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NAME

       r.grow.distance  - Generates a raster map containing distances to nearest raster features.

KEYWORDS

       raster, distance, proximity

SYNOPSIS

       r.grow.distance
       r.grow.distance --help
       r.grow.distance   [-mn]   input=name    [distance=name]    [value=name]    [metric=string]
       [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]

   Flags:
       -m
           Output distances in meters instead of map units

       -n
           Calculate distance to nearest NULL cell

       --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 raster map

       distance=name
           Name for distance output raster map

       value=name
           Name for value output raster map

       metric=string
           Metric
           Options: euclidean, squared, maximum, manhattan, geodesic
           Default: euclidean

DESCRIPTION

       r.grow.distance generates raster maps representing the distance to  the  nearest  non-null
       cell in the input map and/or the value of the nearest non-null cell.

NOTES

       The flag -n calculates the respective pixel distances to the nearest NULL cell.

       The user has the option of specifying five different metrics which control the geometry in
       which grown cells are created, (controlled by the metric parameter):  Euclidean,  Squared,
       Manhattan, Maximum, and Geodesic.

       The  Euclidean  distance or Euclidean metric is the "ordinary" distance between two points
       that one would measure with a ruler, which can be proven by repeated  application  of  the
       Pythagorean theorem.  The formula is given by:
       d(dx,dy) = sqrt(dx^2 + dy^2)
       Cells  grown  using  this  metric would form isolines of distance that are circular from a
       given point, with the distance given by the radius.

       The Squared metric is the Euclidean distance squared, i.e. it simply omits the square-root
       calculation. This may be faster, and is sufficient if only relative values are required.

       The Manhattan metric, or Taxicab geometry, is a form of geometry in which the usual metric
       of Euclidean geometry is replaced by a new metric in which the distance between two points
       is  the  sum  of  the (absolute) differences of their coordinates. The name alludes to the
       grid layout of most streets on the island of Manhattan, which causes the shortest  path  a
       car could take between two points in the city to have length equal to the points’ distance
       in taxicab geometry.  The formula is given by:
       d(dx,dy) = abs(dx) + abs(dy)
       where  cells  grown  using  this  metric  would  form  isolines  of  distance   that   are
       rhombus-shaped from a given point.

       The Maximum metric is given by the formula
       d(dx,dy) = max(abs(dx),abs(dy))
       where the isolines of distance from a point are squares.

       The   Geodesic   metric   is   calculated  as  geodesic  distance,  to  be  used  only  in
       latitude-longitude locations. It is recommended to use it along with the -m flag in  order
       to output distances in meters instead of map units.

EXAMPLES

   Distance from the streams network
       North Carolina sample dataset:
       g.region raster=streams_derived -p
       r.grow.distance input=streams_derived distance=dist_from_streams
       Euclidean distance from the streams network in meters (map subset)
       Euclidean  distance  from  the  streams  network  in  meters  (detail,  numbers shown with
       d.rast.num)

   Distance from sea in meters in latitude-longitude location
       g.region raster=sea -p
       r.grow.distance -m input=sea distance=dist_from_sea_geodetic metric=geodesic

       Geodesic distances to sea in meters

SEE ALSO

        r.grow, r.distance, r.buffer, r.cost, r.patch

        Wikipedia Entry: Euclidean Metric
       Wikipedia Entry: Manhattan Metric

AUTHORS

       Glynn Clements

       Last changed: $Date: 2016-01-21 14:23:39 +0100 (Thu, 21 Jan 2016) $

SOURCE CODE

       Available at: r.grow.distance source code (history)

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