Landslide susceptibility assessment is highly valuable for disaster prevention and mitigation.
This study utilized the aspects of data and content to comprehensively examine the research …

To assess the status of hotspots and research trends on geographic information system
(GIS)–based landslide susceptibility (LS), we analysed 1142 articles from the Thomas …

Groundwater recharge is affected by various anthropogenic activities, land use and land
cover (LULC) change among these. The long-term temporal and seasonal changes in LULC …

This study attempts to identify the essential conditioning factors of landslides to increase the
predictive ability of landslide susceptibility models and explore the effects of different grid …

Abstract “Spatial contraindication” is what exactly landslide susceptibility models have been
seeking. They are designed for depicting perilous land activities, be it natural or …

Gully erosion is identified as an important sediment source in a range of environments and
plays a conclusive role in redistribution of eroded soils on a slope. Hence, addressing …

A new work-flow is proposed to unify the way the community shares Logistic Regression
results for landslide susceptibility purposes. Although Logistic Regression models and …

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

The main purpose of this paper is to explore some potential applications of sophisticated
machine learning techniques such as the kernel logistic regression, Naïve-Bayes tree and …

Abstract The Ziarat Watershed, located in the south of the Golestan Province, Iran, has
witnessed several destructive landslide episodes, prompting a number of researchers to …