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We will present a series of new integrated 3D models of landslide sites that were investigated in distinctive seismotectonic and climatic contexts: (1) along the Hockai Fault Zone in Belgium and (2) in the seismic region of Vrancea, Romania. Both sites are deep-seated failures located in more or less seismically active areas. In such areas, slope stability analyses have to take into account the possible contributions to ground failure. Our investigation methods had to be adapted to capture the deep structure as well as the physico-mechanical characteristics that influence the dynamic behaviour of the landslide body. Field surveys included electrical resistivity tomography profiles, seismic refraction profiles (analysed in terms of both seismic P-wave tomography and surface waves), ambient noise measurements to determine the soil resonance frequencies through H/V analysis, complemented by geological and geomorphic mapping. The H/V method, in particular, is more and more used for landslide investigations or sites marked by topographic relief (in addition to the more classical applications on flat sites). Results of data interpretation were compiled in 3D geological-geophysical models supported by high resolution remote sensing data of the ground surface. Data and results were not only analysed in parallel or successively; to ensure full integration of all inputs-outputs, some data fusion and geostatistical techniques were applied to establish closer links between them. Inside the 3D models, material boundaries were defined in terms of surfaces and volumes. Those were implemented in 2D and 3D numerical dynamic models (presented in a companion paper).

Figure 1: Camera setup optimization sequence for a five sided CAVE with four cameras. The camera positions were constrained to remain on the open top side of the CAVE. Notice the increased point sample density in head height to improve the head-tracking robustness. ABSTRACTWe propose a method to determine the optimal camera alignment for a tracking system with multiple cameras by specifying the volume to be tracked and an initial camera setup. We use optimization strategies based on methods usually employed for solving nonlinear systems of equations. All approaches are fully automatic and take advantage of modern graphics hardware since we also implement a GPU-based, accelerated visibility test. The algorithm automatically optimizes the whole setup by adjusting the given set of camera parameters. We can steer the optimization towards different goals depending on the desired application, e.g. the widest possible volume coverage or maximum camera visibility to overcome heavy occlusion problems during the tracking process. We also consider parameter constraints that the user may specify according to restrictions in the local environment where the cameras have to be mounted. This allows for a convenient definition of higher level constraints for the camera setup.

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In this application paper we'll explain the work flow we use to create immersive visualizations and spatial interaction for geophysical data with a head mounted device (HMD). The data that we analyze consists of two dimensional geographical map data and raw geophysical measurements with devices like seismometers, Electrical Resistivity Tomography (ERT) and seismic tomography profiles as well as other geophysical and geoscientific data. We show the tool chain that we use while explaining the choices that we made along the way. The technical description will be followed by a brief assessment of the added benefit of rendering our data in virtual reality (VR). After the technical description we conclude this paper with some outlook on the (likely) future use of VR in geosciences.