**-a**- Do not align output with the input
**-c**- Use circular neighborhood
**--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

**input**=*name***[required]**- Name of input raster map
**selection**=*name*- Name of an input raster map to select the cells which should be processed
**output**=*name[,**name*,...]**[required]**- Name for output raster map
**size**=*integer*- Neighborhood size
- Default:
*3* **method**=*string[,**string*,...]- Neighborhood operation
- Options:
*average, median, mode, minimum, maximum, range, stddev, sum, count, variance, diversity, interspersion, quart1, quart3, perc90, quantile* - Default:
*average* **weighting_function**=*string*- Weighting function
- Options:
*none, gaussian, exponential, file* - Default:
*none* **none**: No weighting**gaussian**: Gaussian weighting function**exponential**: Exponential weighting function**file**: File with a custom weighting matrix**weighting_factor**=*float*- Factor used in the selected weighting function (ignored for none and file)
**weight**=*name*- Text file containing weights
**quantile**=*float[,**float*,...]- Quantile to calculate for method=quantile
- Options:
*0.0-1.0* **title**=*phrase*- Title for output raster map
**nprocs**=*integer*- Number of threads for parallel computing
- Default:
*1* **memory**=*memory in MB*- Maximum memory to be used (in MB)
- Cache size for raster rows
- Default:
*300*

The user can optionally
specify a **selection** map, to compute new values only where the raster
cells of the selection map are not NULL. In case of a NULL cells,
the values from the input map are copied into the output map.
This may useful to smooth only parts of an elevation map (pits, peaks, ...).

*Example how to use a selection map with method=average:*

input map:

1 1 1 1 1 1 1 1 1 1 1 1 10 1 1 1 1 1 1 1 1 1 1 1 1

* * * * * * * 1 * * * 1 1 1 * * * 1 * * * * * * *

1 1 1 1 1 1 1 2 1 1 1 2 2 2 1 1 1 2 1 1 1 1 1 1 1

1 1 1 1 1 1 2 2 2 1 1 2 2 2 1 1 2 2 2 1 1 1 1 1 1

It is also possible to weigh cells within the neighborhood. This can be either done with a custom weights matrix or by specifying a weighting function.

In order to use a custom weights matrix, *file* needs to be
specified as a **weighting_function** and a path to a text file
containing the weights needs to be given in the **weight** option.

Alternatively, *gaussian* and *exponential* weighting
functions can be selected as weighting function.

For the *gaussian* weighting function, the user specifies the
sigma value (σ) for the gauss filter in the **weighting_factor**
option. The sigma value represents the standard deviation of the gaussian
distribution, where the weighting formula for the gaussian filter is
defined as follows:

exp(-(x*x+y*y)/(2*σ^2))/(2*π*σ^2)

Lower values for sigma result in a steeper curve, so that more weight is put on cells close to the center of the moving window with a steeper decrease in weights with distance from the center.

For the *exponential* weighting function, the user specifies a
factor for an exponential kernel in the **weighting_factor**.
Negative factors result in negative exponential decrease in weights from
the center cell. The weighting formula for the exponential kernel is
defined as follows:

exp(factor*sqrt(x*x+y*y))

Stronger negative values for the factor result in a steeper curve, so that more weight is put on cells close to the center of the moving window with a steeper decrease in weights with distance from the center.

Optionally, the user can also run * r.neighbors* specify
the

*Neighborhood Operation Methods:*
The **neighborhood** operators determine what new
value a center cell in a neighborhood will have after examining
values inside its neighboring cells.
Each cell in a raster map layer becomes the center cell of a neighborhood
as the neighborhood window moves from cell to cell throughout the map layer.
* r.neighbors* can perform the following operations:

**average**- The average value within the neighborhood.
In the following example, the result would be:

(7*4 + 6 + 5 + 4*3)/9 = 5.6667

The result is rounded to the nearest integer (in this case 6).Raw Data Operation New Data +---+---+---+ +---+---+---+ | 7 | 7 | 5 | | | | | +---+---+---+ average +---+---+---+ | 4 | 7 | 4 |--------->| | 6 | | +---+---+---+ +---+---+---+ | 7 | 6 | 4 | | | | | +---+---+---+ +---+---+---+

**median**- The value found half-way through a list of the neighborhood's values, when these are ranged in numerical order.
**mode**- The most frequently occurring value in the neighborhood.
**minimum**- The minimum value within the neighborhood.
**maximum**- The maximum value within the neighborhood.
**range**- The range value within the neighborhood.
**stddev**- The statistical standard deviation of values within the neighborhood (rounded to the nearest integer).
**sum**- The sum of values within the neighborhood.
**count**- The count of filled (not NULL) cells.
**variance**- The statistical variance of values within the neighborhood (rounded to the nearest integer).
**diversity**- The number of different values within the neighborhood. In the above example, the diversity is 4.
**interspersion**- The percentage of cells containing values which differ from the values
assigned to the center cell in the neighborhood, plus 1.
In the above example, the interspersion is:

5/8 * 100 + 1 = 63.5

The result is rounded to the nearest integer (in this case 64). **quart1, quart3**- The result will be the first or the third quartile (equal of 25th and 75th percentiles).
**perc90**- The result will be the 90th percentile of neighborhood.
**quantile**- Any quantile as specified by "quantile" input parameter.

*Neighborhood Size:*
The neighborhood **size** specifies which cells surrounding any given
cell fall into the neighborhood for that cell.
The **size** must be an odd integer and represent the length of one of
moving window edges in cells.
For example, a size value of 3 will result in

_ _ _ |_|_|_| 3 x 3 neighborhood ---> |_|_|_| |_|_|_|

*Matrix weights:*
A custom matrix can be used if none of the neighborhood operation
methods are desirable by using the **weight**. This option must
be used in conjunction with the **size** option to specify the
matrix size and *file* needs to be specified as
**weighting_function**. The weights desired are to be entered into a
text file. For example, to calculate the focal mean with a matrix
**size** of 3,

r.neigbors in=input.map out=output.map size=3 weighting_function=file \ weight=weights.txt

3 3 3 1 4 8 9 5 3

+-+-+-+ |3|3|3| +-+-+-+ |1|4|8| +-+-+-+ |9|5|3| +-+-+-+

0 1 1 1 0 1 0 0 0 1 1 0 0 0 1 1 0 0 0 1 0 1 1 1 0

sum(w[i]*x[i]) / sum(w[i])

**-a**- If specified,
will not align the output raster map layer with that of the input raster map layer. The**r.neighbors**program works in the current geographic region. It is recommended, but not required, that the resolution of the geographic region be the same as that of the raster map layer. By default, if unspecified,**r.neighbors**will align these geographic region settings.**r.neighbors** **-c**-
This flag will use a circular neighborhood for the moving analysis window,
centered on the current cell.
The exact masks for the first few neighborhood sizes are as follows:

3x3 . X . 5x5 . . X . . 7x7 . . . X . . . X O X . X X X . . X X X X X . . X . X X O X X . X X X X X . . X X X . X X X O X X X . . X . . . X X X X X . . X X X X X . . . . X . . . 9x9 . . . . X . . . . 11x11 . . . . . X . . . . . . . X X X X X . . . . X X X X X X X . . . X X X X X X X . . X X X X X X X X X . . X X X X X X X . . X X X X X X X X X . X X X X O X X X X . X X X X X X X X X . . X X X X X X X . X X X X X O X X X X X . X X X X X X X . . X X X X X X X X X . . . X X X X X . . . X X X X X X X X X . . . . . X . . . . . X X X X X X X X X . . . X X X X X X X . . . . . . . X . . . . .

* r.neighbors* doesn't propagate NULLs, but computes the
aggregate over the non-NULL cells in the neighborhood.

The **-c** flag and the **weights** parameter are mutually exclusive. Any
use of the two together will produce an error. Differently-shaped neighborhood
analysis windows may be achieved by using the **weight=** parameter to
specify a weights file where all values are equal. The user can also vary the
weights at the edge of the neighborhood according to the proportion of the cell
that lies inside the neighborhood circle, effectively anti-aliasing the analysis
mask.

For aggregates where a weighted calculation isn't meaningful (specifically: minimum, maximum, diversity and interspersion), the weights are used to create a binary mask, where zero causes the cell to be ignored and any non-zero value causes the cell to be used.

* r.neighbors* copies the GRASS

- Whether the input map is integer or floating-point.
- Whether the weighted or unweighted version of the aggregate is used.

input type/weight | integer | float | ||
---|---|---|---|---|

no | yes | no | yes | |

average | float | float | float | float |

median | [1] | [1] | float | float |

mode | integer | integer | [2] | [2] |

minimum | integer | integer | float | float |

maximum | integer | integer | float | float |

range | integer | integer | float | float |

stddev | float | float | float | float |

sum | integer | float | float | float |

count | integer | float | integer | float |

variance | float | float | float | float |

diversity | integer | integer | integer | integer |

interspersion | integer | integer | integer | integer |

quart1 | [1] | [1] | float | float |

quart3 | [1] | [1] | float | float |

perc90 | [1] | [1] | float | float |

quantile | [1] | [1] | float | float |

[1] For integer input, quantiles may produce float results from
interpolating between adjacent values.

[2] Calculating the mode of floating-point data is essentially
meaningless.

With the current aggregates, there are 5 cases:

- Output is always float: average, variance, stddev, quantiles (with interpolation).
- Output is always integer: diversity, interspersion.
- Output is integer if unweighted, float if weighted: count.
- Output matches input: minimum, maximum, range, mode (subject to note 2 above), quantiles (without interpolation).
- Output is integer for integer input and unweighted aggregate, otherwise float: sum.

To reduce the memory requirements to minimum, set option **memory** to zero.
To take advantage of the parallelization, GRASS GIS
needs to be compiled with OpenMP enabled.

g.region rows=10 cols=10

r.random.cells output=random_cells distance=0 ncells=50

r.neighbors input=random_cells output=counts method=count

r.mapcalc "count_around = if( isnull(random_cells), counts, counts - 1)"

Updates for GRASS GIS 7 by Glynn Clements and others

Available at: r.neighbors source code (history)

Latest change: Tuesday Apr 26 13:35:34 2022 in commit: 1c7f66747d7c7b68ae88d5d3b0feae59141633c5

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© 2003-2022 GRASS Development Team, GRASS GIS 8.3.dev Reference Manual