100 citations as recorded by crossref.

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3. Degradation of marls; two case studies from the Iberian Peninsula E. Alonso et al. https://doi.org/10.1144/EGSP23.5
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5. RS & GIS-based landslide susceptibility mapping of the Balason River basin, Darjeeling Himalaya, using logistic regression (LR) model S. Mondal & S. Mandal https://doi.org/10.1080/17499518.2017.1347949
6. Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria Y. Achour et al. https://doi.org/10.1007/s12517-017-2980-6
7. A GIS Plugin for Susceptibility Modeling: Case Study of Wildfires in Vila Nova de Foz Côa A. Padrão et al. https://doi.org/10.3390/land11071093
8. Post-seismic monitoring of cliff mass wasting using an unmanned aerial vehicle and field data at Egremni, Lefkada Island, Greece I. Koukouvelas et al. https://doi.org/10.1016/j.geomorph.2020.107306
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12. Analytical hierarchy process (AHP) based landslide susceptibility mapping of Lish river basin of eastern Darjeeling Himalaya, India B. Mandal & S. Mandal https://doi.org/10.1016/j.asr.2018.08.008
13. Rule-based fuzzy inference system for landslide susceptibility mapping along national highway 7 in Garhwal Himalayas, India S. Badola et al. https://doi.org/10.1016/j.qsa.2023.100093
14. Exploring discrepancies between quantitative validation results and the geomorphic plausibility of statistical landslide susceptibility maps S. Steger et al. https://doi.org/10.1016/j.geomorph.2016.03.015
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17. Spatio-statistical comparative approaches for landslide susceptibility modeling: case of Mae Phun, Uttaradit Province, Thailand M. Moazzam et al. https://doi.org/10.1007/s42452-020-2106-8
18. Spatio-Statistical Analysis of Flood Susceptibility Assessment Using Bivariate Model in the Floodplain of River Swat, District Charsadda, Pakistan M. Moazzam et al. https://doi.org/10.4236/gep.2020.85010
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20. Identifying the role of structural and lithological control of landslides using TOBIA and Weight of Evidence: case studies from Romania V. Ilinca et al. https://doi.org/10.1007/s10346-021-01749-8
21. Assessment of physical vulnerability of buildings and analysis of landslide risk at the municipal scale: application to the Loures municipality, Portugal C. Guillard-Gonçalves et al. https://doi.org/10.5194/nhess-16-311-2016
22. A comparative analysis of statistical landslide susceptibility mapping in the southeast region of Minas Gerais state, Brazil C. Barella et al. https://doi.org/10.1007/s10064-018-1341-3
23. Comparative landslide susceptibility mapping using local inventories: a case study from Trabzon, Türkiye Ş. Öztürk https://doi.org/10.1007/s11069-025-07371-4
24. Literature review and bibliometric analysis on data-driven assessment of landslide susceptibility P. Lima et al. https://doi.org/10.1007/s11629-021-7254-9
25. GIS-Based Approaches for the Landslide Susceptibility Prediction in Setif Region (NE Algeria) Z. Karim et al. https://doi.org/10.1007/s10706-018-0615-7
26. Application of a relief-optimized method for target space exteriorization sampling in landslide susceptibility assessment Y. Cui et al. https://doi.org/10.1007/s11629-025-9504-8
27. GIS-based landslide susceptibility zonation using bivariate statistical and expert approaches in the city of Constantine (Northeast Algeria) H. Bourenane et al. https://doi.org/10.1007/s10064-014-0616-6
28. Aplicação do índice estatístico e análise multicritério no mapeamento da suscetibilidade a deslizamentos, no município do Ipojuca, Pernambuco, Brasil C. Duarte et al. https://doi.org/10.26848/rbgf.v17.2.p1015-1037
29. Landslide susceptibility assessment of South Pars Special Zone, southwest Iran M. Azarafza et al. https://doi.org/10.1007/s12665-018-7978-1
30. Integrating principal component analysis with statistically-based models for analysis of causal factors and landslide susceptibility mapping: A comparative study from the loess plateau area in Shanxi (China) Y. Tang et al. https://doi.org/10.1016/j.jclepro.2020.124159
31. The (f)utility to account for pre-failure topography in data-driven landslide susceptibility modelling S. Steger et al. https://doi.org/10.1016/j.geomorph.2020.107041
32. Integrating Landslide Typology with Weighted Frequency Ratio Model for Landslide Susceptibility Mapping: A Case Study from Lanzhou City of Northwestern China H. Shu et al. https://doi.org/10.3390/rs13183623
33. Predicting Landslide Susceptibility Using Cost Function in Low-Relief Areas: A Case Study of the Urban Municipality of Attecoube (Abidjan, Ivory Coast) F. Gnagne et al. https://doi.org/10.3390/earth6030084
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35. Landslide Susceptibility Assessment at the Basin Scale for Rainfall- and Earthquake-Triggered Shallow Slides C. Gordo et al. https://doi.org/10.3390/geosciences9060268
36. Implications of Landslide Typology and Predisposing Factor Combinations for Probabilistic Landslide Susceptibility Models: A Case Study in Lajedo Parish (Flores Island, Azores—Portugal) R. Silva et al. https://doi.org/10.3390/geosciences8050153
37. 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
38. Susceptibility modelling of hummocky terrain distribution using the information value method (Deception Island, Antarctic Peninsula) R. Melo et al. https://doi.org/10.1016/j.geomorph.2011.12.027
39. Distribution and temporal-spatial characteristics of geohazards in a rainstorm-prone area of SE China considering the land use Z. Guo et al. https://doi.org/10.1016/j.bgtech.2025.100184
40. Modeling Typhoon Event-Induced Landslides Using GIS-Based Logistic Regression: A Case Study of Alishan Forestry Railway, Taiwan S. Chen et al. https://doi.org/10.1155/2013/728304
41. Normalized Landslide Index Method for susceptibility map development in El Salvador A. Posner & K. Georgakakos https://doi.org/10.1007/s11069-015-1930-4
42. GIS-based landslide susceptibility zonation and comparative analysis using analytical hierarchy process and conventional weighting-based multivariate statistical methods in the Lachung River Basin, North Sikkim S. Wadadar & B. Mukhopadhyay https://doi.org/10.1007/s11069-022-05344-5
43. Shallow landslides predisposing and triggering factors in developing a regional early warning system D. Tiranti et al. https://doi.org/10.1007/s10346-018-1096-8
44. Landslide susceptibility mapping using modified information value model in the Lish river basin of Darjiling Himalaya B. Mandal & S. Mandal https://doi.org/10.1007/s41324-017-0096-4
45. Landslide hazard mapping along national highway-154A in Himachal Pradesh, India using information value and frequency ratio K. Singh & V. Kumar https://doi.org/10.1007/s12517-017-3315-3
46. Aveiro Canyon Head (Portugal) Submarine Slope Instability Assessment N. Lapa et al. https://doi.org/10.3390/app10249038
47. Landslide Susceptibility Mapping Using Bivariate Statistical Models and GIS in Chattagram District, Bangladesh M. Chowdhury & B. Hafsa https://doi.org/10.1007/s10706-022-02111-y
48. Landslide susceptibility zonation using the analytical hierarchy process (AHP) in the Bafoussam-Dschang region (West Cameroon) F. Zangmene et al. https://doi.org/10.1016/j.asr.2023.02.014
49. Combining Social Vulnerability and Physical Vulnerability to Analyse Landslide Risk at the Municipal Scale C. Guillard-Gonçalves & J. Zêzere https://doi.org/10.3390/geosciences8080294
50. The Role of Soil Type in Triggering Shallow Landslides in the Alps (Lombardy, Northern Italy) F. Luino et al. https://doi.org/10.3390/land11081125
51. Evaluating effectiveness of frequency ratio, fuzzy logic and logistic regression models in assessing landslide susceptibility: a case from Rudraprayag district, India M. Sahana & H. Sajjad https://doi.org/10.1007/s11629-017-4404-1
52. Three-Dimensional Mineralization Prediction Using the Information Value Method: A Case Study of the Bainiuchang Ag Polymetallic Deposit, Southwest China F. Jia et al. https://doi.org/10.3390/min15080783
53. Using InfoVal method and GIS techniques for the spatial modelling of landslide susceptibility in the upper catchment of river Meenachil in Kerala H. Vijith et al. https://doi.org/10.1007/s12524-009-0028-4
54. Evaluation and Validation of Landslide Spatial Susceptibility in the Western Ghats of Kerala, through GIS-based Weights of Evidence Model and Area under Curve Technique V. Prasannakumar & H. Vijith https://doi.org/10.1007/s12594-012-0171-3
55. Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Eastern Black Sea region of Turkey) H. Nefeslioglu et al. https://doi.org/10.1016/j.geomorph.2006.10.036
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62. Implementation of reconstructed geomorphologic units in landslide susceptibility mapping: the Melen Gorge (NW Turkey) T. Gorum et al. https://doi.org/10.1007/s11069-007-9190-6
63. Sea cliff instability susceptibility at regional scale: a statistically based assessment in the southern Algarve, Portugal F. Marques et al. https://doi.org/10.5194/nhess-13-3185-2013
64. RER2023: the landslide inventory dataset of the May 2023 Emilia-Romagna meteorological event M. Berti et al. https://doi.org/10.5194/essd-17-1055-2025
65. Application and validation of bivariate GIS-based landslide susceptibility assessment for the Vitravo river catchment (Calabria, south Italy) M. Conforti et al. https://doi.org/10.1007/s11069-011-9781-0
66. A GIS-based approach for gully erosion susceptibility modelling using bivariate statistics methods in the Ourika watershed, Morocco M. Meliho et al. https://doi.org/10.1007/s12665-018-7844-1
67. 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
68. Modeling debris flow initiation and run-out in recently burned areas using data-driven methods R. Melo & J. Zêzere https://doi.org/10.1007/s11069-017-2921-4
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