9 citations as recorded by crossref.

1. Reforecasting Two Heavy-Precipitation Events with Three Convection-Permitting Ensembles V. Capecchi https://doi.org/10.1175/WAF-D-20-0130.1
2. From Rainfall to Absolute Landslide Probability: A Machine Learning–Based Approach J. Jin et al. https://doi.org/10.1061/NHREFO.NHENG-2545
3. Development of a data-driven model for spatial and temporal shallow landslide probability of occurrence at catchment scale M. Bordoni et al. https://doi.org/10.1007/s10346-020-01592-3
4. Risk Factor Detection and Landslide Susceptibility Mapping Using Geo-Detector and Random Forest Models: The 2018 Hokkaido Eastern Iburi Earthquake Y. Liu et al. https://doi.org/10.3390/rs13061157
5. Assessment of Ground Instabilities’ Causative Factors Using Multivariate Statistical Analysis Methods: Case of the Coastal Region of Northwestern Rif, Morocco H. Tribak et al. https://doi.org/10.3390/geosciences12100383
6. A Hybrid Variable Weight Theory Approach of Hierarchical Analysis and Multi-Layer Perceptron for Landslide Susceptibility Evaluation: A Case Study in Luanchuan County, China M. Li et al. https://doi.org/10.3390/su15031908
7. GIS-based comparative study of Bayes network, Hoeffding tree and logistic model tree for landslide susceptibility modeling W. Chen & S. Zhang https://doi.org/10.1016/j.catena.2021.105344
8. A novel dynamic rockfall susceptibility model including precipitation, temperature and snowmelt predictors: a case study in Aosta Valley (northern Italy) G. Bajni et al. https://doi.org/10.1007/s10346-023-02091-x
9. Evaluation of landslide susceptibility based on VW-AHP-IV model: a case of Pengyang County, Ningxia, China M. Li et al. https://doi.org/10.1007/s12665-023-10787-5