Riverside landslides present a significant geohazard globally, posing threats to
infrastructure and human lives. In line with the United Nations' Sustainable Development …

This study performs a GIS-based landslide susceptibility assessment using a convolutional
neural network, CNN, in a study area of the Gorzineh-khil region, northeastern Iran. For this …

In the past few decades, digital technologies have played a more and more important role in
landslide disaster risk management. To identify the progress and future directions with …

Landslide susceptibility assessment is the globally approved procedure to prepare geo-
hazard maps of landslide-prone areas, which are highly used in urban management and …

The hydrological system of thebasin of Lake Urmia is complex, deriving its supply from a
network comprising 13 perennial rivers, along withnumerous small springs and direct …

Landslide susceptibility assessment (LSA) based on machine learning methods has been
widely used in landslide geological hazard management and research. However, the …

Rainfall-induced landslides cause frequent disruptions to critical infrastructure in
mountainous countries. Climate change is altering rainfall patterns and localizing extreme …

At 17: 00 (UTC+ 8) on 1 June 2022, an Ms 6.1 reverse earthquake struck Lushan County,
Ya'an City, Sichuan Province. This earthquake event had a focal depth of 10 km and the …

The construction of the Three Gorges Reservoir (TGR) has considerably increased landslide
hazard due to the 30-m annual fluctuating reservoir water level. In this study, the influence of …

Displacement prediction is critical for the early detection of landslides, and the empirical,
statistical, and machine learning models have been commonly used. In the Three Gorges …