3D data are more and more available and used in earth sciences for a large variety of purposes (glacial changes, forestry, erosion in rivers, changes of land use, sediment transport, landslides, etc). A large variety of methods are now available to acquire such data on the field (terrestrial or airborne LiDAR, photogrammetry from drones or cameras). Our team has developed two plugins freely available in CloudCompare to process point clouds: 3DMASC (Letard et al, 2023) for general purpose classification, and G3Point (Steer et al, 2023) for grain segmentation and features extraction. In this short course, participants will learn how to efficiently use 3DMASC to classify fluvial environments (typically vegetation, rock and sediments) and then apply G3Point on sediments to segment grains and extract their geometries (size, orientation). Workshop material: TLS data set acquired along a fluvial reach (small bedrock gorges and an alluvial bar) provided to the participants.