A prototype of a low-cost GNSS (Global Navigation Satellite System) monitoring system was installed on a deep-seated landslide in north-western Slovenia to test its performance under field conditions. The system consists of newly developed GNSS stations based on low-cost, dual-frequency receivers and open-source GNSS processing software. It automatically receives GNSS data and transmits them over the Internet. The system processes the data server-side and makes them available to the end user via a web portal. The detected surface displacements were evaluated through a comparison with the network of classic geodetic measurements. The results of a nine-month monitoring period using seven GNSS stations provided a detailed insight into the spatial and temporal pattern of deep-seated landslide surface movements. The displacement data were correlated with precipitation measurements at the site to reveal how different parts of the landslide react to rainfall. These data form the basis for the further development of an early-warning system which will help to manage the risk the landslide poses to the local population and infrastructure.

Detecting the mechanism of landslides and evaluating their dynamics is challenging, especially concerning composite landslides. For this purpose, several investigation and monitoring techniques should be implemented to obtain reliable information on landslide characteristics (e.g., geological and hydrogeological conditions and type of landslide processes), kinematics (displacement rate), and potential triggering mechanisms (e.g., change in groundwater table and precipitation). The Urbas landslide in northwest Slovenia has been studied for decades through geological, geotechnical, geodetic, and remote sensing investigations. However, due to the complexity of the landslide and the short duration of continuous monitoring, no assessment of its dynamics has been made. To meet this need, this study analysed continuous and periodic monitoring of landslide displacements using data from the global navigation satellite system (GNSS), a wire extensometer, unmanned aerial vehicle (UAV) photogrammetry, and hydrometeorological sensing (groundwater table, precipitation). The results of this study show that the dynamics of the Urbas landslide differ along the landslide area, depending on local geological and hydrogeological conditions. Consequently, certain parts of the landslide are at different evolutionary states and respond differently to the same external triggers.

The alpine environment is characterized by complex geology, high-energy terrain, deeply incised river valleys with high erosional potential, extreme weather conditions and dynamic geomorphic processes. Such settings provide favourable conditions for the formation of composite landslides rather than individual slope mass movement phenomena. As an example, we present the kinematics of the composite landslide Urbas in the North of Slovenia which developed in the complex geological and morphological settings characteristic of the alpine environment. The research combines several monitoring techniques and involves the integration of both surface and subsurface displacements measured in the landslide area. The results indicate that the composite sliding process consists of several simultaneous and interrelated types of movements occurring in different segments of the unstable mass that are governed by different mechanisms of displacements, such as rockfall, sliding and debris flow. The kinematic characteristics of a deep-seated landslide that formed in such conditions vary spatially, but is rather homogenuous vertically, indicating translational type of movement. Spatial kinematic heterogeneity is primarily related to the diverse terrain topography, reflecting in different displacement trends. Based on the revealed kinematic proprieties of the sliding material, the sediment discharge illustrates the sliding material balance which estimates the volume of the retaining material that represents the potential for slope mass movement events of larger scales.