Other packages > Find by keyword >

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 26 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
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

SelvarMix  
Regularization for Variable Selection in Model-Based Clustering and Discriminant Analysis
Performs a regularization approach to variable selection in themodel-based clustering and classifica ...
Download / Learn more Package Citations See dependency  
ncodeR  
Techniques for Automated Classifiers
A set of techniques that can be used to develop, validate, and implement automated classifiers. A po ...
Download / Learn more Package Citations See dependency  
PCADSC  
Tools for Principal Component Analysis-Based Data Structure Comparisons
A suite of non-parametric, visual tools for assessing differences in data structures for two datase ...
Download / Learn more Package Citations See dependency  
RCytoGPS  
Using Cytogenetics Data in R
Defines classes and methods to process text-based cytogenetics using the CytoGPS web site, then imp ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
leafgl  
High-Performance 'WebGl' Rendering for Package 'leaflet'
Provides bindings to the 'Leaflet.glify' JavaScript library which extends the 'leaflet' JavaScript l ...
Download / Learn more Package Citations See dependency  

28,332

R Packages

239,283

Dependencies

75,113

Author Associations

28,333

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA