lidR
: (A workshop for) Airborne LiDAR Data Manipulation and Visualization for Forestry Applications
People
Presenter: Tristan Goodbody (UBC)
Assistants:
Alexandre Morin-Bernard (Laval)
Leanna Stackhouse (UBC)
Liam Irwin (UBC)
Materials
This repository contains the material for a ~3 hour lidR
tutorial workshop. You should install the material on your own machine from this repository. It contains the code, the shapefiles and point-clouds we will use. The workshop intends to:
- Present an overview of what can be done with
lidR
- Give users an understanding of how
lidR
may fit their needs - Exercises will be done depending on available time - users are encouraged to work on these after the workshop!
Find the code, exercises, and solutions used in the .\R
directory.
Requirements
R version and Rstudio
- You need to install a recent version of
R
i.e.R 4.0.x
or newer. - We will work with Rstudio. This IDE is not mandatory to follow the workshop but is highly recommended.
R Packages
You need to install the lidR
package in its latest version (v >= 4.0.0).
install.packages("lidR")
To run all code in the tutorial yourself, you will need to install the following packages. You can use lidR
without them, however.
<- c("geometry","viridis","future","sf","gstat","terra","mapview","mapedit","concaveman","microbenchmark")
libs
install.packages(libs)
Estimated schedule
- Introduction and set-up (09:00)
- Read LAS and LAZ files (09:15)
- Spatial queries (09:35)
- Area-Based Approach (09:45)
- Canopy Height Model (10:00)
- Digital Terrain Model (10:10)
— Break until 10:30 —
- Individual tree segmentation (10:30)
- File collection processing engine (basic) (11:00)
- File collection processing engine (advanced) (11:30)
Resources
We strongly recommend having the following resources available to you:
- The
lidR
official documentation - The lidRbook of tutorials
When working on exercises:
lidR
lidR
is an R package to work with LiDAR data developed at Laval University (Québec). It was developed & continues to be maintained by Jean-Romain Roussel and was made possible between:
2015 and 2018 thanks to the financial support of the AWARE project NSERC CRDPJ 462973-14; grantee Prof. Nicholas C. Coops.
2018 and 2021 thanks to the financial support of the Ministère des Forêts, de la Faune et des Parcs (Québec).
The current release version of lidR
can be found on CRAN and source code is hosted on GitHub.