R package for airborne LiDAR data manipulation and visualisation for forestry applications

lidR package provides functions to read and write .las and .laz files, plot a cloud of points, compute metrics using an area-based approach, compute digital canopy models, thin lidar data, automatically extract ground inventories, process a set of tiles in multicore, classify data from shapefiles and provides other tools to manipulate liDAR data. lidR package is designed mainly for research purposes using an area-based approach.

lidR provides an open-source and R-based implementation of the main functions from software like FUSION or lastools. lidR is flexible because it allows the user to program their own tools rather rely on a set of predefined tools.

Since version 1.1.0 the package contains C++ code. The process to install the package from github for Windows users is more complex than before as you need developpement tools to be able to compile C++ code. Windows users can download and install a binary version of the package (not necesseraly up-to date).

Install R development package sudo apt-get install r-base-dev

Install Rtools: https://cran.r-project.org/bin/windows/Rtools/

I can't help you. Reading documentation seems prohibited for non mac user. Read this page: https://www.rstudio.com/products/rpackages/devtools/

installed.packages(c("methods","magrittr","dtplyr","rgl","reshape2","tools","parallel","fields","raster","rgdal","plyr","rgeos","data.table","dplyr","sp","Rcpp"))

install.packages("devtools")
devtools::install_github("Jean-Romain/lidR")
library(lidR)

Note for Windows users : tested on Windows 7. Installation might work as well as for GNU/Linux. But maybe not... Windows behaviours are... unpredictable.

• Read .las and .laz files
• Write .las and .laz files
• Retrieve indiviual pulses
• Retrieve individual flightlines
• Compute a digital canopy model
• Compute any set of metrics on a cloud of points
• Rasterize and apply any function to compute a set of metrics using an area based approach
• Classify and filter data from geographic shapefiles
• Filter cloud of points based on any condition test
• Thin a cloud of points to reach an homogeneous point density
• Clip data bases on discs, rectangles or polygons
• Manage a catalog of .las tiles
• Extract automatically a set of ground plot inventories (even plots falling between two or more tiles)
• Analyse a full set of tiles in parallel computing
• Plot 3D LiDAR data
• plot metrics in 2D and 3D

lidar = LoadLidar("myfile.las")
plot(lidar)

metric = gridMetrics(lidar, 20, mean(Z))
plot(metric)

• Function classifyFromShapefile is, at least, 3 times faster. Parts of the function have been rewritten in C++. The new column is added by reference
• Include the Martin Isenburg source code of LASlib and LASzip.
• Function readLAs have been rewritten in C++ using LASlib. It is 2 times faster and it's safer.
• Add function writeLAS using LASlib.
• Support of compressed .laz format in readLAS and writeLAS thanks to LASlib and LASzip.
• Function readLAS replace loadLidar.
• Objects Lidar do not exist anymore. They are called LAS. It does not change anything for users.