3DPointCloudToolBox contains general packages with state-of-the-art algorithms and dedicated functions for point cloud preprocessing, including the alignment of point clouds PointCloudAlignment and PointCloudComparison for point cloud comparison (point-to-point and point-to-surface). This library uses object-oriented programming under the MATLAB® environment, which enables the management of large datasets. The elementary brick is the object class PointCloud created with a series of properties useful for data treatment, which includes the point’s position (X; Y; Z), intensities (I), colors (R; G; B), normal vectors (Nx; Ny; Nz), etc. Other included properties are related to the spatial distribution of the points, such as Delaunay triangulation or voxel structure, Kd-tree. The 3DPointCloudToolBox contains specific postprocessing packages oriented toward rockfall (RockfallQuantification) or landslide (LandslideTracking under development) analysis.


3DPointCloudToolBox is a freeware developped at the Group Risk at the University of Lausanne. No warranty is made for the functioning of the software and no responsibility is assumed by in the use of this tool.


There is no formal ongoing support for this freely distributed public software. However, if you have any questions or suggestions, please contact dario.carrea@unil.ch


Here you can find more information of the methods use in the 3DPointCloudToolBox:

MATLAB Virtual Toolbox for Retrospective Rockfall Source Detection and Volume Estimation Using 3D Point Clouds: A Case Study of a Subalpine Molasse Cliff (Carrea et al. 2021)

Use of targets to track 3D displacements in highly vegetated areas affected by landslides (Franz et al. 2016)

Correction of terrestrial LiDAR intensity channel using Oren–Nayar reflectance model: An application to lithological differentiation (Carrea et al. 2016)