The Himalayan region and hilly areas face severe challenges due to landslide occurrences
during the rainy seasons in India, and the study area, ie, the Rudraprayag district, is no …

Earthquake-induced landslides (EQL) can take a heavy toll on people's life and properties,
thus attracting extensive attention of the geosciences community. Carrying out earthquake …

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

In this study, we developed multiple hybrid machine-learning models to address parameter
optimization limitations and enhance the spatial prediction of landslide susceptibility models …

This study aims to evaluate a new approach in modeling gully erosion susceptibility (GES)
based on a deep learning neural network (DLNN) model and an ensemble particle swarm …

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 …

The main goal of this study is to produce landslide susceptibility maps of a landslide-prone
area (Haraz) in Iran by using both fuzzy logic and analytical hierarchy process (AHP) …

Over the last few decades, many researchers have produced landslide susceptibility maps
using different techniques including the probability method (frequency ratio), the analytical …

Abstract The Mugling–Narayanghat road section falls within the Lesser Himalaya and
Siwalik zones of Central Nepal Himalaya and is highly deformed by the presence of …

We present a hybrid intelligent approach based on Naïve Bayes trees (NBT) and random
subspace (RS) ensemble for landslide susceptibility mapping at the Bijar region, Kurdistan …