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# Overview
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`lidaRtRee` is an `R` package that provides functions for **forest analysis using airborne laser scanning** (lidar remote sensing) data: tree detection / segmentation and area-based approach. It includes complementary steps for forest mapping: extraction of both physical (gaps, edges, trees) and statistical features from lidar data, model calibration with ground reference, and maps export.
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`lidaRtRee` is an `R` package that provides functions for **forest analysis using airborne laser scanning** (LiDAR remote sensing) data: tree detection / segmentation and area-based approach. It includes complementary steps for forest mapping: extraction of both physical (gaps, edges, trees) and statistical features from LiDAR data, model calibration with ground reference, and maps export.
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# Installation
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* `R` >= 4.0.3 recommended, package `lidR` >= 3.1.0 required
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* `R` >= 4.2.3 recommended, package `lidR` >= 4.0.0 required
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* **The package is available on [CRAN](https://cran.r-project.org/package=lidaRtRee)**, to install run in the `R` console `install.packages("lidaRtRee")`
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* **build development version from source** with the `devtools` package by running in an `R` console: `devtools::install_git("https://gitlab.irstea.fr/jean-matthieu.monnet/lidaRtRee/", branch="dev")`
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* **build development version from source** with the `devtools` package by running in an `R` console: `devtools::install_git("https://gitlab.irstea.fr/jean-matthieu.monnet/lidaRtRee/")`
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# Tutorials
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**Tutorials** using `lidaRtRee` functions are available on the [lidaRtRee_tutorials](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/) repository, as `Rmarkdown` files, `html` and `pdf` files, and including datasets to run the code. The [wiki](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/wikis/home) presents the different tutorials:
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**Tutorials** using `lidaRtRee` functions are available on the [lidaRtRee_tutorials](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/) repository, as `Rmarkdown` files and `html` files, and including datasets to run the code. The [wiki](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/wikis/home) presents the different tutorials:
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* [ALS data checking and preprocessing](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/wikis/ALS-data-preprocessing)
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* [ALS data pre-processing](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/wikis/ALS-data-preprocessing)
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* [Tree detection](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/wikis/Tree-segmentation)
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* [Forest field plot coregistration with ALS data](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/wikis/Field-plot-coregistration-with-ALS-data)
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* [Forest gaps and edges detection](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/wikis/Forest-gaps-and-edges-detection)
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* [Forest structure metrics computation and mapping](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/wikis/Forest-structure-metrics-mapping)
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* [Area-based approach for forest parameters estimation](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/wikis/Area-based-approach) |
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* [Area-based approach for forest parameters estimation](https://gitlab.irstea.fr/jean-matthieu.monnet/lidartree_tutorials/-/wikis/Area-based-approach) |
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