Forest Analysis with Airborne Laser Scanning (LiDAR) Data.

lidaRtRee

R package for forest analysis with airborne laser scanning data

lidaRtRee provides functions for forest objects detection, structure features computation, model calibration and mapping:

• co-registration of field plots with LiDAR data (Monnet and Mermin (2014));
• tree detection (method 1 in Eysn et al. (2015)) and segmentation;
• forest parameters estimation with the area-based approach: model calibration with ground reference, and maps export;
• extraction of both physical (gaps, edges, trees) and statistical features from LiDAR data useful for e.g. habitat suitability modeling (Glad et al. (2020)) or forest maturity mapping (Fuhr et al. (2022)).

Install

• R >= 4.2.3 recommended, package lidR >= 4.0.0 required.
• Install from CRAN, by running in the R console: install.packages("lidaRtRee").
• Build development version from source with the devtools package: devtools::install_git("https://forgemia.inra.fr/lidar/lidaRtRee").

Tutorials

Tutorials using lidaRtRee functions are available in the vignettes folder as Rmarkdown files, including datasets to run the code. The available tutorials are:

• ALS data pre-processing.
• Tree detection.
• Forest field plot coregistration with ALS data.
• Forest gaps and edges detection.
• Forest structure metrics computation and mapping.
• Area-based approach for forest parameters estimation:
  • data preparation,
  • model calibration and
  • mapping.

Acknowledgements / funding

lidaRtRee development (2018-2021) was funded by the ADEME (french Agency for Ecological Transition) through the PROTEST project (grant 1703C0069 of the GRAINE program).