Tool access

The R package lidaRtRee can be installed from CRAN. Source codes and tutorials ara also available.

Presentation

lidaRtRee is an R package that provides functions for forest analysis using airborne laser scanning (LiDAR remote sensing) data:
– tree detection (method 1 in Eysn et al., 2015) and segmentation;
– forest parameters estimation and mapping with the area-based approach (implemented in Aussenac et al., 2023).

It includes complementary steps for forest mapping:
– co-registration of field plots with LiDAR data (Monnet and Mermin, 2014);
– extraction of both statistical and object features (gaps, edges, trees) from LiDAR data useful for e.g. habitat suitability modeling (Glad et al., 2020) and forest maturity mapping (Fuhr et al., 2022).

This package aims to foster applications of LiDAR data in forest ecology and management. LiDAR data are now increasingly available (e.g. the LiDAR HD program in France: the R package lidarHD is also available to make the download and management of those files easier).

Contact

References

Aussenac R., Monnet J.-M., Klopčič M., Hawryło P., Socha J., Mahnken M., Gutsch M., Cordonnier T., Vallet P., 2023. Diameter, height and species of 42 million trees in three European landscapes generated from field data and airborne laser scanning data, Open Research Europe, 3-32. https://doi.org/10.12688/openreseurope.15373.2

Eysn L., Hollaus M., Lindberg E., Berger F., Monnet J.-M., Dalponte M., Kobal M., Pellegrini M., Lingua E., Mongus D., Pfeifer N., 2015. A benchmark of lidar-based single tree detection methods using heterogeneous forest data from the Alpine space, Forests, 6, 12, p. 1721‑1747. https://doi.org/10.3390%2Ff6051721

Fuhr M., Lalechère E., Monnet J., Bergès L., 2022. Detecting overmature forests with airborne laser scanning (ALS), Remote Sensing in Ecology and Conservation, 8, 5, p. 731‑743. https://doi.org/10.1002%2Frse2.274

Glad A., Reineking B., Montadert M., Depraz A., Monnet J., 2019. Assessing the performance of object‐oriented LiDAR predictors for forest bird habitat suitability modeling, Remote Sensing in Ecology and Conservation, 6, 1, p. 5‑19 https://doi.org/10.1002%2Frse2.117

Monnet J.-M., 2023, « lidaRtRee: R package for forest analysis with airborne laser scanning (LiDAR) data », https://doi.org/10.57745/JV66MZ, Recherche Data Gouv, V1

Monnet J.-M., Mermin É., 2014. Cross-correlation of diameter measures for the co-registration of forest inventory plots with airborne laser scanning data, Forests, 5, 9, p. 2307‑2326.  https://doi.org/10.3390%2Ff5092307

Monnet J.-M., Paccard P., Riond C., 2020. La télédétection aéroportée pour la gestion des territoires forestiers de montagne. Sciences Eaux & Territoires, (33), 64–69. https://doi.org/10.14758/SET-REVUE.2020.3.12

Le développement de lidaRtRee a bénéficié d’un financement de l’ADEME via le projet PROTEST (programme GRAINE, convention 1703C0069).