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NAME

       v.decimate  - Decimates a point cloud
       Copies points from one vector to another while applying different decimations

KEYWORDS

       vector, LIDAR, generalization, decimation, extract, select, points, level1

SYNOPSIS

       v.decimate
       v.decimate --help
       v.decimate   [-gfczxbt]   input=name    [layer=string]    output=name    [zrange=min,max]    [cats=range]
       [skip=integer]       [preserve=integer]       [offset=integer]       [limit=integer]        [zdiff=float]
       [cell_limit=integer]   [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]

   Flags:
       -g
           Apply grid-based decimation

       -f
           Use only first point in grid cell during grid-based decimation

       -c
           Only one point per cat in grid cell

       -z
           Use z in grid decimation

       -x
           Store only the coordinates, throw away categories
           Do not story any categories even if they are present in input data

       -b
           Do not build topology
           Advantageous when handling a large number of points

       -t
           Do not create attribute table

       --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]
           Name of input vector map
           Or data source for direct OGR access

       layer=string
           Layer number or name (’-1’ for all layers)
           A  single vector map can be connected to multiple database tables. This number determines which table
           to use. When used with direct OGR access this is the layer name.
           Default: -1

       output=name [required]
           Name for output vector map

       zrange=min,max
           Filter range for z data (min,max)

       cats=range
           Category values
           Example: 1,3,7-9,13

       skip=integer
           Throw away every n-th point
           For example, 5 will import 80 percent of points. If not specified, all points are copied

       preserve=integer
           Preserve only every n-th point
           For example, 4 will import 25 percent of points. If not specified, all points are copied

       offset=integer
           Skip first n points
           Skips the given number of points at the beginning.

       limit=integer
           Copy only n points
           Copies only the given number of points

       zdiff=float
           Minimal difference of z values
           Minimal difference between z values in grid-based decimation

       cell_limit=integer
           Preserve only n points per grid cell
           Preserves only the given number of points per grid cell in grid-based decimation

DESCRIPTION

       v.decimate reduces number of points in the input vector map and copies them over  to  the  output  vector
       map. Different point decimation techniques can be applied to reduce the number of points.

       Two main decimation techniques are:

           •   count-based decimation (skip, preserve, offset and limit options)

           •   grid-based decimation (-g flag)

       The grid-based decimation will remove points based on:

           •   similar z coordinates (-z flag and zdiff option)

           •   same categories (-c flag)

           •   count of points (-f flag and cell_limit option)

       The grid-based decimation is currently using a 2D grid, so the points are placed and compared within this
       2D  grid.  The  comparison  can happen using z coordinates or categories.  Note that although the grid is
       only 2D, the module works with 3D points.

       The grid-based decimation extent and resolution depend on the current  computational  region  as  set  by
       g.region.  As a consequence, the output is limited only to computational region in this case.

       TODO: Currently, any output is limited by the region.

       The  count-based  decimation result highly depends on how the data are ordered in the input. This applies
       especially to offset and limit options where the resulting shape and densities  can  be  surprising.  The
       options  skip  and  preserve  are  influenced  by  order of points in a similar way but they usually keep
       relative density of points (which may or may  not  be  desired).   On  the  other  hand,  the  grid-based
       decimation will generally result in more even density of output points (see Figure 1).

       Besides decimation, point count can be reduced by applying different selections or filters, these are:

           •   selection by category (cats option)

           •   selection by z values (zrange option)

NOTES

       The  grid-based  decimation  requires all points which will be saved in output to fit into the computer’s
       memory (RAM).  It is advantageous to have the  region  only  in  the  area  with  the  points,  otherwise
       unnecessary  memory  is  allocated.  Higher (finer) resolutions and higher amount of preserved points per
       cell require more memory.  The count-based decimation has no limitation regarding the available memory.

       Significant speed up can be gained using -b flag which disables  building  of  topology  for  the  output
       vector  map. This may limit the use of the vector map by some modules, but for example, this module works
       without topology as well.

EXAMPLES

       Keep only every forth point, throw away the rest:
       v.decimate input=points_all output=points_decimated_every_4 preserve=4

       Keep only points within a grid cell  (given  by  the  current  computational  region)  which  has  unique
       categories (e.g. LIDAR classes):
       v.decimate input=points_all output=points_decimated_unique_cats layer=1 -g -c

         Figure  1:  Comparison  of  original  points,  decimation  result with every forth point preserved, and
       grid-based decimation result with points with unique categories in each grid cell

       Keep only points with category 2 and keep only approximately 80% of the points:
       v.decimate input=points_all output=points_decimated_ skip=5 cats=2 layer=1

REFERENCES

           •   Petras, V., Petrasova, A., Jeziorska, J., Mitasova, H. (2016). Processing  UAV  and  LiDAR  point
               clouds  in  grass  GIS.  The International Archives of Photogrammetry, Remote Sensing and Spatial
               Information Sciences, 41, 945 (DOI)

SEE ALSO

        v.extract, v.outlier, v.select, v.category, v.build, v.in.lidar, g.region

AUTHOR

       Vaclav Petras, NCSU OSGeoREL

SOURCE CODE

       Available at: v.decimate source code (history)

       Accessed: Monday Apr 01 03:08:35 2024

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       © 2003-2024 GRASS Development Team, GRASS GIS 8.3.2 Reference Manual

GRASS 8.3.2                                                                                   v.decimate(1grass)