15 citations as recorded by crossref.

1. PROMICE-2022 ice mask: a high-resolution outline of the Greenland Ice Sheet from August 2022 G. Luetzenburg et al. https://doi.org/10.5194/essd-18-411-2026
2. Size scaling of large landslides from incomplete inventories O. Korup et al. https://doi.org/10.5194/nhess-24-3815-2024
3. Assessing the impact of climate change on landslides near Vejle, Denmark, using public data K. Svennevig et al. https://doi.org/10.5194/nhess-24-1897-2024
4. A review on landslide susceptibility mapping research in Bangladesh M. Chowdhury https://doi.org/10.1016/j.heliyon.2023.e17972
5. Global landslide susceptibility prediction based on the automated machine learning (AutoML) framework G. Tang et al. https://doi.org/10.1080/10106049.2023.2236576
6. A novel deep learning framework for landslide susceptibility assessment using improved deep belief networks with the intelligent optimization algorithm S. Meng et al. https://doi.org/10.1016/j.compgeo.2024.106106
7. Unified Global Landslide Catalogue (UGLC): a single, standardised global-scale landslide dataset S. Mancino et al. https://doi.org/10.5194/essd-18-4697-2026
8. Landslide topology uncovers failure movements K. Bhuyan et al. https://doi.org/10.1038/s41467-024-46741-7
9. Construction of landslide relics inventory and analysis of its spatial distribution characteristics in Nyingchi, China Z. Xiao et al. https://doi.org/10.1007/s11707-025-1195-5
10. The ITAlian rainfall-induced LandslIdes CAtalogue, an extensive and accurate spatio-temporal catalogue of rainfall-induced landslides in Italy S. Peruccacci et al. https://doi.org/10.5194/essd-15-2863-2023
11. 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
12. LMHLD: A Large-Scale Multisource High-Resolution Landslide Dataset for Landslide Detection Based on Deep Learning G. Liu et al. https://doi.org/10.1109/TGRS.2025.3619062
13. Event-driven erosion of a glacial till cliff J. Rossius et al. https://doi.org/10.1016/j.geomorph.2025.109626
14. Aerial Data Analysis for Integration Into a Green Cadastre—An Example From Aarhus, Denmark J. Knopp et al. https://doi.org/10.1109/JSTARS.2023.3289218
15. Sustainable Landslide Risk Assessment in Zonguldak Province Using AHP and Artificial Intelligence: Integration with InSAR and Inventory Data S. Kutoglu & D. Arca https://doi.org/10.3390/su18094263