Working with Point Clouds in CloudCompare and Classifying with CANUPO
Summary
This exercise will walk you through 1) basic operations and use in CloudCompare, and 2) use of an Open-Source plugin in CloudCompare called CANUPO (http://nicolas.brodu.net/en/recherche/canupo/) that allows for point cloud classification. This unit can be used with any point cloud dataset. An optional activity imports rasters created in CloudCompare and conducts additional analyses in ESRI ArcGIS. This assignment follows Structure from Motion for Analysis of River Characteristics and uses an open source software, CloudCompare (https://www.danielgm.net/cc/) that allows for viewing and manipulation of point clouds.
Day 4 - This activity is part of the 2-week remote field course Geoscience Field Issues Using High-Resolution Topography to Understand Earth Surface Processes
In spring 2020, the world was hit by a pandemic that spread globally by March, causing universities and most of the world to move to remote means. Summer field camps, long hailed as a rite of passage in the geosciences, were canceled throughout the US. The community moved quickly, with NAGT developing remote learning tools and arranging for sharing and collaboration between instructors and institutions. As such, UNAVCO (GETSI) and University of Northern Colorado embarked on a data collection campaign for a summer field course entitled "Geoscience Field Issues Using High-Resolution Topography to Understand Earth Surface Processes" – originally slated for in-person teaching. The team collected GNSS data, drone imagery for use in structure from motion, and terrestrial laser scanning from a site near Greeley, Colorado on the Poudre River.
Context
Audience
This exercise is intended for majors-level geoscience courses that have field or remote (online) field components.
Skills and concepts that students must have mastered
This exercise assumes students have some familiarity with high-resolution topographic data in point cloud format. It is helpful if students have some background in geomorphology and/or physical geography concepts.
How the activity is situated in the course
This activity is the fourth component of a virtual field campaign and associated activities outlined in the course Geoscience Field Issues Using High-Resolution Topography to Understand Earth Surface Processes. This exercise follows an introduction to SfM (Getting started with Structure from Motion (SfM) photogrammetry), GPS/GNSS georeferencing (Post-processing GPS/GNSS Base Station Position and Ground Control Points for Structure from Motion), and a more in depth SfM exercise (Structure from Motion for Analysis of River Characteristics).
Activity Length
This takes about two hours. The optional "Working with Rasters in ArcGIS" activity would take about another hour. The instructor gives an introduction to the activity and CloudCompare software. This could be conducted synchronously remotely, such as in Zoom. Alternatively, and in-person implementation could be completed using screen share. Students then work independently to complete the exercise.
Goals
Content/concepts goals for this activity
- Classify a point cloud using a trained classifier
Higher order thinking skills goals for this activity
- Use a point cloud to take measurements of geomorphic features to test a hypothesis
- Assess strengths and weaknesses of a classification and resulting products
Other skills goals for this activity
- Create derivative products such as digital terrain model, slope, and hillshade rasters.
Description and Teaching Materials
This exercise uses a point cloud of a topographic feature of interest (in this case, a river bend) and imports it into CloudCompare, a point cloud viewer and manipulation platform. Students view the point cloud, measure features within the cloud, and classify the cloud. From the classified ground points, students make derivative rasters including a digital terrain model, slope, and hillshade model.
Students can use a point cloud they created in Day 3's Structure from Motion for Analysis of River Characteristics, download a point cloud from an open source resource such as OpenTopography, or use this provided dataset (Area 1 or Area 2 from Day 3's activity).
- Sheep Draw Vignette (Microsoft Word 2007 (.docx) 2MB Oct27 20)
- Student CloudCompare Activity (Microsoft Word 2007 (.docx) 5.7MB Oct27 20)
- Point cloud dataset of Poudre River at Sheep Draw (note: these files are provided as private instructor files because they are the product from Day 3's Structure from Motion for Analysis of River Characteristics; however, if you wish your students to start with point cloud data and not do the SfM processing themselves, they can uses these files)
- Additional Activity Working with Rasters in ArcGIS (Microsoft Word 2007 (.docx) 1.7MB Oct27 20)- Optional raster activity conducted with rasters created in CloudCompare
Technology Needs
Students need to install CloudCompare (open source)
If optional "Working with Rasters in ArcGIS" activity is used, ESCRI ArcGIS Desktop or Pro is needed.
Teaching Notes and Tips
- Some students lack the computing power needed to view, manipulate, and classify point clouds. For those students, I recommend having them use a smaller point cloud.
- Some students seem to have major issues installing and running CloudCompare. I do not have a solution for this at this time not do I know what the cause of this issue.
Assessment
s the summative assessment, students answer questions about the accuracy and applications of their product. Formative assessment should be done through discussion with students as a whole group or individually.
References and Resources
- CloudCompare - https://www.danielgm.net/cc/
- CANUPO classification of point cloud points - http://nicolas.brodu.net/en/recherche/canupo/
- Article about CANUPO - http://nicolas.brodu.net/common/recherche/publications/canupo.pdf
- Scott et al. Topographic Differencing: Earthquake along the Wasatch fault has information about CloudCompare
- Sources of topographic datasets
- OpenTopography - https://opentopography.org/
- UNAVCO - https://www.unavco.org/data/lidar-sfm/sfm-data/sfm-data.html