diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..dcd0b1fa7d944ef382a5391ea0b6c3f5c2ffc78a
--- /dev/null
+++ b/README.md
@@ -0,0 +1,11 @@
+# `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
diff --git a/area-based.1.data.preparation.Rmd b/area-based.1.data.preparation.Rmd
index 36fc58c4157e84f695df60b35a3ad89b3ef4b88c..7981a672f42e69c623a82c70cf9fdc90479030bd 100644
--- a/area-based.1.data.preparation.Rmd
+++ b/area-based.1.data.preparation.Rmd
@@ -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`
 
diff --git a/area-based.2.model.calibration.Rmd b/area-based.2.model.calibration.Rmd
index b0543bace76e697206d352d119b1b14ca71a1528..3a7c290e46fa7e49a67f912cfcd58b74b03b66cf 100644
--- a/area-based.2.model.calibration.Rmd
+++ b/area-based.2.model.calibration.Rmd
@@ -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
 
diff --git a/coregistration.Rmd b/coregistration.Rmd
index 9ef664e504ecf380ecc1ed62ea7b0cd1c2089e60..019164f4f885f758e47e45b8db92f771cdf1aad7 100644
--- a/coregistration.Rmd
+++ b/coregistration.Rmd
@@ -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
diff --git a/forest.structure.metrics.Rmd b/forest.structure.metrics.Rmd
index 3af8544f543e066f8cf78e2a8cf477b805ff405b..105d3fa1376b0bf003bb68153e37feeea78ddcda 100644
--- a/forest.structure.metrics.Rmd
+++ b/forest.structure.metrics.Rmd
@@ -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:  
diff --git a/gaps.edges.detection.Rmd b/gaps.edges.detection.Rmd
index ddbc06adca6017a9cc443635675e5f2b4a0a24a4..ad9cab03d037235b15bc499237414a96f0511746 100644
--- a/gaps.edges.detection.Rmd
+++ b/gaps.edges.detection.Rmd
@@ -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
 
diff --git a/tree.detection.Rmd b/tree.detection.Rmd
index 5a9e7b39963a7b730eda994e46873e09e64fd924..19aee4c9ed6c2ca3db1d0e2a0a75ea3aeae0e3e5 100644
--- a/tree.detection.Rmd
+++ b/tree.detection.Rmd
@@ -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