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PiC  

Pointcloud Interactive Computation
View on CRAN: Click here


Download and install PiC package within the R console
Install from CRAN:
install.packages("PiC")

Install from Github:
library("remotes")
install_github("cran/PiC")

Install by package version:
library("remotes")
install_version("PiC", "1.2.7")



Attach the package and use:
library("PiC")
Maintained by
Roberto Ferrara
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-02-18
Latest Update: 2025-02-18
Description:
Provides advanced algorithms for analyzing pointcloud data 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>.
How to cite:
Roberto Ferrara (2025). PiC: Pointcloud Interactive Computation. R package version 1.2.7, https://cran.r-project.org/web/packages/PiC. Accessed 06 Aug. 2026.
Previous versions and publish date:
(2026-07-29 15:40), 1.0.3 (2025-02-18 11:00), 1.2.6 (2025-10-11 20:00), 1.2.7 (2025-11-07 16:30), 3.3.1 (2026-06-29 10:20), 3.3 (2026-06-27 11:30)
Other packages that cited PiC R package
View PiC citation profile
Other R packages that PiC depends, imports, suggests or enhances
Complete documentation for PiC
Functions, R codes and Examples using the PiC R package
Full PiC package functions and examples
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