10 citations as recorded by crossref.

1. Regional landslide susceptibility mapping of earthflows using deep neural networks: A case study in the southern Apennines, Italy A. Doglioni et al. https://doi.org/10.1016/j.enggeo.2026.108753
2. Integrating GIS and comparative multi-criteria decision-making techniques for landslide susceptibility assessment R. Faisal & Z. Shehab https://doi.org/10.1177/03091333251380439
3. Research on a spatial multi-scale detection method for newly occurred landslides by coupling LGBM and YOLO X. Yu & Z. Wang https://doi.org/10.1007/s11069-026-08134-5
4. Deep Learning in Slope Stability Analysis: Evolution, Challenges, and Future Directions D. Li et al. https://doi.org/10.1007/s10706-025-03424-4
5. Assessing the impact of training samples overlap and density in random forest for landslide susceptibility mapping: Implications for degraded land management in Bandung Regency, Indonesia H. Nugroho et al. https://doi.org/10.15243/jdmlm.2025.125.8933
6. Landslide susceptibility zoning through physically-based limit equilibrium method modelling F. Mevoli et al. https://doi.org/10.1016/j.catena.2025.109726
7. Improving landslide susceptibility mapping: The role of non-landslide sample selection in machine learning models M. Abdelkader et al. https://doi.org/10.1016/j.rsase.2025.101759
8. Landslide Risk Assessment in the Xiluodu Reservoir Area Using an Integrated Certainty Factor–Logistic Regression Model J. Fan et al. https://doi.org/10.3390/geomatics5040059
9. Multi-hazard Vulnerability Assessment Through RS-GIS and AHP: A Geo-Spatial Study of Keleghai River Basin in India A. Roy & S. Dhar https://doi.org/10.1007/s41742-025-00867-8
10. Landslide susceptibility assessment incorporating characteristic rainfall parameters and multi-weight dominant factor analysis: a case study of extreme rainfall in Western Qinling based on evolution of data-driven models S. Liu et al. https://doi.org/10.1007/s12303-025-00083-8