In complex and heterogeneous geoenvironments, landslides exhibit varying features in
different environments, and data in landslide inventories are imbalanced. Existing data …

In this study, the future landslide population amount risk (LPAR) is assessed based on
integrated machine learning models (MLMs) and scenario simulation techniques in …

In recent years, scholars worldwide have achieved significant scientific advancements in
landslide research, particularly in urban planning. However, few have systematically …

Differences in model application effectiveness, insufficient numbers of disaster samples, and
unreasonable selection of non-hazard samples are common problems in landslide …

A landslide susceptibility map (LSM) is the basis of hazard and risk assessment, guiding
land planning and utilization, early warning of disaster, etc. Researchers are often overly …

In Romania, local stakeholders' knowledge plays a decisional role in emergencies,
supporting rescue officers in natural hazard events, coordinating and assisting, both …

The representation of terrain propensity to generate landslides, meaning the mapping of
landslide susceptibility, represents a first step in the assessment of the risk induced by these …

The multidisciplinary approach outlined in this paper aims to assess the correlation between
geophysical and social vulnerability for disaster risk reduction. To achieve this, two multi …

Global warming increases the frequency and intensity of extreme rainfall, putting many
areas at risk of landslides. Landslide susceptibility assessment is essential to understand …

The aim of the present study was to assess differences in the conditioning factors and the
performance of landslide susceptibility mapping (LSM), employing the SHapley Additive …