Ubuntu Manpage: 3D raster maps in general

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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 tile layout of the RASTER3D library

Terminology and naming
GRASS GIS uses terminology where continuous 3D data represented by regular grid or lattice
is called 3D raster map. 3D raster map works in 3D in the same 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).
While the term layer emphasizes overlaying or stacking up. The former is not the only
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 as the (2D) raster map. A cell is a
cuboid or cube 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, for example in Python, 3D raster related things
can be referred differently, for example according to a programming language standards.
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. 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
The modules r3.in.ascii and r3.in.bin supports generic x,y,z ASCII and binary array
import. Alternatively, 3D rasters can be generated from 3D point vector data
(v.to.rast3). Always the full map is imported. 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. 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.

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). Note that Vis5D is limited in the number of supported volumes.

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

• Temporal data processing

• Projections and spatial transformations

• wxGUI 3D View Mode

• m.nviz.image

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