lidR v1.2.1
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Airborne LiDAR Data Manipulation and Visualization for Forestry Applications
Airborne LiDAR (Light Detection and Ranging) interface for data
manipulation and visualization. Read/write 'las' and 'laz' files, computation
of metrics in area based approach, point filtering, artificial point reduction,
classification from geographic data, normalization, individual tree segmentation
and other manipulations.
Readme
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 a point cloud, compute metrics using an area-based approach, compute digital canopy models, thin lidar data, manage a catalog of datasets, automatically extract ground inventories, process a set of tiles in multicore, individual tree segmentation, classify data from geographic data, and provides other tools to manipulate LiDAR data.
lidR provides an open-source and R-based implementation of several classical functions used in software dedicated to LiDAR data manipulation. lidR is flexible because it allows the user to program their own tools and manipulate their own objects in R rather than rely on a set of predefined tools.
Please contact the author for bug reports or feature requests (on github, preferably). I enjoy implementing new features!
Features (not exhaustive)
- Read write .las and .laz files
- Plot 3D LiDAR data
- Retrieve indiviual pulses and flightlines
- Compute any set of metrics using an area based approach
- Compute any set of metrics on a cloud of points
- Classify and clip data from geographic shapefiles
- Colorize a point cloud from RGB images
- Filter a cloud of points based on any condition test
- Clip data based on discs, rectangles or polygons
- Manage a catalog of
.las
tiles - Thin a point cloud to reach a homogeneous pulse density
- Automatically extract a set of ground plot inventories
- Analyse a full set of tiles in parallel computing
- Compute a digital canopy model (DCM)
- Compute a digital terrain model (DTM)
- Normalize a point cloud substracting a DTM
- Individual tree segmentation
Install lidR
- The latest released version from CRAN with
install.packages("lidR")
- The latest development version from github with
devtools::install_github("Jean-Romain/rlas", dependencies=TRUE)
devtools::install_github("Jean-Romain/lidR", dependencies=TRUE)
To install the package from github make sure you have a working development environment.
- Windows: Install Rtools.exe.
- Mac: Install
Xcode
from the Mac App Store. - Linux: Install the R development package, usually called
r-devel
orr-base-dev
Some examples
Changelog
Functions in lidR
Name | Description | |
LASheader-class | An S4 class to represent the header read in a .las or .laz file | |
LASheader | Create a LASheader object | |
VCI | Vertical Complexity Index | |
as.SpatialPixelsDataFrame | Transform a 'lasmetrics' object into a SpatialPixelsDataFrame object | |
LAD | Leaf area density | |
-,LAS,RasterLayer-method | Convenient operator to lasnormalize | |
LAS-class | An S4 class to represent the data read in a .las or .laz file | |
LAS | Create a LAS object | |
as.SpatialPointsDataFrame | Transform a LAS object into a SpatialPointsDataFrame object | |
as.lasmetrics | Set the class 'lasmetrics' to a data.frame or a data.table | |
as.raster.lasmetrics | Transform a lasmetrics object into a spatial RasterLayer object | |
$,LAS-method | Extract parts of a LAS object | |
extent,LAS-method | Extent | |
gap_fraction_profile | Gap fraction profile | |
grid_canopy | Canopy surface model | |
grid_tincanopy | Canopy height model based on a triangulation. | |
lasarea | Compute the area covered by of a set a points. | |
lascolor | Compute the color from RGB fields | |
lasdecimate | Thin LiDAR data | |
lidrpalettes | Palettes | |
plot.Catalog | Plot a Catalog object | |
rumple_index | Rumple index of roughness | |
set.colors | Automatic colorization | |
catalog_select | Select LAS files interactively | |
entropy | Normalized Shannon diversity index | |
lasfilter | Return points with matching conditions | |
lasfilters | Predefined filters | |
lasscanline | Retrieve individual scanline | |
lastrees | Individual tree segmentation | |
catalog | Build a catalog of las tiles/files | |
catalog_apply | Apply a function to a set of tiles using several cores. | |
grid_metrics3d | Voxelize the space and compute metrics for each voxel | |
grid_terrain | Digital Terrain Model | |
grid_density | Pulse density surface model | |
lasflightline | Retrieve individual flightlines | |
lasground | Classify points as ground or not ground | |
plot.LAS | Plot LiDAR data | |
plot.lashexametrics | Plot an object of class lashexametrics in 2D | |
grid_hexametrics | Compute metrics for hexagonal cells | |
grid_metrics | Rasterize the space and compute metrics for each cell | |
laspulse | Retrieve individual pulses | |
lasroi | Select a region of interest interactively | |
lasmetrics | Compute metrics for a cloud of points | |
lasnormalize | Subtract digital terrain model | |
plot.lasmetrics | Plot an object of class lasmetrics in 2D | |
plot.lasmetrics3d | Plot voxelized LiDAR data | |
lidR-deprecated | Deprecated function(s) in the lidR package | |
lidr_options | Options Settings for the lidR package | |
tree_metrics | Compute metrics for each tree | |
writeLAS | Write a las or laz file | |
stdmetrics | Predefined standard metrics functions | |
summary.LAS | Summary of LAS data | |
catalog_index | Retrieve the tiles containing ROIs | |
catalog_queries | Extract LiDAR data based on a set of coordinates | |
lasclassify | Classify LiDAR points from source data | |
lasclip | Clip LiDAR points | |
plot3d | Plot a wireframe of a RasterLayer or a lasmetrics object | |
readLAS | Read .las or .laz files | |
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Details
Type | Package |
Date | 2017-05-23 |
URL | https://github.com/Jean-Romain/lidR |
BugReports | https://github.com/Jean-Romain/lidR/issues |
License | GPL-3 |
LazyData | true |
RoxygenNote | 6.0.1 |
LinkingTo | Rcpp,RcppProgress |
Encoding | UTF-8 |
biocViews | |
Collate | 'RcppExports.R' 'catalog.r' 'catalog_apply.r' 'catalog_index.r' 'catalog_query.r' 'catalog_select.r' 'constant.R' 'deprecated.r' 'grid_canopy.r' 'grid_density.r' 'grid_hexametrics.r' 'grid_metrics.r' 'grid_metrics3d.r' 'grid_terrain.r' 'grid_tincanopy.r' 'lasheader-class.r' 'las-class.r' 'lasaggreagte.r' 'lasarea.r' 'lascheck.r' 'lasclassify.r' 'lasclip.r' 'lascolor.r' 'lasdecimate.r' 'lasextent.r' 'lasfilter.r' 'lasground.r' 'lasindentify.r' 'lasmetrics.r' 'lasnormalize.r' 'lasroi.r' 'lassummary.r' 'lastrees.r' 'lidRError.r' 'metrics.r' 'metrics_canopy_roughtness.r' 'mutatebyref.r' 'option.r' 'plot.catalog.r' 'plot.las.r' 'plot.lashexametrics.r' 'plot.lasmetrics.r' 'plot.lasmetrics3d.r' 'plot3d.r' 'readLAS.r' 'subcircled.r' 'tree_metrics.r' 'utils_colors.r' 'utils_geometry.r' 'utils_interpolations.r' 'utils_misc.r' 'utils_typecast.r' 'writeLAS.r' 'zzz.r' |
imports | data.table , geometry , grDevices , gstat , lazyeval , parallel , RANN , raster , Rcpp , rgeos , rgl , rlas (>= 1.1.0) , settings , sp , stats , tools , utils |
suggests | EBImage , hexbin , rgdal , testthat |
depends | magrittr , methods , R (>= 3.1.0) |
linkingto | RcppProgress |
Contributors | David Auty, Florian De Boissieu, Andrew S<c3><a1>nchez Meador |
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