TreeLS: Terrestrial Point Cloud Processing of Forest Data

High performance algorithms for manipulation of terrestrial 'LiDAR' (but not only) point clouds for use in research and forest monitoring applications, being fully compatible with the 'LAS' infrastructure of 'lidR'. For in depth descriptions of stem denoising and segmentation algorithms refer to Conto et al. (2017) <doi:10.1016/j.compag.2017.10.019>.

Version: 2.0.2
Depends: R (≥ 3.3.0), data.table (≥ 1.12.0), magrittr (≥ 1.5), lidR (≥ 3.0.0)
Imports: rgl, raster, sp, deldir, dismo, nabor, benchmarkme, rlas, glue, mathjaxr
LinkingTo: RcppArmadillo, Rcpp, BH, RcppEigen
Published: 2020-08-26
Author: Tiago de Conto [aut, cre]
Maintainer: Tiago de Conto <tdc.florestal at>
License: GPL-3
NeedsCompilation: yes
Materials: README
CRAN checks: TreeLS results


Reference manual: TreeLS.pdf
Package source: TreeLS_2.0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: TreeLS_2.0.2.tgz, r-oldrel: not available
Old sources: TreeLS archive


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