In recent decades, data-driven landslide susceptibility models (DdLSM), which are based on
statistical or machine learning approaches, have become popular to estimate the relative …

Background This paper reviews the classical and some particular factors contributing to
earthquake-triggered landslide activity. This analysis should help predict more accurately …

Landslide initiation and dynamics are approached with different methods according to the
scale of investigation. Individual landslides are typically described mechanistically, relying …

Rockslides and Rock Avalanches of Central Asia: Distribution, Impacts, and Hazard
Assessment arms scientists with an inclusive and specialized reference for future studies of …

Data-driven landslide susceptibility models (LSM) have been widely used to spatially predict
areas likely affected by landslides. Even though such approaches are used to estimate the …

Moderate-relief landscapes, such as the Czech Flysch Outer Western Carpathians (COWC),
in comparison with alpine regions are rarely subject to extensive landslide inventory …

Predicting landslide occurrence is of key importance for understanding the
geomorphological development of mountain environments as well as to assess the potential …

Electronic databases of landslides seldom include the triggering mechanisms, rendering
these inventories unusable for landslide hazard modeling. We present a method for …

In this paper we present new and review already existing landslide and earthquake data for
a large part of the Tien Shan, Central Asia. For the same area, only partial databases for sub …

Whilst correlations have been made between the loess of Europe and China, deposits in
Central Asia have remained largely overlooked by scientific investigation. The nature of the …