Workshop Materials

GitHub

Workshop materials are online on GitHub:

https://github.com/UP-RS-ESP/PointCloudWorkshop-May2022

CloudCompare tutorials

Data sets

For the practical of the 20th June, link to the ALS and TLS data:

https://filesender.renater.fr/?s=download&token=a7b405a3-4830-42a7-bf2e-13e1861e24ac

For the video tutorials:

The sample data set for the tutorials on CloudCompare can be downloaded here:

Hope_fault_NZ, NCALM 2014b.laz

The data set is a small part of the 2014 acquisition of the Marlborough faults in NZ (https://doi.org/10.5069/G9G44N75). The original, and complete dataset can be downloaded from OpenTopography. This data was later used in the Bernard, Lague and Steer, 2021 paper on landslide detection from point clouds.

Provided below is a subsample version of the above dataset (minimum point spacing of 50 cm) to simplify data manipulation:

Hope_fault_NZ,NCALM 2014b_sub.laz

Terrestrial LiDAR data (subsampled at 5 cm) used in the CANUPO tutorial (description in Lague et al., 2013 (M3C2):

cliff5cm_feb09

Videos

1.a CloudCompare for earth sciences and environmental point clouds

1.b CloudCompare: GUI, cloning, subsampling, segmentation, merging, saving, terminology

2. What's in a .las / .laz file?

3.a Scalar fields part 1

3.b Scalar fields part 2

4. Comparing point clouds

5. Raster DEM creation, simple meshing, normals and advanced Poisson reconstruction

6.a Earth and environmental point clouds classification

6.b Classification tutorial with CANUPO in CloudCompare, terrestrial LiDAR

6.c Rule based classification

Dimitri Lague Monday 20 9h30

The pdf of the presentation.

Practical with CloudCompare

ICP + quality control using M3C2

Survey 1 and survey 2

Hands-on ICP with CloudCompare

Practical with Python

Jupyter notebook

ROOM 1

3D landslide detection using CloudCompare

ROOM2

scene.ply

voxelized_watershed.py