Landslide susceptibility map** (LSM) has been widely used as an important reference for
development and construction planning to mitigate the potential social‐eco impact caused …

In the 21st Century, disasters have severe negative impacts on cities worldwide. Given the
significant casualties and property damage caused by disasters, it is necessary for disaster …

The frequency of landslides and related economic and environmental damage has
increased in recent decades across the hilly areas of the world, no exception is Bangladesh …

Abstract Machine learning methods require a vast amount of data to train a model. The data
necessary for landslide susceptibility map** is a collection of landslide causative factors …

Precipitation is the main factor that triggers landslides. Rainfall-induced landslide
susceptibility map** (LSM) is crucial for disaster prevention and disaster losses mitigation …

Landslide susceptibility map** (LSM) comprehensively evaluates the spatial probability of
landslide occurrence by using different environmental factors. However, most of the …

In this study, a landslide susceptibility assessment is performed by combining two machine
learning regression algorithms (MLRA), such as support vector regression (SVR) and …

The hydrological system of thebasin of Lake Urmia is complex, deriving its supply from a
network comprising 13 perennial rivers, along withnumerous small springs and direct …

Riverbank erosion is one of the most catastrophic hazards that renders floodplains
vulnerable across the world vulnerable. It creates a significant negative impact on the …