Currently, researchers commonly use convolutional neural network (CNN) models for
landslide remote sensing image recognition. However, with the increase in landslide …

Against the backdrop of global warming and increased rainfall, the hazards and potential
risks of landslides are increasing. The rapid generation of a landslide inventory is of great …

Efficient and accurate landslide recognition is crucial for disaster prevention and post-
disaster rescue efforts. However, compared to machine learning, deep learning approaches …

A landslide is a kind of geological disaster with high frequency, great destructiveness, and
wide distribution today. The occurrence of landslide disasters bring huge losses of life and …

The recognition and mapping of landslide (RML) is an important task in hazard and risk
research and can provide a scientific basis for the prevention and control of landslide …

The traditional high-level remote landslide recognition efficiency which relies on the artificial
discrimination of geological experts is low. In this paper, an automatic landslide terrain …

Landslides are a type of frequent and widespread natural disaster. It is of great significance
to extract location information from the landslide in time. At present, most articles still select …

Currently, the application of remote sensing technology in landslide identification and
investigation is an important research direction in the field of landslides. To address the …

Traditional methods for landslide survey, whether field investigation or human remote
sensing-based interpretation approaches, all require considerable labour costs and expert …

Regional landslide identification is important for the risk management of landslide hazards.
The traditional methods of regional landslide identification were mainly conducted by a …