This thesis addresses different aspects of spatial data handling in connection with investigations of large rockslides. As such, most of the research was carried out in a cross disciplinary and highly applied context. The focus of the thesis is on spatial data handling methodology which directly or indirectly can be used to support in rockslide investigations. Rockslide investigation is a comprehensive term covering all aspects of the evaluation process; from the initial planning of field investigations to data analysis and communication of final results. Central topics addressed in this thesis are; a) How data reduction affect the geometrical accuracy of digital terrain models b) How interactive geometric modelling and geovisualization can be used in complex rockslide investigations and c) How statistical analyses can be used to evaluate displacement measurements of unstable rock slopes. Digital terrain modelling forms an important component of the methodology used for rockslide investigations. The first subtopic addressed in this thesis is related to the construction of Triangulated Irregular Networks (TINs) from Light Detection and Ranging (LIDAR) data. As the LIDAR technology tends to generate large data volumes, the resulting terrain models are generally too large to be efficiently handled by ordinary workstations. Therefore, comparisons of various data reduction (decimation) methods were conducted. Their performances were evaluated by means of deviations from terrain models constructed from full datasets. Evaluation criteria included deviations in volume, surface area and elevation. The results showed that the method using a vertical point selection threshold combined with a data dependent triangulation had the overall best performance when tested on 30 different test datasets. The main objective of the geovisualization part of this thesis was to determine the geometric shapes and locations of potential basal sliding surfaces, for the Åknes rockslide in western Norway, along with the volumes of unstable rock associated with different sliding scenarios. The Åknes rockslide is one of the world's most investigated rockslides due to its potentially catastrophic consequences. A custom written geovisualization application for the Åknes investigation provided the visual context needed for data interpretation and interactive geometric modelling of sliding surfaces. This geovisualization approach enabled geoscientists to develop different sliding scenarios. A scenario putting the basal sliding surface at a depth of 105m to 115m below the topographic surface, delineating an unstable rock volume of 43 million m3, was considered as the most realistic. Statistical approaches for analyzing displacement measurements were also addressed in this thesis. Several methods including regression analysis, spectral analysis and hypothesis testing were demonstrated to measurements obtained from Global Positioning System (GPS), total stations and extensometers at the Åknes rockslide. Displacement measurements obtained from lasers and crackmeters at the Nordnes rockslide in Northern Norway were also analysed. As with the Åknes rockslide, the Nordnes rockslide has the potential for devastating consequences in terms tsunami generation. Consequently, thorough statistical analyses of the available displacement data are crucial in order to obtain accurate estimates for the displacement rates as well as for gaining insight into the sliding processes. Displacement data from both sites clearly showed seasonal variations but the overall long term displacements were regarded constant. Prediction intervals were derived from the current monitoring data from the Nordnes site. These prediction intervals are considered useful for evaluation of future displacement measurements.