Commit 6ddad2c8 authored by Monnet Jean-Matthieu's avatar Monnet Jean-Matthieu
Browse files

Changed licence CC-By to GPLv3

parent 0aa4e991
# `lidaRtRee` tutorials
`lidaRtRee_tutorials` is a repository that provides tutorials for forest analysis with airborne laser scanning (ALS or lidar remote sensing) data, using functions from `R` packages [lidR](https://github.com/Jean-Romain/lidR/) (also available on [CRAN](https://cran.r-project.org/web/packages/lidR/index.html)) and [lidaRtRee](https://gitlab.irstea.fr/jean-matthieu.monnet/lidaRtRee). Tutorials are available as `Rmarkdown`, `html` and `pdf` files. Datasets useful for code running are also provided.
# Available tutorials
- [tree detection and segmentation](Tree-segmentation),
- [field plot co-registration with ALS data](Field-plot-coregistration-with-ALS-data),
- [forest structure metrics mapping](Forest-structure-metrics-mapping),
- [forest gaps and edges detection](Forest-gaps-and-edges-detection),
- [area-based approach for forest parameters estimation and mapping](Area-based-approach).
\ No newline at end of file
......@@ -18,7 +18,7 @@ knitr::opts_chunk$set(fig.align = "center")
The code below presents a workflow to prepare inventory data for the calibration of area-based models with airborne laser scanning data and field measurements.
Licence: CC-BY / [Source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/area-based.1.data.preparation.Rmd)
Licence: GNU GPLv3 / [Source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/area-based.1.data.preparation.Rmd)
Required `R` libraries : `ggplot2`, `sf`, `ggmap`
......
......@@ -19,7 +19,7 @@ knitr::opts_chunk$set(fig.align = "center")
---
The code below presents a workflow to calibrate prediction models for the estimation of forest parameters from ALS-derived metrics, using the area-based approach (ABA). The workflow is based on functions from `R` packages `lidaRtRee` and `lidR`.
Licence: CC-BY / [Source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/area-based.2.model.calibration.Rmd)
Licence: GNU GPLv3 / [Source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/area-based.2.model.calibration.Rmd)
# Load data
......
......@@ -20,7 +20,7 @@ knitr::opts_chunk$set(fig.align = "center")
---
This workflow compares a canopy height model (CHM) derived from airborne laser scanning (ALS) data with tree positions inventoried in the field, and then proposes a translation in plot position for better matching. The method is described in @Monnet2014. Here it is exemplified with circular plots, but it can be applied to any shape of field plots. The workflow is based on functions from packages `lidaRtRee` and `lidR`. Example data were acquired in the forest of Lac des Rouges Truites (Jura, France).
Licence: CC BY / [Source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/coregistration.Rmd)
Licence: GNU GPLv3 / [Source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/coregistration.Rmd)
## Material
......
......@@ -17,7 +17,7 @@ knitr::opts_chunk$set(fig.align = "center")
```
---
Licence: CC-BY / [Source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/forest.structure.metrics.Rmd)
Licence: GNU GPLv3 / [Source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/forest.structure.metrics.Rmd)
The R code below presents a forest structure metrics computation workflow from Airborne Laser Scanning (ALS) data. Workflow is based on functions from packages `lidaRtRee` and `lidR`, packages `vegan` and `foreach` are also required. Metrics are computed for each cell of a grid defined by a resolution. Those metrics are designed to describe the 3D structure of forest.
Different types of metrics are computed:
......
......@@ -19,7 +19,7 @@ knitr::opts_chunk$set(fig.align = "center")
---
This tutorial presents R code for forest gaps and edges detection from Airborne Laser Scanning (ALS) data. The workflow is based on functions from packages `lidaRtRee` and `lidR`.
Licence: CC BY / [Source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/gap.edges.detection.Rmd)
Licence: GNU GPLv3 / [Source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/gap.edges.detection.Rmd)
## Study area and ALS data
......
......@@ -30,7 +30,7 @@ The code below presents a tree segmentation workflow from Airborne Laser Scannin
Steps 1 and 3 are documented in [@Monnet10; @Monnet11c]. The detection performance of this algorithm was evaluated in a benchmark [@Eysn15].
Licence: CC-BY / [source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/tree.detection.Rmd)
Licence: GNU GPLv3 / [source page](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/blob/master/tree.detection.Rmd)
## Material
### Field inventory
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment