This paper presents an overview of the use of lineaments in landslide hazard mapping. The
lineaments are normally derived either from aerial photographs or satellite imagery. The …

Statistical learning theory is the basis of support vector machine (SVM) technique. This
technique in natural hazard assessment is getting extremely popular these days. It contains …

This study compares the landslide susceptibility maps from four application models,
namely,(1) the bivariate model of the Dempster–Shafer based evidential belief function …

Landslide susceptibility, hazards, and risks have been extensively explored and analyzed in
the past decades. However, choosing relevant conditioning factors in such analyses …

Globally, and in China, landslides constitute one of the most important and frequently
encountered natural hazard events. In the present study, landslide susceptibility evaluation …

A detailed landslide susceptibility map was produced using a logistic regression method
with datasets developed for a geographic information system (GIS). Known as one of the …

The main purpose of this study is to highlight the conceptual differences of produced
susceptibility models by applying different sampling strategies: from all landslide area with …

An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic
Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications …

Landslides are a common geologic hazard that disrupts the social and economic balance of
the affected society. Therefore, identifying zones prone to landslides is necessary for safe …

This work evaluates the performance of three machine learning (ML) techniques, namely
logistic regression (LGR), linear regression (LR), and support vector machines (SVM), and …