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
andLASzip
. - Function
readLAs
have been rewritten in C++ usingLASlib
. It is 2 times faster and it's safer. - Add function
writeLAS
usingLASlib
. - Support of compressed
.laz
format inreadLAS
andwriteLAS
thanks toLASlib
andLASzip
. - Function
readLAS
replaceloadLidar
. - Objects
Lidar
do not exist anymore. They are calledLAS
. It does not change anything for users.