FORTLS: Automatic Processing of TLS Point Cloud Data for Forestry Purposes

Process automation of Terrestrial Laser Scanner (TLS) point cloud data derived from single scans. 'FORTLS' enables (i) detection of trees and estimation of diameter at breast height (dbh), (ii) estimation of some stand 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. (2020, <doi:10.3390/IECF2020-08066>).

Version: 1.0.2
Depends: R (≥ 3.5.0)
Imports: dbscan, Distance, ggvoronoi, htmlwidgets, lidR, plotly, progress, Rcpp (≥ 1.0.5), raster, scales, sp, tidyr, vroom
LinkingTo: Rcpp, RcppEigen
Suggests: testthat
Published: 2021-04-21
Author: Juan Alberto Molina-Valero [aut, cph, cre], María José Ginzo Villamayor [aut, com], Manuel Antonio Novo Pérez [aut, com], Adela Martínez-Calvo [aut, com], Juan Gabriel Álvarez-González [aut, ths], Fernando Montes [aut], César Pérez-Cruzado [aut, ths]
Maintainer: Juan Alberto Molina-Valero <juanalberto.molina.valero at>
License: GPL-3
NeedsCompilation: yes
Citation: FORTLS citation info
Materials: README
CRAN checks: FORTLS results


Reference manual: FORTLS.pdf
Package source: FORTLS_1.0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: FORTLS_1.0.1.tgz, r-oldrel: FORTLS_1.0.1.tgz
Old sources: FORTLS archive


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