lidR (version 3.0.4)

normalize_intensity: Normalize intensity

Description

Normalize intensity values using multiple methods.

Usage

normalize_intensity(las, algorithm)

Arguments

las

An object of class LAS or LAScatalog.

algorithm

an intensity normalizaton algorithm. lidR currently has range_correction.

Value

Returns an object of class LAS. The attribute 'Intensity' records the normalized intensity. An extra attribute named 'RawIntensity' records the original intensities.

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: How much data is loaded at once.

• chunk buffer: No buffer needed. A buffer of 0 is used and cannot be changed

• chunk alignment: Align the processed chunks.

• progress: Displays a progression estimation.

• output files*: Mandatory because the output is likely to be too big to be returned in R and needs to be written in las/laz files. Supported templates are {XLEFT}, {XRIGHT}, {YBOTTOM}, {YTOP}, {XCENTER}, {YCENTER} {ID} and, if chunk size is equal to 0 (processing by file), {ORIGINALFILENAME}.

• select: The function will write files equivalent to the original ones. Thus select = "*" and cannot be changed.

• filter: Read only points of interest.

See Also

Other normalize: normalize_height()

Examples

# NOT RUN {
# A valid file properly populated
LASfile <- system.file("extdata", "Topography.laz", package="lidR")
las <- readLAS(LASfile)

# pmin = 15 because it is an extremely small file
# strongly decimated to reduce its size. There are
# actually few multiple returns
sensor <- track_sensor(las, Roussel2020(pmin = 15))

# Here the effect is virtually null because the size of
# the sample is too small to notice any effect of range
las <- normalize_intensity(las, range_correction(sensor, Rs = 2000))
# }