Multi-platform remote sensing using space-, airborne and ground-based sensors has
become essential tools for landslide assessment and disaster-risk prevention. Over the last …

In this study, we used an Unmanned Aerial Vehicle (UAV) to collect a time series of high-
resolution images over four years at seven epochs to assess landslide dynamics. Structure …

Data-driven landslide susceptibility models formally integrate spatial landslide information
with explanatory environmental variables that describe predisposing factors of slope …

Landslide susceptibility maps are helpful tools to identify areas potentially prone to future
landslide occurrence. As more and more national and provincial authorities demand for …

Empirical models are frequently applied to produce landslide susceptibility maps for large
areas. Subsequent quantitative validation results are routinely used as the primary criteria to …

A precise, accurate and complete landslide inventory is indispensable for the establishment
of reliable landslide susceptibility and hazard maps. In the preparation of landslide …

Predictive spatial modelling is an important task in natural hazard assessment and
regionalisation of geomorphic processes or landforms. Logistic regression is a multivariate …

The reliability of input data to be used within statistically based landslide susceptibility
models usually determines the quality of the resulting maps. For very large territories …

Complete landslide inventories are rarely available. The objectives of this study were to (i)
elaborate the influence of incomplete landslide inventories on statistical landslide …

Geohazard recognition and inventory mapping are absolutely the keys to the establishment
of reliable susceptibility and hazard maps. However, it has been challenging to implement …