Package: FORTLS
Title: Automatic Processing of Terrestrial-Based Technologies Point
        Cloud Data for Forestry Purposes
Version: 1.6.0
Date: 2025-07-30
Authors@R: c(
    person("Juan Alberto", "Molina-Valero", role = c("aut", "cph", "cre"),
    email = "jamolinavalero@gmail.com"),
    person("Adela", "Martínez-Calvo", role = c("aut", "com")),
    person("María José", "Ginzo Villamayor", role = c("aut", "com")),
    person("Manuel Antonio", "Novo Pérez", role = c("aut", "com")),
    person("Juan Gabriel", "Álvarez-González", role = c("aut", "ths")),
    person("Fernando", "Montes", role = "aut"),
    person("César", "Pérez-Cruzado", role = c("aut", "ths")))
Author: Juan Alberto Molina-Valero [aut, cph, cre],
  Adela Martínez-Calvo [aut, com],
  María José Ginzo Villamayor [aut, com],
  Manuel Antonio Novo Pérez [aut, com],
  Juan Gabriel Álvarez-González [aut, ths],
  Fernando Montes [aut],
  César Pérez-Cruzado [aut, ths]
Maintainer: Juan Alberto Molina-Valero <jamolinavalero@gmail.com>
Description: Process automation of point cloud data derived from terrestrial-based technologies such as Terrestrial Laser Scanner (TLS) or Mobile Laser Scanner. '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 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, <doi:10.1016/j.envsoft.2022.105337>). 
URL: https://molina-valero.github.io/FORTLS/,
        https://github.com/Molina-Valero/FORTLS
BugReports: https://github.com/Molina-Valero/FORTLS/issues
License: GPL-3
Depends: R (>= 4.1.0)
Imports: data.table, dbscan, Distance, glue, htmlwidgets, lidR,
        methods, moments, parallel, plotly, progress, raster, Rcpp(>=
        1.0.10), RCSF, reticulate, scales, sf, tidyr, VoxR, vroom
Suggests: devtools, kableExtra, knitr, rmarkdown, systemfonts, testthat
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
Encoding: UTF-8
RoxygenNote: 7.3.2
VignetteBuilder: knitr
StagedInstall: yes
NeedsCompilation: yes
Packaged: 2025-07-29 13:09:48 UTC; jamol
Repository: CRAN
Date/Publication: 2025-07-29 19:20:32 UTC
Built: R 4.6.0; x86_64-w64-mingw32; 2025-10-11 04:02:55 UTC; windows
Archs: x64
