PiC: Pointcloud Interactive Computation
Provides advanced algorithms for analyzing pointcloud data from terrestrial laser scanner in
forestry applications. Key features include fast voxelization of
large datasets; segmentation of point clouds into forest floor,
understorey, canopy, and wood components. The package enables
efficient processing of large-scale forest pointcloud data, offering
insights into forest structure, connectivity, and fire risk
assessment. Algorithms to analyze pointcloud data (.xyz input file).
For more details, see Ferrara & Arrizza (2025) <https://hdl.handle.net/20.500.14243/533471>.
For single tree segmentation details, see Ferrara et al. (2018)
<doi:10.1016/j.agrformet.2018.04.008>.
| Version: |
1.2.6 |
| Depends: |
R (≥ 4.3) |
| Imports: |
collapse, conicfit, data.table, dbscan, dplyr, foreach, magrittr, sf, stats, tictoc, utils |
| Suggests: |
DT, fs, ggplot2, later, plotly, shiny, shinycssloaders, shinydashboard, shinydashboardPlus, shinyFeedback, shinyFiles, shinyjs, shinythemes, shinyWidgets, testthat (≥ 3.0.0), tools, withr |
| Published: |
2025-10-11 |
| DOI: |
10.32614/CRAN.package.PiC |
| Author: |
Roberto Ferrara 
[aut, cre],
Stefano Arrizza
[ctb] |
| Maintainer: |
Roberto Ferrara <roberto.ferrara at cnr.it> |
| BugReports: |
https://github.com/rupppy/PiC/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/rupppy/PiC |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
PiC results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=PiC
to link to this page.