh Province, Indonesia H. Basri et al. 10.1088/1755-1315/667/1/012059
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