Landslide susceptibility assessment (LSA) based on machine learning methods has been
widely used in landslide geological hazard management and research. However, the …

There is a need for geomorphology to integrate better with related disciplines, especially in
Critical Zone science. To help satisfy this integration, geomorphology's knowledge‐base …

Bivariate data-driven methods have been widely used in landslide susceptibility analysis.
However, the names, principles, and correlations of bivariate methods are still confused. In …

The overarching goal of the study was the development of a potentially dynamic rockfall
susceptibility model by including climate predictors. The work is based on previously defined …

Landslide is one of the most highly frequent natural hazards that can bring serious
casualties. One of the most susceptible landslide regions in Indonesia is Bogor area (the …

The Pemo Highway is a critical transportation road to Medog County in the Tibet Plateau
(TP). Since its completion in 2021, the Pemo Highway has been prone to frequent …

The selection of disaster-inducing factors and the construction of assessment models are
two important stages in landslide susceptibility assessment. Existing research has neglected …

Recently, machine learning models have received huge attention for environmental risk
modeling. One of these applications is landslide susceptibility mapping which is a necessary …

Landslides are among the most dangerous hazards in Asia, posing a significant threat to
human lives, infrastructure, and sustainable development. Landslide susceptibility maps …

Landslides, resulting from disturbances in slope equilibrium, pose a significant threat to
landscapes, infrastructure, and human life. Triggered by factors such as intense …