Automatic Processing of Terrestrial-Based Technologies Point Cloud Data for Forestry Purposes.
FORTLS 
Automatic Processing of Close-Range Technologies Point Cloud Data for Forestry Purposes
Process automation of point cloud data derived from terrestrial-based technologies such as Terrestrial Laser Scanner (TLS) or Mobile Laser Scanner (MLS). 'FORTLS' enables (i) detection of trees and estimation of tree-level attributes (e.g. diameters and heights), (ii) estimation of stand-level variables (e.g. density, basal area, mean and dominant height), (iii) computation of metrics related to important forest attributes estimated in Forest Inventories (FIs) at stand-level, and (iv) optimization of plot design for combining TLS data and field measured data. Documentation about 'FORTLS' is described in Molina-Valero et al. (2022, https://doi.org/10.1016/j.envsoft.2022.105337).
Get the lat stable version of FORTLS from GitHub (included in the master branch)
remotes::install_github("Molina-Valero/FORTLS", ref = "devel", dependencies = TRUE)
Acknowledgements
FORTLS it is being developed at Czech University of Life Sciences Prague and University of Santiago de Compostela.
Development of the FORTLS package is being possible thanks to the following fellowships/projects:
- Climate Change Adaptation of Forests in the Brdy Highland LIFE21-CCA-CZ-LIFE-Adapt-Brdy/101074426
- Design of forest monitoring systems on a regional scale [ED431F 2020/02] supported by the Regional Government of Galicia
- Ramón Areces Foundation Grants for Postdoctoral Studies XXXV Call for Expansion of Studies Abroad in Life and Matter Sciences.
