This study is an attempt to quantitatively test and compare novel advanced-machine
learning algorithms in terms of their performance in achieving the goal of predicting flood …

This analysis aims to generate landslide susceptibility maps (LSMs) using various machine
learning methods, namely random forest (RF), alternative decision tree (ADTree) and …

Landslides are among the most harmful natural hazards for human beings. This study aims
to delineate landslide hazard zones in the Darjeeling and Kalimpong districts of West …

The objective of this study is to assess the gully head-cut erosion susceptibility and identify
gully erosion prone areas in the Meimand watershed, Iran. In recent years, this study area …

Gully erosion is a disruptive phenomenon which extensively affects the Iranian territory,
especially in the Northern provinces. A number of studies have been recently undertaken to …

Landslide is one of the most important geomorphological hazards that cause significant
ecological and economic losses and results in billions of dollars in financial losses and …

In this study, a novel approach of the landslide numerical risk factor (LNRF) bivariate model
was used in ensemble with linear multivariate regression (LMR) and boosted regression …

Rapid population growth and its corresponding effects like the expansion of human
settlement, increasing agricultural land, and industry lead to the loss of forest area in most …

The morphometric characteristics of the Kalvārī basin were analyzed to prioritize sub-basins
based on their susceptibility to erosion by water using a remote sensing-based data and a …

Gully erosion is a form of natural disaster and one of the land loss mechanisms causing
severe problems worldwide. This study aims to delineate the areas with the most severe …