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index.qmd
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---
title: "`lidR`: (A workshop for) Airborne LiDAR Data Manipulation and Visualization for Forestry Applications"
author: "Tristan R.H. Goodbody, Jean-Romain Roussel"
institute: "University of British Columbia, Université Laval, Ministère des Forêts, de la Faune et des Parcs (Québec)"
date: 2023-09-05
---
```{r, echo = FALSE}
library(rgl)
r3dDefaults = rgl::r3dDefaults
m = structure(c(0.921, -0.146, 0.362, 0, 0.386, 0.482, -0.787, 0,
-0.06, 0.864, 0.5, 0, 0, 0, 0, 1), .Dim = c(4L, 4L))
r3dDefaults$FOV = 50
r3dDefaults$userMatrix = m
r3dDefaults$zoom = 0.75
knitr::opts_chunk$set(
comment = "#>",
collapse = TRUE,
fig.align = "center")
rgl::setupKnitr(autoprint = TRUE)
options(lidR.progress = FALSE)
```
## 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](https://github.com/tgoodbody/lidRtutorial). 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
Find the code, exercises, and solutions used in the `.\code` sub-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](https://www.rstudio.com/). 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).
``` r
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.
``` r
libs <- c("geometry","viridis","future","sf","maptools","terra","mapview","mapedit","concaveman")
install.packages(libs)
```
## Estimated schedule {.smaller}
- 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](https://cran.r-project.org/web/packages/lidR/lidR.pdf)
- The [lidRbook](https://r-lidar.github.io/lidRbook/) of tutorials
When working on exercises:
- [Stack Exchange with the `lidR` tag](https://gis.stackexchange.com/questions/tagged/lidr)
## `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](https://github.com/Jean-Romain) 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](https://cran.r-project.org/web/packages/lidR/) and source code is hosted on [GitHub](https://github.com/r-lidar/lidR).