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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    [-gfczxb]    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

       --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

SEE ALSO

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

AUTHORS

       Vaclav Petras, NCSU OSGeoREL

       Last changed: $Date: 2015-10-01 03:55:00 +0200 (Thu, 01 Oct 2015) $

SOURCE CODE

       Available at: v.decimate source code (history)

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