Package: RMCC 0.1.1

Jean-Romain Roussel

RMCC: Airborne LiDAR Filtering Method Based on Multiscale Curvature

Multiscale Curvature Classification of ground returns in 3-D LiDAR point clouds, designed for forested environments. 'RMCC' is a porting to R of the 'MCC-lidar' method by Evans and Hudak (2007) <doi:10.1109/TGRS.2006.890412>.

Authors:Jean-Romain Roussel [aut, cre], Evans Jeffrey S [aut], Hudak Andrew T [aut], Green Code LLC [cph], Jarno Elonen [cph], Thomas Becker [cph]

RMCC_0.1.1.tar.gz
RMCC_0.1.1.zip(r-4.7)RMCC_0.1.1.zip(r-4.6)RMCC_0.1.1.zip(r-4.5)
RMCC_0.1.1.tgz(r-4.6-x86_64)RMCC_0.1.1.tgz(r-4.6-arm64)RMCC_0.1.1.tgz(r-4.5-x86_64)RMCC_0.1.1.tgz(r-4.5-arm64)
RMCC_0.1.1.tar.gz(r-4.7-arm64)RMCC_0.1.1.tar.gz(r-4.7-x86_64)RMCC_0.1.1.tar.gz(r-4.6-arm64)RMCC_0.1.1.tar.gz(r-4.6-x86_64)
RMCC_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
RMCC/json (API)

# Install 'RMCC' in R:

install.packages('RMCC', repos = c('https://r-lidar.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/r-lidar/rmcc/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

rmcc_cloud - Airborne LiDAR point cloud

On CRAN:

cpp

4.15 score 7 stars 2 scripts 470 downloads 1 exports 2 dependencies

Last updated from:a19ba68ce6. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	133
linux-devel-x86_64	OK	136
source / vignettes	OK	179
linux-release-arm64	OK	130
linux-release-x86_64	OK	134
macos-release-arm64	OK	139
macos-release-x86_64	OK	232
macos-oldrel-arm64	OK	145
macos-oldrel-x86_64	OK	207
windows-devel	OK	147
windows-release	OK	123
windows-oldrel	OK	121
wasm-release	OK	118