Forecasting the time of failure of landslides at slope-scale is a difficult yet important task that
can mitigate the effects of slope failures in terms of both human lives and economic losses …

Landslide is one of the repeated geological hazards during rainy season, which causes
fatalities, damage to property and economic losses in Korea. Landslides are responsible for …

Abstract Machine learning algorithms are an important measure with which to perform
landslide susceptibility assessments, but most studies use GIS-based classification methods …

Rainfall-induced landslides represent an important threat in mountainous areas. Therefore,
a physically-based model called “Fast Shallow Landslide Assessment Model”(FSLAM) was …

The influence of vegetation on mechanical and hydrological soil behavior represents a
significant factor to be considered in shallow landslides modelling. Among the multiple …

In recent decades, data-driven landslide susceptibility models (DdLSM), which are based on
statistical or machine learning approaches, have become popular to estimate the relative …

Shallow slope failures triggered by rainfall commonly pose considerable risks in
mountainous areas. In order to delineate areas where landslides are more prone to occur …

Abstract Slope Stability Models (SSMs) are valuable tools used as decision support in land
management to mitigate catastrophic effects caused by rainfall-induced shallow landslides …

Shallow, rainfall-triggered landslides are an important catchment process that affect the rate
and calibre of sediment within river networks and create a significant hazard, particularly …

Soil thickness, intended as depth to bedrock, is a key input parameter for many
environmental models. Nevertheless, it is often difficult to obtain a reliable spatially …