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3D raster data in GRASS GIS

   3D raster maps in general
       GRASS  GIS  is one of the few GIS software packages with 3D raster data support.  Data are
       stored as a 3D raster with 3D cells of a given volume.  3D rasters are designed to support
       representations  of trivariate continuous fields.  The vertical dimension supports spatial
       and temporal units.  Hence space time 3D raster with different temporal resolutions can be
       created and processed.

       GRASS  GIS 3D raster maps use the same coordinate system as 2D raster maps (row count from
       north to south) with an additional z dimension (depth) counting from bottom  to  top.  The
       upper  left  corner  (NW)  is  the origin.  3D rasters are stored using a tile cache based
       approach. This allows arbitrary read and write operations in the created  3D  raster.  The
       size  of  the  tiles  can  be  specified at import time with a given import module such as
       r3.in.ascii or the data can be retiled using r3.retile after import or creation.
        The 3D raster map coordinate system and the internal tile layout of the RASTER3D library

   Terminology and naming
       In GRASS GIS terminology, continuous 3D data represented by regular  grid  or  lattice  is
       called 3D raster map.  3D raster map works in 3D in the same was as (2D) raster map in 2D,
       so it is called the same except for the additional 3D.  Some literature or other  software
       may  use  terms  such  as  3D  grid, 3D lattice, 3D matrix, 3D array, volume, voxel, voxel
       model, or voxel cube.  Note that terms volume and  volumetric  often  refer  to  measuring
       volume (amount) of some substance which may or may not be related to 3D rasters.

       Note  that  GRASS GIS uses the term 3D raster map or just 3D raster for short, rather than
       3D raster layer because term map emphasizes the mapping of positions to  values  which  is
       the  purpose of 3D raster map (in mathematics, map or mapping is close to a term function)
       On the other hand, the term layer emphasizes overlaying or stacking up.  The former is not
       the  only  operation done with data and the latter could be confusing in case of 3D raster
       data.

       3D raster map is divided into cells in the same way as the (2D) raster map.  A cell  is  a
       cube  or  a  (rectangular)  cuboid depending on the resolution.  The resolution influences
       volume of one cell.  Some literature or other software  may  use  terms  such  as  volume,
       volume  unit,  volumetric pixel, volume pixel, or voxel.  Note that voxel can be sometimes
       used to refer to a whole 3D raster and that for example in 3D computer graphics, voxel can
       denote object with some complicated shape.

       Type  of  map and element name in GRASS GIS is called raster_3d.  The module family prefix
       is r3.  Occasionally, 3D raster related things can be referred  differently,  for  example
       according  to  a programming language standards.  This might be the case of some functions
       or classes in Python.

       In GRASS GIS 3D rasters as stored in tiles which are hidden from user most  of  the  time.
       When  analyzing or visualizing 3D rasters user can create slices or cross sections. Slices
       can be horizontal, vertical,  or  general  plains  going  through  a  3D  raster.  Slices,
       especially  the  horizontal  ones,  may  be called layers in some literature or some other
       software.  Cross sections are general functions, e.g. defined by 2D raster, going  through
       a  3D  raster.   Another often used term is an isosuface which has the same relation to 3D
       raster as contour (isoline) to a 2D raster. An isosurface  is  a  surface  that  represent
       places with a constant value.

       When 3D raster is used in the way that vertical dimension represents time 3D raster can be
       referred to as space time cubes (STC) or space time cube 3D raster.  Some  literature  may
       also use space time voxel cube, space time voxel model or some other combination.

   3D raster import
   Import from external files
       The  modules  r3.in.ascii  and  r3.in.bin  supports  generic  x,y,z ASCII and binary array
       import.

       In case of CSV tables, the modules v.in.ascii (using the -z flag) may be a choice to first
       import the 3D points as vector points and the convert them to 3D raster (see below).

       Import  of  3D (LiDAR) points and their statistics can be done using r3.in.lidar for LiDAR
       data and r3.in.xyz for CSV and other ASCII text formats.

   Conversion from 3D vector points
       3D rasters can be generated from 3D point vector data (v.to.rast3). Always the full map is
       imported.

   Conversion from 2D raster maps
       3D  raster  can  also  be  created  based  on  2D elevation map(s) and value raster map(s)
       (r.to.rast3elev). Alternatively, a 3D raster can be composed of  several  2D  raster  maps
       (stack  of maps).  2D rasters are considered as slices in this case and merged into one 3D
       raster map (r.to.rast3).

   3D region settings and 3D MASK
       GRASS GIS 3D raster map processing is always performed in the current 3D  region  settings
       (see g.region, -p3 flags), i.e.  the current region extent, vertical extent and current 3D
       resolution are used.  If the 3D resolution differs from that of the input  raster  map(s),
       on-the-fly resampling is performed (nearest neighbor resampling).  If this is not desired,
       the input map(s) has/have to be  reinterpolated  beforehand  with  one  of  the  dedicated
       modules.  Masks can be set (r3.mask).

   3D raster analyses and operations
       Powerful  3D raster map algebra is implemented in r3.mapcalc.  A 3D groundwater flow model
       is implemented in r3.gwflow.

   3D raster conversion to vector or 2D raster maps
       Slices from a 3D raster map can be converted to  a  2D  raster  map  (r3.to.rast).   Cross
       sectional  2D  raster  map can be extracted from 3D raster map based on a 2D elevation map
       (r3.cross.rast).

   3D raster statistics
       3D raster statistics can be calculated with r3.stats and r3.univar.

   3D raster interpolation
       From 3D vector points, GRASS 3D raster maps can be interpolated (v.vol.rst).  Results  are
       3D raster maps, however 2D raster maps can be also extracted.

   3D raster export
       The  modules  r3.out.ascii and r3.out.bin support the export of 3D raster maps as ASCII or
       binary files. The output of these modules can be imported with  the  corresponding  import
       modules noted above.

       NetCDF  export  of  3D  raster  maps  can  be performed using the module r3.out.netcdf. It
       supports 3D raster maps with spatial dimensions and temporal (vertical) dimension.

   Working with 3D visualization software
       GRASS GIS can be used for visualization of 3D rasters, however it has also tools to easily
       export the data into other visualization packages.

       GRASS  GIS  3D  raster  maps  can  be  exported to VTK using r3.out.vtk.  VTK files can be
       visualized with the VTK Toolkit, Paraview and MayaVi.  Moreover, GRASS GIS 2D raster  maps
       can  be  exported  to  VTK with r.out.vtk and GRASS GIS vector maps can be exported to VTK
       with v.out.vtk.

       Alternatively, GRASS 3D raster maps can be imported and exported from/to Vis5D (r3.in.v5d,
       r3.out.v5d).

   3D raster data types
       3D  raster’s  single-precision  data type is most often called "FCELL" or "float", and the
       double-precision one "DCELL" or "double".

   See also
           •   Introduction into raster data processing

           •   Introduction into vector data processing

           •   Introduction into image processing

           •   Introduction into temporal data processing

           •   Projections and spatial transformations

           •   wxGUI 3D View Mode

           •   m.nviz.image

SOURCE CODE

       Available at: 3D raster data in GRASS GIS source code (history)

       Accessed: Saturday Jun 24 10:01:41 2023

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