As laser scanning technology has improved a lot in recent years, terrestrial laser scanners (TLS) have become popular devices for surveying tasks with high accuracy demands, such as deformation analyses. For this reason, finding a stochastic model for TLS measurements is very important in order to get statistically reliable results. The measurement accuracy of laser scanners—especially of their rangefinders—is strongly dependent on the scanning conditions, such as the scan configuration, the object surface geometry and the object reflectivity. This study demonstrates a way to determine the intensity-dependent range precision of 3D points for terrestrial laser scanners that measure in 3D mode by using range residuals in laser beam direction of a best plane fit. This method does not require special targets or surfaces aligned perpendicular to the scanner, which allows a much quicker and easier determination of the stochastic properties of the rangefinder. Furthermore, the different intensity types—raw and scaled—intensities are investigated since some manufacturers only provide scaled intensities. It is demonstrated that the intensity function can be derived from raw intensity values as written in literature, and likewise—in a restricted measurement volume—from scaled intensity values if the raw intensities are not available.

This article investigates the usage of terrestrial laser scanner (TLS) point clouds for monitoring the gradual movements of soil masses due to freeze–thaw activity and water saturation, commonly referred to as solifluction. Solifluction is a geomorphic process which is characteristic for hillslopes in (high-)mountain areas, primarily alpine periglacial areas and the arctic. The movement can reach millimetre-to-centimetre per year velocities, remaining well below the typical displacement mangitudes of other frequently monitored natural objects, such as landslides and glaciers. Hence, a better understanding of solifluction processes requires increased spatial and temporal resolution with relatively high measurement accuracy. To that end, we developed a workflow for TLS point cloud processing, providing a 3D vector field that can capture soil mass displacement due to solifluction with high fidelity. This is based on the common image-processing techniques of feature detection and tracking. The developed workflow is tested on a study area placed in Hohe Tauern range of the Austrian Alps with a prominent assemblage of solifluction lobes. The derived displacements were compared with the established geomonitoring approach with total station and signalized markers and point cloud deformation monitoring approaches. The comparison indicated that the achieved results were in the same accuracy range as the established methods, with an advantage of notably higher spatial resolution. This improvement allowed for new insights considering the solifluction processes.

The perfect knowledge about the scanned object’s geometry is essential for the empirical analysis of the stochastic properties of terrestrial laser scanners (TLSs). The Bonn reference wall is intended to be used as a reference for TLS quality investigations. Therefore, it is necessary to know the geometry of the wall at each time of scanning to avoid the misinterpretation of possible movements as systematic effects in the scanner. For this reason, we investigate the stability of the Bonn reference wall in this study. This includes the definition of a geodetic datum, the quantification of displacements, and the establishment of a suited deformation model. Since we discover a movement of about 1 mm within one day and up to 7 mm over the year, it is necessary to establish a cause-response deformation model to correct the wall movements in the scans. This study proposes two dynamic deformation models to compensate for the movements of the wall within one day and within a year. Our results show that it is better to measure the initial geometry of the wall each day since 89 % of the relative movements can be reduced to a maximum of 0.25 mm with a standard deviation of 0.16 mm (0.23 mm without modeling). If the shape is not initially known each day, the standard deviation of the displacements can be reduced from 1.10 mm to 0.61 mm, but the largest residuals still amount up to 2.5 mm, which is not sufficient for stochastic TLS investigations.