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R package for Airborne LiDAR Data Manipulation and Visualization for Forestry Applications

The lidR package provides functions to read and write.las and.laz files, plot point clouds, compute metrics using an area-based approach, compute digital canopy models, thin LiDAR data, manage a collection of LAS/LAZ files, automatically extract ground inventories, process a collection of tiles using multicore processing, segment individual trees, classify points from geographic data, and provides other tools to manipulate LiDAR data in aresearch and development context.

• 📖 Readthe book to get started with the lidR package.
• 💻 InstalllidR from R with:install.packages("lidR")
• 💵SponsorlidR. It is free and open source, but requires time and effort to develop and maintain.

lidR has been cited by more than 1,000 scientific papers. To cite the package usecitation() from within R:

citation("lidR")#> Roussel, J.R., Auty, D., Coops, N. C., Tompalski, P., Goodbody, T. R. H., Sánchez Meador, A., Bourdon, J.F., De Boissieu, F., Achim, A. (2021). lidR : An R package for analysis of Airborne Laser Scanning (ALS) data. Remote Sensing of Environment, 251 (August), 112061. <doi:10.1016/j.rse.2020.112061>.#> Jean-Romain Roussel and David Auty (2023). Airborne LiDAR Data Manipulation and Visualization for Forestry Applications. R package version 3.1.0. https://cran.r-project.org/package=lidR

You may also be interested by our newlasR package.

In R-fashion style the functionplot, based onrgl, enables the user to display, rotate and zoom a point cloud.

las<- readLAS("<file.las>")plot(las)

lidR has several algorithms from the literature to compute canopy height models either point-to-raster based or triangulation based. This allows testing and comparison of some methods that rely on a CHM, such as individual tree segmentation or the computation of a canopy roughness index.

las<- readLAS("<file.las>")# Khosravipour et al. pitfree algorithmthr<- c(0,2,5,10,15)edg<- c(0,1.5)chm<- rasterize_canopy(las,1, pitfree(thr,edg))plot(chm)

lidR enables the user to manage, use and process a collection oflas files. The functionreadLAScatalog builds aLAScatalog object from a folder. The functionplot displays this collection on an interactive map using themapview package (if installed).

ctg<- readLAScatalog("<folder/>")plot(ctg,map=TRUE)

From aLAScatalog object the user can (for example) extract some regions of interest (ROI) withclip_roi(). Using a catalog for the extraction of the ROI guarantees fast and memory-efficient clipping.LAScatalog objects allow many other manipulations that can be done with multicore processing.

Thesegment_trees() function has several algorithms from the literature for individual tree segmentation, based either on the digital canopy model or on the point-cloud. Each algorithm has been coded from the source article to be as close as possible to what was written in the peer-reviewed papers. Our goal is to make published algorithms usable, testable and comparable.

las<- readLAS("<file.las>")las<- segment_trees(las, li2012())col<- random.colors(200)plot(las,color="treeID",colorPalette=col)

Most of the lidR functions can seamlessly process a set of tiles and return a continuous output. Users can create their own methods using theLAScatalog processing engine via thecatalog_apply() function. Among other features the engine takes advantage of point indexation with lax files, takes care of processing tiles with a buffer and allows for processing big files that do not fit in memory.

# Load a LAScatalog instead of a LAS filectg<- readLAScatalog("<path/to/folder/>")# Process it like a LAS filechm<- rasterize_canopy(ctg,2, p2r())col<- random.colors(50)plot(chm,col=col)

lidR can read full waveform data from LAS files and provides interpreter functions to convert the raw data into something easier to manage and display in R. The support of FWF is still in the early stages of development.

fwf<- readLAS("<fullwaveform.las>")# Interpret the waveform into something easier to managelas<- interpret_waveform(fwf)# Display discrete points and waveformsx<- plot(fwf,colorPalette="red",bg="white")plot(las,color="Amplitude",add=x)

lidR is developed openly byr-lidar.

The development oflidR was made possible through the financial support ofLaval University, theAWARE project andMinistry of Natural Ressources and Forests of Québec. To continue the development of this free software, we now offer consulting, programming, and training services. For more information, please visitour website.

# Ubuntusudo add-apt-repository ppa:ubuntugis/ubuntugis-unstablesudo apt-get updatesudo apt-get install libgdal-dev libgeos++-dev libudunits2-dev libproj-dev libx11-dev libgl1-mesa-dev libglu1-mesa-dev libfreetype6-dev libxt-dev libfftw3-dev# Fedorasudo dnf install gdal-devel geos-devel udunits2-devel proj-devel mesa-libGL-devel mesa-libGLU-devel freetype-devel libjpeg-turbo-devel