Package: FuelDeep3D
Type: Package
Title: 3D Fuel Segmentation Using Terrestrial Laser Scanning and Deep
        Learning
Version: 0.1.1
Authors@R: 
    c(
      person("Venkata Siva Reddy", "Naga",
             role = c("aut", "cre"),
             email = "venkatasivareddy003@gmail.com"),
      person("Alexander John", "Gaskins",
              role = "aut",  
              email = "alexandergaskins@ufl.edu"),
      person("Carlos Alberto", "Silva",
             role = "aut",
             email = "c.silva@ufl.edu")
    )
Description: Provides tools for preprocessing, feature extraction, and segmentation
    of three-dimensional forest point clouds derived from terrestrial laser scanning.
    Functions support creating height-above-ground (HAG) metrics, tiling, and sampling
    point clouds, generating training datasets, applying trained models to new point
    clouds, and producing per-point fuel classes such as stems, branches, foliage,
    and surface fuels. These tools support workflows for forest structure analysis,
    wildfire behavior modeling, and fuel complexity assessment. Deep learning 
    segmentation relies on the PointNeXt architecture described by Qian et al. 
    (2022) <doi:10.48550/arXiv.2206.04670>, while ground classification utilizes 
    the Cloth Simulation Filter algorithm by Zhang et al. (2016) <doi:10.3390/rs8060501>.
Depends: R (>= 4.1)
Imports: stats, RColorBrewer, viridisLite, rlang
Suggests: lidR, reticulate, dbscan, ggplot2, rgl, RCSF, scales
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/venkatasivanaga/FuelDeep3D
BugReports: https://github.com/venkatasivanaga/FuelDeep3D/issues
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2026-02-23 22:27:20 UTC; vs.naga
Author: Venkata Siva Reddy Naga [aut, cre],
  Alexander John Gaskins [aut],
  Carlos Alberto Silva [aut]
Maintainer: Venkata Siva Reddy Naga <venkatasivareddy003@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-02 21:30:03 UTC
Built: R 4.6.0; ; 2026-04-25 19:05:08 UTC; unix
