Machine-learning-based nowcasting of the Vögelsberg deep-seated landslide: why predicting slow deformation is not so easy

Landslides are one of the major weather-related geohazards. To assess their potential impact and design mitigation solutions, a detailed understanding of the slope processes is required. Landslide modelling is typically based on data-rich geomechanical models. Recently, machine learning has shown promising results in modelling a variety of...

Spatial assessment of probable recharge areas-investigating the hydrogeological controls of an active deep-seated gravitational slope deformation

Continuous and slow-moving deep-seated landslides entail challenges for the effective planning of mitigation strategies aiming at the reduction of landslide movements. Given that the activity of most of these landslides is governed by pore pressure variations within the shear zone, profound knowledge about their hydrogeological control is...

Integrated Monitoring of a Slowly Moving Landslide Based on Total Station Measurements, Multi-Temporal Terrestrial Laser Scanning and Space-Borne Interferometric Synthetic Aperture Radar

Continuous landslide monitoring is a crucial task for the management of natural hazards for identifying suitable mitigation measures, including nature-based solutions. In the present study, three monitoring techniques including (i) an automated tracking total station (ATTS), (ii) multi-temporal terrestrial laser scanning (TLS) and (iii) space...