63 citations as recorded by crossref.

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14. GIS-based analysis of landslides susceptibility mapping: a case study of Lushoto district, north-eastern Tanzania M. Makonyo & Z. Zahor 10.1007/s11069-023-06038-2
15. Potential ecotourism site suitability evaluation for sustainable natural resource management in Kafta Sheraro National Park (KSNP), north-western Tigray, Ethiopia S. Abrehe et al. 10.1080/14724049.2021.1897599
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18. Landslide Susceptibility Modeling Using the Index of Entropy and Frequency Ratio Method from Nefas-Mewcha to Weldiya Road Corridor, Northwestern Ethiopia A. Wubalem et al. 10.1007/s10706-022-02214-6
19. Modeling and Prediction of Habitat Suitability for Ferula gummosa Medicinal Plant in a Mountainous Area M. Mohammady et al. 10.1007/s11053-021-09940-3
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21. Probabilistic identification of rockfall source areas at regional scale in El Hierro (Canary Islands, Spain) M. Rossi et al. 10.1016/j.geomorph.2021.107661
22. Completeness of landslide inventory and landslide susceptibility mapping using logistic regression method in Ceyhan Watershed (southern Turkey) S. Tekin 10.1007/s12517-021-07583-5
23. Earthquake-triggered landslide susceptibility in Italy by means of Artificial Neural Network G. Amato et al. 10.1007/s10064-023-03163-x
24. GSFLOW–GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater–surface-water systems G. Ng et al. 10.5194/gmd-11-4755-2018
25. Literature review and bibliometric analysis on data-driven assessment of landslide susceptibility P. Lima et al. 10.1007/s11629-021-7254-9
26. Statistical and machine intelligence based model for landslide susceptibility mapping of Nilgiri district in India Y. R M & B. Dolui 10.1016/j.envc.2021.100211
27. A GIS-Based Comparative Analysis of Frequency Ratio and Statistical Index Models for Flood Susceptibility Mapping in the Upper Krishna Basin, India U. Pawar et al. 10.3390/w14223771
28. Hazard assessment modeling and software development of earthquake-triggered landslides in the Sichuan–Yunnan area, China X. Shao et al. 10.5194/gmd-16-5113-2023
29. A global slope unit-based method for the near real-time prediction of earthquake-induced landslides H. Tanyas et al. 10.1016/j.geomorph.2018.10.022
30. Using machine learning algorithms to map the groundwater recharge potential zones H. Pourghasemi et al. 10.1016/j.jenvman.2020.110525
31. Economic landslide susceptibility under a socio-economic perspective: an application to Umbria Region (Central Italy) M. Donnini et al. 10.1007/s10037-020-00143-6
32. How can statistical and artificial intelligence approaches predict piping erosion susceptibility? M. Hosseinalizadeh et al. 10.1016/j.scitotenv.2018.07.396
33. Relations of land cover, topography, and climate to fire occurrence in natural regions of Iran: Applying new data mining techniques for modeling and mapping fire danger S. Eskandari et al. 10.1016/j.foreco.2020.118338
34. A benchmark dataset and workflow for landslide susceptibility zonation M. Alvioli et al. 10.1016/j.earscirev.2024.104927
35. A spaceborne SAR-based procedure to support the detection of landslides G. Esposito et al. 10.5194/nhess-20-2379-2020
36. 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
37. Research on Uncertainty of Landslide Susceptibility Prediction—Bibliometrics and Knowledge Graph Analysis Z. Yang et al. 10.3390/rs14163879
38. Acquiring vulnerability indicators to geo-hydrological hazards: An example of mobile phone-based data collection P. Salvati et al. 10.1016/j.ijdrr.2021.102087
39. Landslide susceptibility assessment using frequency ratio model in Bogor, West Java, Indonesia F. Silalahi et al. 10.1186/s40562-019-0140-4
40. Landslide susceptibility assessment on a large scale in the Podsljeme area, City of Zagreb (Croatia) S. Bernat Gazibara et al. 10.1080/17445647.2022.2163197
41. Landslide Susceptibility Mapping in Terms of the Slope-Unit or Raster-Unit, Which is Better? S. Ma et al. 10.1007/s12583-021-1407-1
42. Aplicação do índice estatístico e análise multicritério no mapeamento da suscetibilidade a deslizamentos, no município do Ipojuca, Pernambuco, Brasil C. Duarte et al. 10.26848/rbgf.v17.2.p1015-1037
43. Optimizing landslide susceptibility zonation: Effects of DEM spatial resolution and slope unit delineation on logistic regression models R. Schlögel et al. 10.1016/j.geomorph.2017.10.018
44. LAND-SUITE V1.0: a suite of tools for statistically based landslide susceptibility zonation M. Rossi et al. 10.5194/gmd-15-5651-2022
45. An updated version of the SZ-plugin: From space to space–time data-driven modeling in QGIS G. Titti et al. 10.1016/j.jag.2025.104679
46. Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster L. Lombardo et al. 10.1007/s00477-018-1518-0
47. Mapping Susceptibility With Open-Source Tools: A New Plugin for QGIS G. Titti et al. 10.3389/feart.2022.842425
48. Geospatial analysis of landslide susceptibility and safe relocation zones: Insights from recent disasters in Gofa Zone, Southern Ethiopia N. Ayele et al. 10.1016/j.qsa.2025.100272
49. Is multi-hazard mapping effective in assessing natural hazards and integrated watershed management? H. Pourghasemi et al. 10.1016/j.gsf.2019.10.008
50. Assessment of land subsidence susceptibility in Semnan plain (Iran): a comparison of support vector machine and weights of evidence data mining algorithms M. Mohammady et al. 10.1007/s11069-019-03785-z
51. Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling M. Alvioli et al. 10.5194/gmd-9-3975-2016
52. Characteristics and causes of natural and human-induced landslides in a tropical mountainous region: the rift flank west of Lake Kivu (Democratic Republic of the Congo) J. Maki Mateso et al. 10.5194/nhess-23-643-2023
53. Potential suitability mapping evaluation for ecotourism development in Darjeeling Himalayan region of India D. Roy et al. 10.1080/14724049.2023.2272059
54. Implementing landslide path dependency in landslide susceptibility modelling J. Samia et al. 10.1007/s10346-018-1024-y
55. Application of stacking hybrid machine learning algorithms in delineating multi-type flooding in Bangladesh M. Rahman et al. 10.1016/j.jenvman.2021.113086
56. Landslide and Wildfire Susceptibility Assessment in Southeast Asia Using Ensemble Machine Learning Methods Q. He et al. 10.3390/rs13081572
57. GIS‐based susceptibility assessment of the occurrence of gully headcuts and pipe collapses in a semi‐arid environment: Golestan Province, NE Iran N. Kariminejad et al. 10.1002/ldr.3397
58. Improvement of landslide hazard assessments for regulatory zoning in France: STATE–OF–THE-ART perspectives and considerations Y. Thiery et al. 10.1016/j.ijdrr.2020.101562
59. Presenting logistic regression-based landslide susceptibility results L. Lombardo & P. Mai 10.1016/j.enggeo.2018.07.019
60. Landslide susceptibility mapping in East Ungaran, Indonesia: A comparative study using statistical methods D. Maulana et al. 10.15243/jdmlm.2024.114.6107
61. Reliability of water content estimation by profile probe and its effect on slope stability L. Di Matteo et al. 10.1007/s10346-017-0895-7
62. A review of statistically-based landslide susceptibility models P. Reichenbach et al. 10.1016/j.earscirev.2018.03.001
63. Susceptibility mapping of damming landslide based on slope unit using frequency ratio model H. Liu et al. 10.1007/s12517-020-05689-w