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 …

Landslide inventories are in high demand for risk assessment of this natural hazard,
particularly in tropical mountainous regions. This research designed residual networks for …

In this paper, an inventory of the landslide that occurred in Karahacılı at the end of 2019 was
created and the pre-landslide conditions of the region were evaluated with traditional …

Rockfall poses risk to people, their properties and to transportation ways in mountainous
and hilly regions. This catastrophe shows various characteristics such as vast distribution …

In recent years, machine learning techniques have been increasingly applied to the
assessment of various natural disasters, including landslides and floods. Machine learning …

A detailed and state-of-the-art landslide inventory map including precise landslide location
is greatly required for landslide susceptibility, hazard, and risk assessments. Traditional …

The logistic regression (LR) and decision tree (DT) models are widely used for prediction
analysis in a variety of applications. In the case of landslide susceptibility, prediction …

Natural hazards have a great number of influencing factors. Machine-learning approaches
have been employed to understand the individual and joint relations of these factors …

Many automatic landslide detection algorithms are based on supervised classification of
various remote sensing (RS) data, particularly satellite images and digital elevation models …

Landslides are natural disasters that cause environmental and infrastructure damage
worldwide. They are difficult to be recognized, particularly in densely vegetated regions of …