Package: PiC 1.2.7
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>.
Authors:
PiC_1.2.7.tar.gz
PiC_1.2.7.zip(r-4.7)PiC_1.2.7.zip(r-4.6)PiC_1.2.7.zip(r-4.5)
PiC_1.2.7.tgz(r-4.6-any)PiC_1.2.7.tgz(r-4.5-any)
PiC_1.2.7.tar.gz(r-4.7-any)PiC_1.2.7.tar.gz(r-4.6-any)
PiC_1.2.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
PiC/json (API)
NEWS
| # Install 'PiC' in R: |
| install.packages('PiC', repos = c('https://rupppy.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rupppy/pic/issues
Last updated from:8a09fd7926. Checks:7 ERROR, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | ERROR | 266 | ||
| source / vignettes | OK | 201 | ||
| linux-release-x86_64 | ERROR | 185 | ||
| macos-release-arm64 | ERROR | 232 | ||
| macos-oldrel-arm64 | ERROR | 218 | ||
| windows-devel | ERROR | 262 | ||
| windows-release | ERROR | 299 | ||
| windows-oldrel | ERROR | 280 | ||
| wasm-release | OK | 137 |
Exports:Calculate_trees_metricsFlosegForest_segrun_PiCSegOneVoxels
Dependencies:classclassIntclicodetoolscollapseconicfitdata.tableDBIdbscandplyre1071foreachgeigengenericsglueiteratorsKernSmoothlifecyclemagrittrMASSpillarpkgconfigpracmaproxyR6Rcpprlangs2sftibbletictoctidyselectunitsutf8vctrswithrwk
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Calculate tree and canopy metrics | Calculate_trees_metrics |
| Forest floor segmentation | Floseg |
| Forest component segmentation | Forest_seg |
| Launch PiC Shiny App | run_PiC |
| Single Tree wood leaf segmentation | SegOne |
| Voxelize point cloud | Voxels |
| Wood voxels segmentation | Woodseg |
