38 citations as recorded by crossref.

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5. r.survey: a tool for calculating visibility of variable-size objects based on orientation T. Bornaetxea & I. Marchesini 10.1080/13658816.2021.1942476
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8. Space-time data-driven modeling of precipitation-induced shallow landslides in South Tyrol, Italy M. Moreno et al. 10.1016/j.scitotenv.2023.169166
9. An Improved Method for the Evaluation and Local Multi-Scale Optimization of the Automatic Extraction of Slope Units in Complex Terrains Z. Yang et al. 10.3390/rs14143444
10. A Comprehensive Comparison of Stable and Unstable Area Sampling Strategies in Large-Scale Landslide Susceptibility Models Using Machine Learning Methods M. Sinčić et al. 10.3390/rs16162923
11. 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
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14. Integrating Data Modality and Statistical Learning Methods for Earthquake-Induced Landslide Susceptibility Mapping Z. Miao et al. 10.3390/app12031760
15. Correlation does not imply geomorphic causation in data-driven landslide susceptibility modelling – Benefits of exploring landslide data collection effects S. Steger et al. 10.1016/j.scitotenv.2021.145935
16. 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
17. Enhancing Landslide Susceptibility Mapping by Integrating Neighboring Information in Slope Units: A Spatial Logistic Regression L. Li et al. 10.3390/rs16234475
18. Effects of raster resolution on real probability of landslides X. Shao et al. 10.1016/j.rsase.2020.100364
19. Rockfall susceptibility and network-ranked susceptibility along the Italian railway M. Alvioli et al. 10.1016/j.enggeo.2021.106301
20. Terrain visibility impact on the preparation of landslide inventories: a practical example in Darjeeling district (India) T. Bornaetxea et al. 10.5194/nhess-22-2929-2022
21. A novel dynamic rockfall susceptibility model including precipitation, temperature and snowmelt predictors: a case study in Aosta Valley (northern Italy) G. Bajni et al. 10.1007/s10346-023-02091-x
22. Landslide Susceptibility Mapping Based on Multitemporal Remote Sensing Image Change Detection and Multiexponential Band Math X. Yu et al. 10.3390/su15032226
23. Influence of sampling design on landslide susceptibility modeling in lithologically heterogeneous areas A. Dornik et al. 10.1038/s41598-022-06257-w
24. A landslide susceptibility assessment method considering the similarity of geographic environments based on graph neural network Q. Zhang et al. 10.1016/j.gr.2024.04.013
25. Event-Based Landslide Modeling in the Styrian Basin, Austria: Accounting for Time-Varying Rainfall and Land Cover R. Knevels et al. 10.3390/geosciences10060217
26. Adopting the margin of stability for space–time landslide prediction – A data-driven approach for generating spatial dynamic thresholds S. Steger et al. 10.1016/j.gsf.2024.101822
27. Assessing the utility of regionalized rock-mass geomechanical properties in rockfall susceptibility modelling in an alpine environment G. Bajni et al. 10.1016/j.geomorph.2022.108401
28. Landslide susceptibility maps of Italy: Lesson learnt from dealing with multiple landslide types and the uneven spatial distribution of the national inventory M. Loche et al. 10.1016/j.earscirev.2022.104125
29. Graph neural networks with constraints of environmental consistency for landslide susceptibility evaluation H. Zeng et al. 10.1080/13658816.2022.2103819
30. The Open Landslide Project (OLP), a New Inventory of Shallow Landslides for Susceptibility Models: The Autumn 2019 Extreme Rainfall Event in the Langhe-Monferrato Region (Northwestern Italy) M. Licata et al. 10.3390/geosciences13100289
31. Regional susceptibility assessments with heterogeneous landslide information: Slope unit- vs. pixel-based approach L. Jacobs et al. 10.1016/j.geomorph.2020.107084
32. LAND-SUITE V1.0: a suite of tools for statistically based landslide susceptibility zonation M. Rossi et al. 10.5194/gmd-15-5651-2022
33. Application of the group method of data handling (GMDH) approach for landslide susceptibility zonation using readily available spatial covariates M. Panahi et al. 10.1016/j.catena.2021.105779
34. Parameter-free delineation of slope units and terrain subdivision of Italy M. Alvioli et al. 10.1016/j.geomorph.2020.107124
35. The use of machine learning techniques for a predictive model of debris flows triggered by short intense rainfall M. Ponziani et al. 10.1007/s11069-023-05853-x
36. Preparing first-time slope failures hazard maps: from pixel-based to slope unit-based G. Domènech et al. 10.1007/s10346-019-01279-4
37. The influence of land use and land cover change on landslide susceptibility in the Lower Mekong River Basin C. Dandridge et al. 10.1007/s11069-022-05604-4
38. Rapid prediction of the magnitude scale of landslide events triggered by an earthquake H. Tanyaş et al. 10.1007/s10346-019-01136-4