Remove the topography from a point cloud
Subtract digital terrain model (DTM) from LiDAR point cloud to create a dataset normalized with
the ground at 0. The DTM can originate from an external file or can be computed by the user. It can
also be computed on-the-fly. In this case the algorithm does not use rasterized data and each point
is interpolated. There is no inaccuracy due to the discretization of the terrain and the resolution
of the terrain is virtually infinite.
How well the edges of the dataset are interpolated depends on the interpolation method used.
Thus, a buffer around the region of interest is always recommended to avoid edge effects.
The attribute Z of the returned LAS object is the normalized elevation. A new attribute 'Zref'
records the former elevation values, which enables the use of unnormalize_height to restore
original point elevations.
normalize_height( las, algorithm, na.rm = FALSE, use_class = c(2L, 9L), ..., add_lasattribute = FALSE, Wdegenerated = TRUE ) unnormalize_height(las) ## S4 method for signature 'LAS,RasterLayer' e1 - e2 ## S4 method for signature 'LAS,lidRAlgorithm' e1 - e2
las |
An object of class LAS or LAScatalog. |
algorithm |
a spatial interpolation function. |
na.rm |
logical. When using a |
use_class |
integer vector. By default the terrain is computed by using ground points (class 2) and water points (class 9). Relevant only for a normalisation without a raster DTM. |
... |
If |
add_lasattribute |
logical. By default the above see level elevation is retained in a new attribute.
However this new attribute will be discared at write time. If |
Wdegenerated |
logical. The function always check and remove degenerated ground points for computing the DTM to avoid unexpected behaviours such as infinite elevation. If TRUE a warning in thrown to alert about the presence of degenerated ground points. |
e1 |
a LAS object |
e2 |
RasterLayer representing a digital terrain model (can be
computed with grid_terrain) or a spatial interpolation function. |
If the input is a LAS object, return a LAS object. If the input is a
LAScatalog, returns a LAScatalog.
LAScatalog
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 for a LAScatalog (in bold). For more details see the
LAScatalog engine documentation:
chunk size: How much data is loaded at once.
chunk buffer*: Mandatory to get a continuous output without edge effects. The buffer is always removed once processed and will never be returned either in R or in files.
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.
Other normalize:
normalize_intensity()
LASfile <- system.file("extdata", "Topography.laz", package="lidR")
las <- readLAS(LASfile, filter = "-inside 273450 5274350 273550 5274450")
#plot(las)
# First option: use a RasterLayer as DTM
# =======================================================
dtm <- grid_terrain(las, 1, knnidw(k = 6L, p = 2))
las <- normalize_height(las, dtm)
plot(dtm)
#plot(las)
# restore original elevations
las <- unnormalize_height(las)
#plot(las)
# operator - can be used. This is equivalent to the previous
las <- las - dtm
#plot(las)
# restore original elevations
las <- unnormalize_height(las)
# Second option: interpolate each point (no discretization)
# =========================================================
las <- normalize_height(las, tin())
#plot(las)
# operator - can be used. This is equivalent to the previous
las <- unnormalize_height(las)
las <- las - tin()
## Not run:
# All the following syntaxes are correct
las <- normalize_height(las, knnidw())
las <- normalize_height(las, knnidw(k = 8, p = 2))
las <- las - knnidw()
las <- las - knnidw(k = 8)
las <- normalize_height(las, kriging())
las <- las - kriging(k = 8)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.