PiC: Pointcloud Interactive Computation for Forest Structure Analysis

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>.

Version:	1.0.3
Depends:	R (≥ 4.3)
Imports:	collapse, data.table, dbscan, dplyr, foreach, magrittr, stats, tictoc
Suggests:	ggplot2, testthat (≥ 3.0.0), withr
Published:	2025-02-18
DOI:	10.32614/CRAN.package.PiC
Author:	Roberto Ferrara [aut, cre], Stefano Arrizza [aut]
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
CRAN checks:	PiC results

Documentation:

Reference manual:

PiC.pdf

Downloads:

Package source:	PiC_1.0.3.tar.gz
Windows binaries:	r-devel: PiC_1.0.3.zip, r-release: PiC_1.0.3.zip, r-oldrel: PiC_1.0.3.zip
macOS binaries:	r-devel (arm64): not available, r-release (arm64): not available, r-oldrel (arm64): not available, r-devel (x86_64): PiC_1.0.3.tgz, r-release (x86_64): PiC_1.0.3.tgz, r-oldrel (x86_64): PiC_1.0.3.tgz

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