README.md

In FORTLS: 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 latest released version of FORTLS from GitHub (included in the devel branch)

remotes::install_github("Molina-Valero/FORTLS", ref = "devel", dependencies = TRUE)

Acknowledgements

FORTLS it is being developed at University of Santiago de Compostela.

Development of the FORTLS package is being possible thanks to the following projects:

• Modelling the effects of intensity of perturbation on the structure of natural forests and their carbon stocks by using data from the National Forestry Inventory (AGL2016-76769-C2-2-R) supported by the Spanish Ministry of Science and Innovation.
• Development of the Galician continuous forest inventory (2020-CP031) supported by the Regional Government of Galicia.
• Design of forest monitoring systems on a regional scale (ED431F 2020/02) supported by the Regional Government of Galicia.

FORTLS documentation built on Sept. 11, 2023, 5:09 p.m.