Due to their intense concealment and tremendous destructiveness during the course of their
lengthy growth, landslides are difficult to monitor. Landslide data gathering exhibits traits …

The analysis of landslides using monitoring data is a commonly used method for landslide
prediction and early warning. However, the loss of data due to breakdown of the monitoring …

Slope stability analysis based on the deformation monitoring data has been commonly used
to predict and warn slope disasters. However, due to breakdown of the monitoring …

Effective landslide hazard prevention requires accurate landslide prediction models, and the
data-driven approaches based on deep learning models are gradually becoming a hot …

The accurate prediction of displacement is crucial for landslide deformation monitoring and
early warning. This study focuses on a landslide in Wenzhou Belt Highway and proposes a …

Geospatial interpolation plays a pivotal role in spatial analysis because it provides high-
quality data support for various spatiotemporal data mining (STDM) tasks. However …

The widely distributed “Step-type” landslides in the Three Gorges Reservoir (TGR) area
have caused serious casualties and heavy economic losses. The prediction research of …

Landslide disasters cause serious property losses and casualties every year. Landslide
displacement prediction is fundamental for mitigating landslide disasters. Several …

Spatial interpolation techniques are a powerful tool for generating visually continuous
surfaces from scattered point data, and the accuracy of interpolation determines the practical …

Monitoring landslide displacement is critical towards understanding kinematics and
evaluating risk. Both remote sensing technology and in-situ sensors are currently used for …