Tree Stem Shapes Derived from TLS Data as an Indicator for Shallow Landslides

Abstract Landslides or other forms of mass movement influence slope stability, and are known to have significant effects on vegetation patterns. Observation of such surface patterns may result in valuable information for understanding the kinematics of the landslide. In forested regions, tree growth anomaly is often served as an indicator of shallow landslide activity. Terrestrial laser scanning (TLS) is able to acquire accurate and dense 3D point cloud which provides the potential of reconstructing forest structure. In this study, we obtained high density TLS data in the northern Walgau in the federal state of Vorarlberg in Austria, where translational mass movement phenomenon exists in a forested region. A novel algorithm was developed to fast and robustly characterize single tree parameters (e.g. diameter at breast height (DBH), inclination angle of the stem and stem volume). Consequently, these tree parameters were successfully determined at single tree level. Field measurements were conducted in order to validate the results from the modelling algorithm. The root mean square error of DBH is 1.6 cm (4.9%). The average stem inclination angle is 8.2°. The results of this study revealed that characterization of trees (i.e. inclination of the stems) can be used to indicate shallow landslide activities in forested regions. The quantification of tree parameters could also contribute to a better understanding of the interaction between landslides and trees.