100 citations as recorded by crossref.

1. GIS-based landslide susceptibility analysis using frequency ratio and evidential belief function models Z. Zhang et al. https://doi.org/10.1007/s12665-016-5732-0
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3. Landslide susceptibility mapping along Bhalubang — Shiwapur area of mid-Western Nepal using frequency ratio and conditional probability models A. Regmi et al. https://doi.org/10.1007/s11629-013-2847-6
4. 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 https://doi.org/10.1016/j.catena.2016.06.004
5. Mapping the landslide susceptibility in Lantau Island, Hong Kong, by frequency ratio and logistic regression model J. Huang et al. https://doi.org/10.1080/19475683.2014.992373
6. Creating infrastructure for seismic microzonation by Geographical Information Systems (GIS): A case study in the North Anatolian Fault Zone (NAFZ) T. Turk et al. https://doi.org/10.1016/j.cageo.2011.10.006
7. Application of data-driven evidential belief functions to landslide susceptibility mapping in Jinbu, Korea S. Lee et al. https://doi.org/10.1016/j.catena.2012.07.014
8. Landslide susceptibility assessment for the Darjeeling Toy Train route: a GIS and machine learning approach P. Sarkar et al. https://doi.org/10.1007/s00477-024-02885-y
9. GIS-Based Groundwater Potential Mapping in Khorramabad in Lorestan, Iran, using Frequency Ratio (FR) and Weights of Evidence (WoE) Models . Fatemeh Falah & . Hossein Zeinivand https://doi.org/10.1134/S0097807819050051
10. Karst collapse susceptibility mapping considering peak ground acceleration in a rapidly growing urban area K. Papadopoulou-Vrynioti et al. https://doi.org/10.1016/j.enggeo.2013.02.009
11. Landslide Susceptibility Mapping: Machine and Ensemble Learning Based on Remote Sensing Big Data B. Kalantar et al. https://doi.org/10.3390/rs12111737
12. Spatial distribution analysis and susceptibility mapping of landslides triggered before and after Mw7.8 Gorkha earthquake along Upper Bhote Koshi, Nepal J. Tanoli et al. https://doi.org/10.1007/s12517-017-3026-9
13. Landslide susceptibility mapping using tree-based machine learning classifiers and remote sensing derived conditioning factors: A case study of Chikmagalur District, Western Ghats, India B. Ganesh et al. https://doi.org/10.1016/j.ejrs.2026.02.004
14. Quantitative risk assessment of landslides triggered by earthquakes and rainfall based on direct costs of urban buildings J. Vega & C. Hidalgo https://doi.org/10.1016/j.geomorph.2016.07.032
15. Pixel-Based Spatio-Statistical Analysis of Landslide Probability in Humid and Seismically Active Areas of Himalaya and Hindukush S. Khan et al. https://doi.org/10.3390/su16093556
16. A hydroclimatological approach to predicting regional landslide probability using Landlab R. Strauch et al. https://doi.org/10.5194/esurf-6-49-2018
17. Application of various strategies and methodologies for landslide susceptibility maps on a basin scale: the case study of Val Tartano, Italy V. Yordanov & M. Brovelli https://doi.org/10.1007/s12518-020-00344-1
18. Evaluation of environmental parameters in logistic regression models for landslide susceptibility mapping M. Süzen & B. Kaya https://doi.org/10.1080/17538947.2011.586443
19. Establishment of Natural Hazards Mapping Criteria Using Analytic Hierarchy Process (AHP) F. Morales & W. de Vries https://doi.org/10.3389/frsus.2021.667105
20. Evaluation of Conditioning Factors of Slope Instability and Continuous Change Maps in the Generation of Landslide Inventory Maps Using Machine Learning (ML) Algorithms R. Ramos-Bernal et al. https://doi.org/10.3390/rs13224515
21. A bibliometric and content analysis of research trends on GIS-based landslide susceptibility from 2001 to 2020 J. Huang et al. https://doi.org/10.1007/s11356-022-23732-z
22. GIS-Based Rockfall Susceptibility Zoning in Greece C. Saroglou https://doi.org/10.3390/geosciences9040163
23. Spatial prediction of landslide-susceptible zones in El-Qaá area, Egypt, using an integrated approach based on GIS statistical analysis S. Abuzied & H. Alrefaee https://doi.org/10.1007/s10064-018-1302-x
24. Assessment of landslide-triggering factors and occurrence using morphometric parameters in Geyraz Basin, Tokat, Northern Turkey T. Bayer Altın & E. Gökkaya https://doi.org/10.1007/s12665-018-7315-8
25. Landslide susceptibility analysis using Probabilistic Certainty Factor Approach: A case study on Tevankarai stream watershed, India E. Sujatha et al. https://doi.org/10.1007/s12040-012-0230-6
26. Modeling landslides hazard along Amman–Jerash–Irbid Highway, Jordan by integrating open street map (OSM) and weighted linear combination (WLC) techniques A. Al-Rawabdeh et al. https://doi.org/10.1007/s40808-023-01910-3
27. Characterising the spatial distribution, frequency and geomorphic controls on landslide occurrence, Molise, Italy E. Borgomeo et al. https://doi.org/10.1016/j.geomorph.2014.08.004
28. Landslide susceptibility analysis for the Kerch Peninsula using weights of evidence approach and GIS D. Krivoguz & L. Bespalova https://doi.org/10.2205/2019ES000682
29. Robust landslide susceptibility analysis by combination of frequency ratio, heuristic GIS-methods and ground truth evaluation for a mountainous study area with poor data availability in the Three Gorges Reservoir area, PR China M. Schleier et al. https://doi.org/10.1007/s12665-013-2677-4
30. Application of the Multitype Strauss Point Model for Characterizing the Spatial Distribution of Landslides I. Das & A. Stein https://doi.org/10.1155/2016/1612901
31. 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. https://doi.org/10.1080/17499518.2025.2563759
32. A Geomechanical Approach to Landslide Hazard Assessment: The Multiscalar Method for Landslide Mitigation F. Cotecchia et al. https://doi.org/10.1016/j.proeng.2016.08.471
33. Assessing the spatial variability of coefficients of landslide predictors in different regions of Romania using logistic regression M. Mărgărint et al. https://doi.org/10.5194/nhess-13-3339-2013
34. Implementing landslide path dependency in landslide susceptibility modelling J. Samia et al. https://doi.org/10.1007/s10346-018-1024-y
35. Assessing landslide susceptibility and dynamics at cultural heritage sites by integrating machine learning techniques and persistent scatterer interferometry J. Bonini et al. https://doi.org/10.1016/j.geomorph.2024.109522
36. Susceptibility assessment to different types of landslides in the coastal cliffs of Lourinhã (Central Portugal) B. Epifânio et al. https://doi.org/10.1016/j.seares.2014.04.006
37. Bivariate statistical index for landslide susceptibility mapping in the Rorachu river basin of eastern Sikkim Himalaya, India S. Mandal & K. Mandal https://doi.org/10.1007/s41324-017-0156-9
38. A new approach to mapping landslide hazards: a probabilistic integration of empirical and physically based models in the North Cascades of Washington, USA R. Strauch et al. https://doi.org/10.5194/nhess-19-2477-2019
39. Sinkhole Detection and Characterization Using LiDAR-Derived DEM with Logistic Regression Y. Kim et al. https://doi.org/10.3390/rs11131592
40. Methodological Aspects of Building Information System for Monitoring of Landslide Hazards V. Nikolova & P. Zlateva https://doi.org/10.1088/1755-1315/151/1/012028
41. Loess slide susceptibility assessment using frequency ratio model and artificial neural network H. Qiu et al. https://doi.org/10.1144/qjegh2017-056
42. Evaluating underlying causative factors for earthquake-induced landslides and landslide susceptibility mapping in Upper Indrawati Watershed, Nepal P. Gautam et al. https://doi.org/10.1186/s40677-021-00200-3
43. Landslide susceptibility of the Prato–Pistoia–Lucca provinces, Tuscany, Italy S. Segoni et al. https://doi.org/10.1080/17445647.2016.1233463
44. Geographic information system for the development of soil suitability map in south Chennai, India V. Stalin & R. Murugan https://doi.org/10.1007/s12517-014-1323-0
45. Slope Failure Characteristics and Slope Movement Susceptibility Assessment Using GIS in a Medium Scale: A Case Study from Ouled Driss and Machroha Municipalities, Northeast Algeria R. Hadji et al. https://doi.org/10.1007/s13369-016-2046-1
46. Development of a landslide susceptibility assessment for a rail network K. Martinović et al. https://doi.org/10.1016/j.enggeo.2016.10.011
47. Application of Analytical Hierarchy Process (AHP) algorithm to income insecurity susceptibility mapping – A study in the district of Purulia, India M. Mishra & S. Chatterjee https://doi.org/10.1016/j.seps.2017.07.002
48. A Review of Landslide Conditioning Factors in the Tropical Forests A. Jasni et al. https://doi.org/10.47836/pjst.32.S4.04
49. An Open-Source Platform for GIS Data Management and Analytics F. Piccoli et al. https://doi.org/10.3390/s23083788
50. Determination of landslide hazardous map using logistic regression in Lima Puluh Kota Regency . Ahyuni et al. https://doi.org/10.1088/1742-6596/2582/1/012012
51. 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. https://doi.org/10.1007/s10346-016-0708-4
52. A review on spatial, temporal and magnitude prediction of landslide hazard A. Tyagi et al. https://doi.org/10.1016/j.jaesx.2022.100099
53. Mapping of Groundwater Spring Potential in Karst Aquifer System Using Novel Ensemble Bivariate and Multivariate Models V. Nhu et al. https://doi.org/10.3390/w12040985
54. GIS-based landslide susceptibility mapping using Frequency ratio method: A case study from Adigrat-Mugulat mountain chains, northern Ethiopia A. Abay et al. https://doi.org/10.1016/j.sciaf.2025.e02661
55. Landslide Susceptibility Mapping Using GIS-Based Data Mining Algorithms V. Vakhshoori et al. https://doi.org/10.3390/w11112292
56. Redundancy and hierarchical cluster analyses for characterizing geomorphic features contributing to the formation of landslide dams H. Chen et al. https://doi.org/10.1007/s10346-024-02310-z
57. Data-driven segmentation of observation-level logistic regression models Y. Choi et al. https://doi.org/10.1093/jrsssc/qlaf015
58. 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. https://doi.org/10.3390/su9050813
59. Application of logistic regression and fuzzy operators to landslide susceptibility assessment in Azdavay (Kastamonu, Turkey) M. Ercanoglu & F. Temiz https://doi.org/10.1007/s12665-011-0912-4
60. Influence of Tectonics and Morphometric Features on the Landslide Distribution: A Case Study from the Mesima Basin (Calabria, South Italy) M. Conforti & F. Ietto https://doi.org/10.1007/s12583-019-1231-z
61. Methods of Evaluation for Region’s Landslide Susceptibility. Short Overview Д. Кривогуз & D. Krivoguz https://doi.org/10.12737/22192
62. Factors influencing landslide occurrence in low-relief formerly glaciated landscapes: landslide inventory and susceptibility analysis in Minnesota, USA L. Triplett et al. https://doi.org/10.1007/s11069-025-07262-8
63. Analysis of bi-variate statistical and multi-criteria decision-making models in landslide susceptibility mapping in lower Mandakini Valley, India H. Mirdda et al. https://doi.org/10.1007/s10708-019-09991-3
64. Landslide susceptibility assessment in the rocky coast subsystem of Essaouira, Morocco A. Khouz et al. https://doi.org/10.5194/nhess-22-3793-2022
65. Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya A. Regmi et al. https://doi.org/10.1007/s12517-012-0807-z
66. A single framework for assessing flash flood and landslide susceptibility: an application to the Mediterranean Liguria region, Italy A. Riveros et al. https://doi.org/10.5194/nhess-26-2437-2026
67. Integration of landslide susceptibility assessment in urban development: a case study in Predeal town, Romanian Carpathians B. Mihai et al. https://doi.org/10.1111/area.12123
68. Digital Elevation Models of Rockfalls and Landslides: A Review and Meta-Analysis M. Kakavas & K. Nikolakopoulos https://doi.org/10.3390/geosciences11060256
69. Insights Gained from the Review of Landslide Susceptibility Assessment Studies in Italy S. Segoni et al. https://doi.org/10.3390/rs16234491
70. Description of a GIS-based rockfall hazard assessment methodology and its application in mountainous sites N. Depountis et al. https://doi.org/10.1007/s10064-019-01590-3
71. Landslide dam formation susceptibility analysis based on geomorphic features C. Chen & J. Chang https://doi.org/10.1007/s10346-015-0671-5
72. Buffer movement analysis and blunder probability analysis for GIS-based landslide susceptibility mapping E. HAMASAKI et al. https://doi.org/10.3313/jls.52.51
73. A watershed fragility index for assessing the vulnerability of river ecosystems K. Lira et al. https://doi.org/10.1016/j.ecolind.2025.113908
74. Determination of the development of settlements above earthquake susceptibility classes in Atakum district (Samsun/Turkey) M. Bahadır et al. https://doi.org/10.26833/ijeg.1465072
75. Landslide susceptibility analysis for the Kerch Peninsula using weights of evidence approach and GIS D. Krivoguz & L. Bespalova https://doi.org/10.2205/2020ES000682
76. The relations between settlement and selected environmental features with regard to landslide hazard in the Polish Carpathians P. Śleszyński et al. https://doi.org/10.1016/j.catena.2025.108897
77. The Contribution of Landslide Susceptibility Factors Through the Use of Rock Engineering System (RES) to the Prognosis of Slope Failures: An Application in Panagopoula and Malakasa Landslide Areas in Greece N. Tavoularis et al. https://doi.org/10.1007/s10706-017-0403-9
78. Automated derivation and spatio-temporal analysis of landslide properties in southern Kyrgyzstan D. Golovko et al. https://doi.org/10.1007/s11069-016-2636-y
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80. A simple method for landslide risk assessment in the Rivière Aux Vases basin, Quebec, Canada A. Regmi & N. Agrawal https://doi.org/10.1016/j.pdisas.2022.100247
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100. Susceptibility factors of drainage basins to shallow landslides in coffee-growing areas in the Department of Caldas, Colombia L. Salazar Gutiérrez et al. https://doi.org/10.1007/s12665-021-09428-6