Landslide occurrence has become increasingly influenced by human activities. Accordingly,
changing land use and land cover (LULC) is an important conditioning factor in landslide …

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 …

With the increasing threat of recurring landslides, susceptibility maps are expected to play a
bigger role in promoting our understanding of future landslides and their magnitude. This …

Estimation of landslide susceptibility is still an ongoing requirement for land use
management plans. Here, we proposed two novel intelligence hybrid models that rely on an …

Using multiple ensemble learning techniques for improving the predictive accuracy of
landslide models is an active research area. In this study, we combined a radial basis …

The main aim of this study is to propose a novel hybrid intelligent model named MBSVM
which is an integration of the MultiBoost ensemble and a support vector machine (SVM) for …

In this study, we have developed five spatially explicit ensemble predictive machine learning
models for the landslide susceptibility mapping of the Van Chan district of the Yen Bai …

Abstract Knowledge of wildfire behavior is of key importance for planning and allocating
resources to fire suppression efforts. In this study, we analyzed the spatial pattern of wildfires …

Landslide susceptibility mapping is among the first works for disaster management and land
use planning activities in a mountain area like Ganzhou City. The aims of the current study …

This study presents an analysis of the influence of general landscape-level indicators on
wildfire and its spatial susceptibility across a fire-prone landscape in the southeast of China …