30 citations as recorded by crossref.

1. Predisposing Factors for Shallow Landslides in Alpine and Hilly/Apennines Environments: A Case Study from Piemonte, Italy E. Fedato et al.
2. Short range tracking of rainy clouds by multi-image flow processing of X-band radar data L. Mesin
3. Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data E. Leonarduzzi et al.
4. Predictive Power Evaluation of a Physically Based Model for Shallow Landslides in the Area of Oltrepò Pavese, Northern Italy R. Valentino et al.
5. A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale S. Zhang et al.
6. Failure characteristics of soft rock and overlying soil after excavation of adjacent hard rock considering the rainfall K. Li et al.
7. Probabilistic landslide ensemble prediction systems: lessons to be learned from hydrology E. Canli et al.
8. Prediction of the instability probability for rainfall induced landslides: the effect of morphological differences in geomorphology within mapping units K. Wang et al.
9. Modelling catchment‐scale shallow landslide occurrence and sediment yield as a function of rainfall return period C. Bovolo & J. Bathurst
10. Hydrological and geotechnical investigations of mass movements in an equatorial city (Yaoundé, Cameroon) B. Ngounou Ngatcha et al.
11. Sediment modelling with fine temporal and spatial resolution for a hilly catchment A. Elliott et al.
12. Spatial patterns of rainfall and shallow landslide susceptibility J. Minder et al.
13. Spatially distributed rainfall information and its potential for regional landslide early warning systems E. Canli et al.
14. Rainfall-induced landslides assessment in the Fengjie County, Three-Gorge reservoir area, China K. Wang & S. Zhang
15. Research on the Impact of Regional-Scale Soil Mechanics Parameter Disturbances on Rainfall Landslides Warning K. Wang et al.
16. aiNet- and GIS-based regional prediction system for the spatial and temporal probability of rainfall-triggered landslides C. Li et al.
17. A prototype system for space–time assessment of rainfall-induced shallow landslides in Italy L. Montrasio et al.
18. Statistical modelling of rainfall-induced shallow landsliding using static predictors and numerical weather predictions: preliminary results V. Capecchi et al.
19. Numerical Analysis of the Effect of Subgrid Variability in a Physically Based Hydrological Model on Runoff, Soil Moisture, and Slope Stability E. Leonarduzzi et al.
20. Preliminary establishment of a mass movement warning system for Taiwan using the soil water index C. Chen et al.
21. Spatial variations of landslide severity with respect to meteorological and soil related factors K. Dutta et al.
22. Influence of subsurface flow by Lidar DEMs and physical soil strength considering a simple hydrologic concept for shallow landslide instability mapping S. Kim et al.
23. Rainfall-induced shallow landslides: a model for the triggering mechanism of some case studies in Northern Italy L. Montrasio et al.
24. Comparison between different approaches to modeling shallow landslide susceptibility: a case history in Oltrepo Pavese, Northern Italy D. Zizioli et al.
25. Different Time-Increment Rainfall Prediction Models: a Machine Learning Approach Using Various Input Scenarios A. Rahimi et al.
26. Shallow landslides triggered by rainfalls: modeling of some case histories in the Reggiano Apennine (Emilia Romagna Region, Northern Italy) L. Montrasio et al.
27. Rainfall-induced shallow landslides and soil wetness: comparison of physically based and probabilistic predictions E. Leonarduzzi et al.
28. Integration of rainfall thresholds and susceptibility maps in the Emilia Romagna (Italy) regional-scale landslide warning system S. Segoni et al.
29. Assessment of Landslide Susceptibility of Physically Based Model Considering Characteristics of the Unsaturated Soil J. Kim & H. Park
30. Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides R. Greco & L. Pagano