Upon the introduction of machine learning (ML) and its variants, in the form that we know
today, to the landslide community, many studies have been carried out to explore the …

The design, implementation, management, and verification of landslide early warning
systems (LEWSs) are gaining increasing attention in the literature and among government …

The intensity of extreme precipitation events is projected to increase in a warmer climate,,,–,
posing a great challenge to water sustainability in natural and built environments. Of …

Rainfall-induced landslide hazard warning, which refers to the prediction of the spatial-
temporal probability of landslide occurrence in a certain area under the conditions of …

Worldwide, landslides incur catastrophic and significant economic and human losses.
Previous studies have characterized the patterns in landslides' fatalities, from all kinds of …

Determining the time, location, and severity of natural disaster impacts is fundamental to
formulating mitigation strategies, appropriate and timely responses, and robust recovery …

Precipitation represents a life‐critical energy and hydrologic exchange between the Earth's
atmosphere and its surface. As such, knowledge of where, when and how much rain and …

Landslides affect nearly every country in the world each year. To better understand this
global hazard, the Landslide Hazard Assessment for Situational Awareness (LHASA) model …

Satellite rainfall products have been available for many years (since'90) with an increasing
spatial/temporal resolution and accuracy. Their global scale coverage and near real-time …

This paper studies, designs and implements a new type of emergency decision support
system that aims to improve the decision-making of emergency managers in crisis situations …