Fully supervised machine learning models are widely applied for landslide susceptibility
prediction (LSP), mainly using landslide and non-landslide samples as output variables and …

Pipelines are a critical component of transportation infrastructure. They offer the safest and
most efficient way to transport large volumes of oil and natural gas from development areas …

Effective utilization of reservoirs facilitates the distribution of water resources in both time
and space, providing strong support for the sustainable growth of the economy and society …

Early detection of landslides is important for prevention and mitigation of landslide disasters.
Especially, accurately identifying potential landslides along high‐speed railway is becoming …

The prediction of landslide deformation is an important part of landslide early warning
systems. Displacement prediction based on geotechnical in-situ monitoring performs well …

Landslides, ubiquitous geological hazards on steep slopes, present formidable challenges
in tropical regions with dense rainforest vegetation, impeding accurate mapping and risk …

This study presents a novel method for assessing landslide hazards along highways using
remote sensing and machine learning. We extract geospatial features such as slope, aspect …

Landslides frequently cause serious property damage and casualties. Therefore, it is crucial
to have rapid and accurate landslide mapping (LM) to support post-earthquake landslide …

Landslides caused by mega earthquakes and other extreme climate change pose a major
threat to lives and infrastructure. However, the lack of a detailed and timely landslide …

High spectral resolution imagery of the Earth's surface enables users to monitor changes
over time in fine-grained scale, playing an increasingly important role in agriculture …