This paper presents a broad overview, characterisation and visualisation of the role of 18
anthropogenic process types in triggering and influencing 21 natural hazards, and natural …

Digital elevation models (DEMs) are considered an imperative tool for many 3D visualization
applications; however, for applications related to topography, they are exploited mostly as a …

The present study aims to develop two hybrid models to optimize the factors and enhance
the predictive ability of the landslide susceptibility models. For this, a landslide inventory …

The current study aimed at evaluating the capabilities of seven advanced machine learning
techniques (MLTs), including, Support Vector Machine (SVM), Random Forest (RF) …

The machine-learning “black box” models, which lack interpretability, have limited
application in landslide susceptibility mapping. To interpret the black-box models, some …

Landslides are a common type of natural disaster that brings great threats to the human lives
and economic development around the world, especially in the Chinese Loess Plateau …

Decision tree-based classifier ensemble methods are a machine learning (ML) technique
that combines several tree models to produce an effective or optimum predictive model, and …

Hazards and disasters have always negative impacts on the way of life. Landslide is an
overwhelming natural as well as man-made disaster that causes loss of natural resources …

The main purpose of the present study is to use three state-of-the-art data mining
techniques, namely, logistic model tree (LMT), random forest (RF), and classification and …

Landslide is a natural hazard that results in many economic damages and human losses
every year. Numerous researchers have studied landslide susceptibility mapping (LSM) …