Algorithms for tree detection, noise removal, stem modelling, 3D visualization and manipulation of terrestrial 'LiDAR' (but not only) point clouds, currently focusing on high performance applications for forest inventory - being fully compatible with the 'LAS' infrastructure provided by 'lidR'. For in depth descriptions of the stem classification and segmentation algorithms check out Conto et al. (2017) <doi:10.1016/j.compag.2017.10.019>.
| Version: | 1.0 |
| Depends: | R (≥ 3.3.0), data.table (≥ 1.12.0), magrittr (≥ 1.5), lidR (≥ 2.0.0) |
| Imports: | rgl (≥ 0.99.0), raster (≥ 2.8.19) |
| LinkingTo: | Rcpp, BH, RcppEigen |
| Published: | 2019-03-13 |
| Author: | Tiago de Conto [aut, cre] |
| Maintainer: | Tiago de Conto <ti at forlidar.com.br> |
| License: | GPL-3 |
| URL: | https://github.com/tiagodc/TreeLS |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | TreeLS results |
| Reference manual: | TreeLS.pdf |
| Package source: | TreeLS_1.0.tar.gz |
| Windows binaries: | r-devel: TreeLS_1.0.zip, r-release: TreeLS_1.0.zip, r-oldrel: TreeLS_1.0.zip |
| OS X binaries: | r-release: TreeLS_1.0.tgz, r-oldrel: TreeLS_1.0.tgz |
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