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Raster data processing in GRASS GIS

   Raster maps in general
       A  "raster  map" is a data layer consisting of a gridded array of cells.  It has a certain
       number of rows and columns, with a data point (or null  value  indicator)  in  each  cell.
       These  may  exist as a 2D grid or as a 3D cube made up of many smaller cubes, i.e. a stack
       of 2D grids.

       The geographic boundaries of the raster map are described by the north, south,  east,  and
       west fields. These values describe the lines which bound the map at its edges. These lines
       do NOT pass through the center of the grid cells at the edge of the  map,  but  along  the
       edge  of  the map itself.  i.e. the geographic extent of the map is described by the outer
       bounds of all cells within the map.

       As a general rule in GRASS GIS:

       1      Raster output maps have their bounds and resolution equal to those of  the  current
              computational region.

       2      Raster   input   maps   are   automatically   cropped/padded  and  rescaled  (using
              nearest-neighbour resampling) to match the current region.

       3      Raster input maps are automatically masked if a raster map named MASK  exists.  The
              MASK is only applied when reading maps from the disk.

       There  are  a few exceptions to this:* programs read the data cell-for-cell, with no
       resampling. When reading non-georeferenced data, the imported map will  usually  have  its
       lower-left  corner  at  (0,0)  in  the location’s coordinate system; the user needs to use
       r.region to "place" the imported map.

       Some programs which need to perform specific types of resampling (e.g.  r.resamp.rst) read
       the input maps at their original resolution then do the resampling themselves.

       r.proj  has  to  deal  with two regions (source and destination) simultaneously; both will
       have an impact upon the final result.

   Raster import and export
       The module  offers  a  common  interface  for  many  different  raster  formats.
       Additionally,  it also offers options such as on-the-fly location creation or extension of
       the default region to match the extent of the imported raster  map.   For  special  cases,
       other import modules are available. The full map is always imported.

       For  importing  scanned maps, the user will need to create a x,y-location, scan the map in
       the desired resolution and save it into an appropriate raster  format  (e.g.  tiff,  jpeg,
       png,  pbm)  and then use to import it. Based on reference points the scanned map
       can be recified to obtain geocoded data.

       Raster maps are exported with r.out.gdal into common formats. Also  r.out.bin,  r.out.vtk,
       r.out.ascii  and other export modules are available. They export the data according to the
       current region settings. If those differ from the original map, the map  is  resampled  on
       the  fly  (nearest  neighbor algorithm). In other words, the output will have as many rows
       and columns as the current region.  To  export  maps  with  various  grid  spacings  (e.g,
       500x500  or  200x500),  you  can  just change the region resolution with g.region and then
       export the map. The resampling is done with nearest neighbor algorithm in  this  case.  If
       you  want some other form of resampling, first change the region, then explicitly resample
       the map with e.g.  r.resamp.interp or r.resamp.stats, then export the resampled map.

       GRASS GIS raster map exchange between different locations (same projection) can be done in
       a lossless way using the r.pack and r.unpack modules.

       The  module  displays  general information about a map such as region extent, data
       range, data type, creation history, and other  metadata.   Metadata  such  as  map  title,
       units,  vertical  datum  etc.  can  be updated with Timestamps are managed with
       r.timestamp. Region extent and resolution are mangaged with r.region.

   Raster map operations
   Resampling methods and interpolation methods
       GRASS raster map processing is always  performed  in  the  current  region  settings  (see
       g.region),  i.e.  the  current region extent and current raster resolution is used. If the
       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 resampled beforehand with one of the dedicated modules.

       The built-in nearest-neighbour resampling of raster data calculates  the  centre  of  each
       region cell, and takes the value of the raster cell in which that point falls.

       If  the  point  falls exactly upon a grid line, the exact result will be determined by the
       direction of any rounding error. One consequence of this is that downsampling by a  factor
       which is an even integer will always sample exactly on the boundary between cells, meaning
       that the result is ill-defined.

       The  following  modules  are  available  for  reinterpolation  of  "filled"  raster   maps
       (continuous data) to a different resolution:

           ·   r.resample uses the built-in resampling, so it should produce identical results as
               the on-the-fly resampling done via the raster import modules.

           ·   r.resamp.interp Resampling with nearest neighbor, bilinear,  and  bicubic  method:
               method=nearest uses the same algorithm as r.resample, but not the same code, so it
               may not produce identical results in cases which are decided by  the  rounding  of
               floating-point numbers.
               For  r.resamp.interp  method=bilinear  and  method=bicubic,  the raster values are
               treated as samples at each raster cell’s centre, defining  a  piecewise-continuous
               surface.  The resulting raster values are obtained by sampling the surface at each
               region  cell’s  centre.   As  the  algorithm  only   interpolates,   and   doesn’t
               extrapolate,  a  margin  of  0.5 (for bilinear) or 1.5 (for bicubic) cells is lost
               from the extent of the original raster. Any samples taken within this margin  will
               be null.

           ·   r.resamp.rst  Regularized  Spline  with  Tension  (RST)  interpolation 2D: Behaves
               similarly, i.e. it computes a surface assuming that the values are samples at each
               raster cell’s centre, and samples the surface at each region cell’s centre.

           ·   r.resamp.bspline   Bicubic   or   bilinear   spline  interpolation  with  Tykhonov

           ·   For r.resamp.stats without -w, the  value  of  each  region  cell  is  the  chosen
               aggregate of the values from all of the raster cells whose centres fall within the
               bounds of the region cell.
               With -w, the samples are weighted according to the proportion of the  raster  cell
               which  falls  within  the  bounds  of  the  region cell, so the result is normally
               unaffected by rounding error (a  minuscule  difference  in  the  position  of  the
               boundary  results  in  the  addition  or  subtraction  of  a  sample weighted by a
               minuscule factor; also, The min and max aggregates can’t use weights, so -w has no
               effect for those).

           ·   r.fillnulls  for  Regularized  Spline with Tension (RST) interpolation 2D for hole
               filling (e.g., SRTM DEM)

       Furthermore, there are modules available for reinterpolation of "sparse" (scattered points
       or lines) maps:

           ·   Inverse distance weighted average (IDW) interpolation (

           ·   Interpolating from contour lines (r.contour)

           ·   Various vector modules for interpolation
       For  Lidar  and  similar  data,  and  support loading and binning of
       ungridded x,y,z ASCII data into a new raster map.  The user may choose from a  variety  of
       statistical methods in creating the new raster map.

       Otherwise, for interpolation of scattered data, use the* set of modules.

   Raster MASKs
       If  a  raster map named "MASK" exists, most GRASS raster modules will operate only on data
       falling inside the masked area, and treat any data falling outside of the mask as  if  its
       value  were  NULL. The mask is only applied when reading an existing GRASS raster map, for
       example when used in a module as an input map.

       The mask is read as an integer map. If MASK is actually a floating-point map,  the  values
       will  be  converted  to  integers  using  the  map’s  quantisation rules (this defaults to
       round-to-nearest, but can be changed with r.quant).

       (see r.mask)

   Raster map statistics
       A couple of commands are available to calculate local statistics (r.neighbors), and global
       statistics   (r.statistics,   Profiles  and  transects  can  be  generated
       (d.profile, r.profile, r.transect) as well as histograms (d.histogram) and polar  diagrams
       (d.polar).    Univariate   statistics   (r.univar)   and   reports   are   also  available
       (,r.stats, r.volume).

   Raster map algebra and aggregation
       The r.mapcalc command provides raster map algebra  methods.   The  r.resamp.stats  command
       resamples  raster  map  layers using various aggregation methods, the r.statistics command
       aggregates one map based on a second map.  r.resamp.interp  resamples  raster  map  layers
       using interpolation.

   Regression analysis
       Both   linear   (r.regression.line)   and  multiple  regression  (r.regression.multi)  are

   Hydrologic modeling toolbox
       Watershed modeling related modules are  r.basins.fill,  r.water.outlet,  r.watershed,  and
       r.terraflow.   Water  flow  related modules are r.carve, r.drain, r.fill.dir, r.fillnulls,
       r.flow, and r.topidx.  Flooding can be simulated with r.lake.  Hydrologic simulation model
       are available as r.sim.sediment, r.sim.water, and r.topmodel.

   Raster format
       In GRASS GIS, raster data can be stored as 2D or 3D grids.

   2D raster maps
       2D  rasters  support  three  data  types  (for technical details, please refer to the Wiki
       article GRASS raster semantics):

           ·   32bit signed integer (CELL),

           ·   single-precision floating-point (FCELL), and

           ·   double-precision floating-point (DCELL).
       In most GRASS GIS resources, 2D raster maps are usually called "raster" maps.

   3D raster maps
       The 3D raster map type is usually called "3D raster"  but  other  names  like  "RASTER3D",
       "voxel",  "volume", "GRID3D" or "3d cell" are yet common.  3D rasters support only single-
       and double-precision floating-point.  3D raster’s single-precision data type is most often
       called "float", and the double-precision one "double".

   No-data management and data portability
       GRASS  GIS  distinguishes  NULL  and zero. When working with NULL data, it is important to
       know that operations on NULL cells lead to NULL cells.

       The GRASS GIS raster format is architecture independent and  portable  between  32bit  and
       64bit machines.

   Raster compression
       All  GRASS  GIS raster map types are by default ZLIB compressed, i.e. using ZLIB’s deflate
       algorithm. Through the environment variable GRASS_COMPRESSOR the compression method can be
       set to RLE, ZLIB, LZ4, or BZIP2.

       Important:   the   NULL  file  compression  must  be  explicitly  turned  on  with  export
       GRASS_COMPRESS_NULLS=1 - such raster maps can then only be opened with GRASS GIS 7.2.0  or
       later. NULL file compression can be managed with r.null -z.

       Integer  (CELL  type)  raster  maps can be compressed with RLE if the environment variable
       GRASS_INT_ZLIB exists and is set to value 0. However, this is not recommended.

       Floating point (FCELL, DCELL) raster maps never  use  RLE  compression;  they  are  either
       compressed with ZLIB, LZ4, BZIP2 or are uncompressed.

           DEPRECATED  Run-Length  Encoding,  poor  compression  ratio  but  fast. It is kept for
           backwards compatibility to read raster maps created with GRASS 6. It is only used  for
           raster  maps  of  type  CELL.   FCELL  and  DCELL  maps  are never and have never been
           compressed with RLE.

           ZLIB’s deflate is the default compression method for all raster maps. GRASS GIS 7 uses
           by  default 1 as ZLIB compression level which is the best compromise between speed and
           compression ratio, also when compared to other available  compression  methods.  Valid
           levels  are  in  the  range  [1,  9]  and  can  be  set  with the environment variable

           LZ4 is a very fast compression method, about as fast as no compression.  Decompression
           is  also  very  fast. The compression ratio is generally higher than for RLE but worse
           than for ZLIB. LZ4 is recommended if disk space is not a limiting factor.

           BZIP2 can provide compression ratios much higher than the other methods, but only  for
           large raster maps (> 10000 columns). For large raster maps, disk space consumption can
           be reduced by 30 - 50% when using BZIP2  instead  of  ZLIB’s  deflate.  BZIP2  is  the
           slowest  compression and decompression method. However, if reading from / writing to a
           storage device is the limiting factor, BZIP2  compression  can  speed  up  raster  map
           processing.  Be  aware  that  for  smaller raster maps, BZIP2 compression ratio can be
           worse than other compression methods.

       In the internal cellhd file, the value for "compressed" is 1 for RLE, 2 for  ZLIB,  3  for
       LZ4, and 4 for BZIP2.

       Obviously,   decompression  is  controlled  by  the  raster  map’s  compression,  not  the
       environment variable.

   See also
           ·   Introduction into 3D raster data (voxel) processing

           ·   Introduction into vector data processing

           ·   Introduction into image processing

           ·   Introduction into temporal data processing

           ·   Database management

           ·   Projections and spatial transformations


       Available at: Raster data processing in GRASS GIS source code (history)

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       © 2003-2018 GRASS Development Team, GRASS GIS 7.4.0 Reference Manual