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lidR (version 3.0.4)

clip: Clip points in regions of interest

Description

Clip points within a given region of interest (ROI) from a point cloud (LAS object) or a catalog (LAScatalog object). With a LAS object, the user first reads and loads a point cloud into memory and then can clip it to get a subset within a region of interest. With a LAScatalog object, the user can extract any arbitrary ROI for a set of las/laz files, loading only the points of interest. This is faster, easier and much more memory-efficient for extracting ROIs.

Usage

clip_roi(las, geometry, ...)
clip_rectangle(las, xleft, ybottom, xright, ytop, ...)
clip_polygon(las, xpoly, ypoly, ...)
clip_circle(las, xcenter, ycenter, radius, ...)
clip_transect(las, p1, p2, width, xz = FALSE, ...)

Arguments

las

An object of class LAS or LAScatalog.

geometry

a geometric object. Many types are supported, see section 'supported geometries'.

...

in clip_roi: optional supplementary options (see supported geometries). Unused in other functions

xleft

numeric. left x coordinates of rectangles.

ybottom

numeric. bottom y coordinates of rectangles.

xright

numeric. right x coordinates of rectangles.

ytop

numeric. top y coordinates of rectangles.

xpoly

numeric. x coordinates of a polygon.

ypoly

numeric. y coordinates of a polygon.

xcenter

numeric. x coordinates of disc centers.

ycenter

numeric. y coordinates of disc centers.

radius

numeric. disc radius or radii.

p1, p2

numeric vectors of length 2 that gives the coordinates of two points that define a transect

width

numeric. width of the transect.

xz

bool. If TRUE the point cloud is reoriented to fit on XZ coordinates

Value

If the input is a LAS object: an object of class LAS, or a list of LAS objects if the query implies several regions of interest will be returned. If the input is a LAScatalog object: an object of class LAS, or a list of LAS objects if the query implies several regions of interest will be returned, or a LAScatalog if the queries are immediately written into files without loading anything in R.

Supported geometries

Working with a <code>LAScatalog</code>

This section appears in each function that supports a LAScatalog as input.

In lidR when the input of a function is a LAScatalog the function uses the LAScatalog processing engine. The user can modify the engine options using the available options. A careful reading of the engine documentation is recommended before processing LAScatalogs. Each lidR function should come with a section that documents the supported engine options.

The LAScatalog engine supports .lax files that significantly improve the computation speed of spatial queries using a spatial index. Users should really take advantage a .lax files, but this is not mandatory.

Supported processing options

Supported processing options for a LAScatalog (in bold). For more details see the LAScatalog engine documentation:

  • chunk_size: Does not make sense here.

  • buffer: Not supported yet.

  • alignment: Does not makes sense here.

  • progress: Displays a progress estimation.

  • output_files: If 'output_files' is set in the catalog, the ROIs will not be returned in R. They will be written immediately in files. See LAScatalog-class and examples. The allowed templates in clip_* are {XLEFT}, {XRIGHT}, {YBOTTOM}, {YTOP}, {ID}, {XCENTER}, {YCENTER}. In addition clip_roi supports any names from the table of attributes of a spatial object given as input such as {PLOTID}, {YEAR}, {SPECIES}, for examples, if these attributes exist. If empty everything is returned into R.

  • laz_compression: write las or laz files

  • select: The function will write files equivalent to the originals. This option is not respected.

  • filter: Read only the points of interest.

Examples

Run this code
# NOT RUN {
LASfile <- system.file("extdata", "Megaplot.laz", package="lidR")

# Load the file and clip the region of interest
las = readLAS(LASfile)
subset1 = clip_rectangle(las, 684850, 5017850, 684900, 5017900)

# Do not load the file(s), extract only the region of interest
# from a bigger dataset
ctg = readLAScatalog(LASfile)
subset2 = clip_rectangle(ctg, 684850, 5017850, 684900, 5017900)

# Extract all the polygons from a shapefile
f <- system.file("extdata", "lake_polygons_UTM17.shp", package = "lidR")
lakes <- shapefile(f)
subset3 <- clip_roi(ctg, lakes)

# Extract the polygons, write them in files named after the lake names,
# do not load anything in R
opt_output_files(ctg) <- paste0(tempfile(), "_{LAKENAME_1}")
new_ctg = clip_roi(ctg, lakes)
#plot(mew_ctg)

# Extract a transect
LASfile <- system.file("extdata", "Topography.laz", package="lidR")
ctg <- readLAScatalog(LASfile)
p1 <- c(273357, y = 5274357)
p2 <- c(273642, y = 5274642)
tr1 <- clip_transect(ctg, p1, p2, width = 3)
tr2 <- clip_transect(ctg, p1, p2, width = 3, xz = TRUE)
plot(tr1, axis = TRUE, clear_artifacts = FALSE)
plot(tr2, axis = TRUE, clear_artifacts = FALSE)

# }
# NOT RUN {
plot(subset1)
plot(subset2)
plot(subset3)
# }

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