NAME

       r3.in.xyz   -  Create  a  3D  raster  map  from  an  assemblage  of many coordinates using
       univariate statistics

KEYWORDS

       raster3d, import, voxel, LIDAR, statistics, conversion, aggregation, binning

SYNOPSIS

       r3.in.xyz
       r3.in.xyz --help
       r3.in.xyz    [-sgi]    input=name     output=name      [method=string]       [type=string]
       [separator=character]    [x=integer]    [y=integer]   [z=integer]   [value_column=integer]
       [vrange=min,max]    [vscale=float]    [percent=integer]     [pth=integer]     [trim=float]
       [workers=integer]   [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]

   Flags:
       -s
           Scan data file for extent then exit

       -g
           In scan mode, print using shell script style

       -i
           Ignore broken lines

       --overwrite
           Allow output files to overwrite existing files

       --help
           Print usage summary

       --verbose
           Verbose module output

       --quiet
           Quiet module output

       --ui
           Force launching GUI dialog

   Parameters:
       input=name [required]
           ASCII file containing input data

       output=name [required]
           Name for output raster map

       method=string
           Statistic to use for raster values
           Options:  n,  min,  max,  range,  sum,  mean,  stddev,  variance,  coeff_var,  median,
           percentile, skewness, trimmean
           Default: mean

       type=string
           Storage type for resultant raster map
           Options: float, double
           Default: float

       separator=character
           Field separator
           Special characters: pipe, comma, space, tab, newline
           Default: pipe

       x=integer
           Column number of x coordinates in input file (first column is 1)
           Default: 1

       y=integer
           Column number of y coordinates in input file
           Default: 2

       z=integer
           Column number of z coordinates in input file
           Default: 3

       value_column=integer
           Column number of data values in input file
           If not given or set to 0, the data points’ z-values are used
           Default: 0

       vrange=min,max
           Filter range for value column data (min,max)

       vscale=float
           Scaling factor to apply to value column data
           Default: 1.0

       percent=integer
           Percent of map to keep in memory
           Options: 1-100
           Default: 100

       pth=integer
           pth percentile of the values
           Options: 1-100

       trim=float
           Discard <trim> percent of the smallest and <trim> percent of the largest observations
           Options: 0-50

       workers=integer
           Number of parallel processes to launch
           Options: 1-256
           Default: 1

DESCRIPTION

       r3.in.xyz imports sparse XYZ data from an ASCII file into a 3D  raster  map  (voxels).  It
       does  this  by  running the r.in.xyz module multiple times for different z-ranges and then
       assembling the slices with r.to.rast3.

       See the r.in.xyz help page for general parameter usage and tips.

       The map is created using the rows, columns, and depths set by current region settings.  Be
       sure to check and adjust these with the g.region module before performing the import.

       You  may  either  use  the  z-value  as  the  data  value for the voxel (e.g. with the ’n’
       statistic), or alternately scan another column for the data values to bin into the voxels.
       This alternate data column can be both filtered by range and have a scaling factor applied
       to it.

NOTES

       The 2D and 3D horizontal region resolutions must match. See the EXAMPLES section below.

       Unlike r.in.xyz, reading from stdin and z-scaling are not possible. Filtering  by  z-range
       is accomplished by setting the 3D region.

       To enable parallel processing support, set the workers= option to match the number of CPUs
       or CPU-cores available on your system.  Alternatively, the  WORKERS  environment  variable
       can be set to the number of concurrent processes desired.

       Points  falling  exactly  on  a  vertical  bound will belong to the depth band below them,
       except for points exactly on the top bound, which will belong to the top-most slice.

       The script is expected to be nearly as efficient as if it was fully written in C.

EXAMPLE

       Using the Serpent Mound dataset. (see the GRASS LiDAR wiki page)
         #scan dataset for extent:
         r3.in.xyz -s in=Serpent_Mound_Model_LAS_Data.txt out=dummy \
            x=1 y=2 z=3 separator=space
         # set the 2D and 3D regions:
         g.region n=4323641.57 s=4320942.61 w=289020.90 e=290106.02 res=1 -a
         g.region b=166 t=216 res3=1 tbres=5 -3 -p
         r3.in.xyz in=Serpent_Mound_Model_LAS_Data.txt out=serpent3D \
            method=mean x=1 y=2 z=3 separator=space type=float
       The same, but aggregate and store backscatter  strength  from  column  5  into  voxels  in
       instead of the z-value:
         r3.in.xyz in=Serpent_Mound_Model_LAS_Data.txt out=serpent3D.bakscat \
            method=mean x=1 y=2 z=3 val=5 separator=space type=float

KNOWN ISSUES

       r.to.rast3 always creates a double output map regardless of input.

SEE ALSO

        g.region, r.in.xyz, r.to.rast3

AUTHOR

       Hamish Bowman
       Dunedin, New Zealand

SOURCE CODE

       Available at: r3.in.xyz source code (history)

       Accessed: Tuesday Jun 27 11:14:34 2023

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