Due to the similarity of conditioning factors, the aggregation feature of landslides and the
multi-temporal landslide inventory, the spatial and temporal effects of landslides need to be …

Landslides often happen where they have already occurred in the past. The potential of
landslides to reduce or enhance conditions for further landsliding has long been recognized …

The standard definition of landslide hazard requires the estimation of where, when (or how
frequently) and how large a given landslide event may be. The geoscientific community …

Landslide susceptibility models are fundamental components of landslide risk management
strategies. These models typically assume that landslide occurrence is time‐independent …

Abstract The Hengduan Mountains Region (HMR) is one of the areas that experience the
most frequent geological hazards in China. However, few reports are available that address …

A combined method was developed to forecast the spatial and the temporal probability of
occurrence of rainfall-induced shallow landslides over large areas. The method also …

Various data-driven methods, including empirical, statistical, and machine learning methods,
have been developed to promptly forecast rain-induced landslides. Their abilities differ …

The slip surface is an important structure for analyzing the landslide mechanism, and it will
be deformed by the traction and shear of the slide mass. For the landslide accident without …

Machine learning models have been widely used for landslide susceptibility assessment
(LSA) in recent years. The large number of the inputs or conditioning factors for these …

There is a clear need to improve and update landslide susceptibility models across the
Philippines. This is challenging, as landslides in this region are frequently triggered by …