8 citations as recorded by crossref.

1. A novel deep learning framework for landslide susceptibility assessment using improved deep belief networks with the intelligent optimization algorithm S. Meng et al. 10.1016/j.compgeo.2024.106106
2. Landslide topology uncovers failure movements K. Bhuyan et al. 10.1038/s41467-024-46741-7
3. Assessing the impact of climate change on landslides near Vejle, Denmark, using public data K. Svennevig et al. 10.5194/nhess-24-1897-2024
4. The ITAlian rainfall-induced LandslIdes CAtalogue, an extensive and accurate spatio-temporal catalogue of rainfall-induced landslides in Italy S. Peruccacci et al. 10.5194/essd-15-2863-2023
5. Aerial Data Analysis for Integration Into a Green Cadastre—An Example From Aarhus, Denmark J. Knopp et al. 10.1109/JSTARS.2023.3289218
6. A review on landslide susceptibility mapping research in Bangladesh M. Chowdhury 10.1016/j.heliyon.2023.e17972
7. Global landslide susceptibility prediction based on the automated machine learning (AutoML) framework G. Tang et al. 10.1080/10106049.2023.2236576
8. Landslide Susceptibility Mapping Using Machine Learning: A Danish Case Study A. Ageenko et al. 10.3390/ijgi11060324