GDAL-RASTER-NEIGHBORS(1) GDAL GDAL-RASTER-NEIGHBORS(1)
gdal-raster-neighbors - Compute the value of each pixel from its
neighbors (focal statistics)
Added in version 3.12.
Usage: gdal raster neighbors [OPTIONS] <INPUT> <OUTPUT>
Compute the value of each pixel from its neighbors (focal statistics)
Positional arguments:
-i, --input <INPUT> Input raster datasets [required]
-o, --output <OUTPUT> Output raster dataset [required]
Common Options:
-h, --help Display help message and exit
--json-usage Display usage as JSON document and exit
--config <KEY>=<VALUE> Configuration option [may be repeated]
-q, --quiet Quiet mode (no progress bar)
Options:
-f, --of, --format, --output-format <OUTPUT-FORMAT> Output format ("GDALG" allowed)
--co, --creation-option <KEY>=<VALUE> Creation option [may be repeated]
--overwrite Whether overwriting existing output is allowed
Mutually exclusive with --append
--append Append as a subdataset to existing output
Mutually exclusive with --overwrite
-b, --band <BAND> Input band (1-based index)
--method <METHOD> Method to combine weighed source pixels. METHOD=mean|sum|min|max|stddev|median|mode [may be repeated]
--size <SIZE> Neighborhood size
--kernel <KERNEL> Convolution kernel(s) to apply [1.. values] [required]
--ot, --datatype, --output-data-type <OUTPUT-DATA-TYPE> Output data type. OUTPUT-DATA-TYPE=Byte|Int8|UInt16|Int16|UInt32|Int32|UInt64|Int64|CInt16|CInt32|Float16|Float32|Float64|CFloat32|CFloat64 (default: Float64)
--nodata <NODATA> Assign a specified nodata value to output bands ('none', numeric value, 'nan', 'inf', '-inf')
Advanced Options:
--if, --input-format <INPUT-FORMAT> Input formats [may be repeated]
--oo, --open-option <KEY>=<VALUE> Open options [may be repeated]
gdal raster neighbors applies a kernel (convolution matrix) and a
method to compute the target pixel value from a neighbourhood of the
source pixel value.
At the top edge, the values of the first row are replicated to
virtually extend the source window by a number of rows equal to the
radius of the kernel. And similarly for the bottom, left and right
edges. This strategy may potentially lead to unexpected results
depending on the applied kernel.
For a given target cell, if the corresponding source value (the one
at the center of the kernel) is nodata, the resulting pixel is
nodata. For other source values in the neighborhood defined by the
kernel, source nodata values are ignored.
This algorithm can be part of a gdal pipeline or gdal raster
pipeline.
The following options are available:
-f, --of, --format, --output-format <OUTPUT-FORMAT>
Which output raster format to use. Allowed values may be given
by gdal --formats | grep raster | grep rw | sort
--co, --creation-option <NAME>=<VALUE>
Many formats have one or more optional creation options that
can be used to control particulars about the file created. For
instance, the GeoTIFF driver supports creation options to
control compression, and whether the file should be tiled.
May be repeated.
The creation options available vary by format driver, and some
simple formats have no creation options at all. A list of
options supported for a format can be listed with the
--formats command line option but the documentation for the
format is the definitive source of information on driver
creation options. See Raster drivers format specific
documentation for legal creation options for each format.
--overwrite
Allow program to overwrite existing target file or dataset.
Otherwise, by default, gdal errors out if the target file or
dataset already exists.
--band <BAND>
Source band number (indexing starts at one). If it is not
specified, all input bands are used.
--kernel
Convolution kernel to apply to source pixels in a neighborhood
of each pixel.
+o either the name of a well-known kernel, among edge1, edge2,
sharpen, gaussian, or unsharp-masking, corresponding to
those kernels (convolution matrix), with the addition of:
+o equal corresponding to a kernel with all coefficients at
one kernel size can be any odd number between 3 and 99):
\begin{align}
\begin{bmatrix} 1 & 1 & 1\\ 1 & 1 & 1 \\ 1 & 1 & 1
\end{bmatrix} \end{align}
For method mean, this corresponds to a box blur filter.
+o u corresponding to an horizontal derivative with
coefficients:
\begin{align}
\begin{bmatrix} 0 & 0 & 0\\ -0.5 & 0 & 0.5 \\ 0 & 0 &
0 \end{bmatrix} \end{align}
+o v corresponding to a vertical derivative with
coefficients:
\begin{align}
\begin{bmatrix} 0 & -0.5 & 0\\ 0 & 0 & 0 \\ 0 & 0.5 &
0 \end{bmatrix} \end{align}
edge1, edge2, sharpen, u and v are only supported for a
kernel size equal to 3.
gaussian is supported for a kernel size equal to 3 or 5.
unsharp-masking is supported for a kernel size equal to
5.
+o or the values of the coefficients of the kernel as a square
matrix of width and height N, where N is an odd number, as
[[val00, val01, ..., val0N],[val10, val11, ...,
val1N],...,[valN0, valN1, ..., valNN]].
If --method is set to mean, this has the effect of adding
the sum of the (contributing, i.e. non nodata) weighted
source pixels and dividing it by the sum of the coefficients
in the kernel.
If --kernel is specified several times, there will one output
band for each combination of kernel and input band.
--size <SIZE>
Size of the kernel. Odd number between 3 and 99.
NOTE:
Computation time is proportional to the square of the
kernel size.
For kernels edge1, edge2, sharpen, u, v, gaussian, equal,
defaults to 3.
For kernel unsharp-masking, defaults to 5.
For kernels specified through their coefficient values, it is
deduced from the shape of the matrix.
--method sum|mean|min|max|stddev|median|mode
Function to apply to the weighted source pixels in the
neighborhood defined by the kernel. Defaults to mean, except
when --kernel is set to u, v, edge1, edge2, or a user defined
kernel whose sum of coefficients is zero, in which case sum is
used.
+o sum: computes the sum of the value of contributing source
pixels multiplied by the corresponding weight of the kernel.
This corresponds to a kernel with un-normalized sum of
coefficients.
+o mean: computes the average of the value of contributing
source pixels multiplied by the corresponding weight of the
kernel. This has the effect of normalizing kernel
coefficients so their sum is one.
+o min: computes the minimum of the value of contributing
source pixels multiplied by the corresponding weight of the
kernel
+o max: computes the maximum of the value of contributing
source pixels multiplied by the corresponding weight of the
kernel
+o stddev: computes the standard deviation of the value of
contributing source pixels multiplied by the corresponding
weight of the kernel
+o median: computes the median of the value of contributing
source pixels multiplied by the corresponding weight of the
kernel
+o mode (majority): computes the most frequent of the value of
contributing source pixels multiplied by the corresponding
weight of the kernel
--nodata
Set the NoData value for the output dataset. May be set to
none to leave the NoData value undefined. If --nodata is not
specified, gdal raster neighbors will use a NoData value from
the first source dataset to have one.
GDALG OUTPUT (ON-THE-FLY / STREAMED DATASET)
This program supports serializing the command line as a JSON file
using the GDALG output format. The resulting file can then be opened
as a raster dataset using the GDALG: GDAL Streamed Algorithm driver,
and apply the specified pipeline in a on-the-fly / streamed way.
Example 1: Compute the horizontal and vertical derivative of a
single-band raster
gdal raster neighbors --kernel u --kernel v in.tif uv.tif
Example 2: Compute the average value around each pixel in a 3x3
neighborhood
gdal raster neighbors --kernel equal --method mean in.tif mean.tif
Example 3: Compute the maximum value around each pixel in a 5x5
neighborhood
gdal raster neighbors --kernel equal --size 5 --method max in.tif max.tif
Example 4: Compute a sharpen filter of a single-band raster, by manually
specifying the kernel coefficients.
gdal raster neighbors "--kernel=[[0,-1,0],[-1,5,-1],[0,-1,0]]" in.tif sharpen.tif
Even Rouault <even.rouault@spatialys.com>
1998-2026
March 20, 2026 GDAL-RASTER-NEIGHBORS(1)
NAME
gdal-raster-neighbors - Compute the value of each pixel from its
neighbors (focal statistics)
Added in version 3.12.
SYNOPSIS
Usage: gdal raster neighbors [OPTIONS] <INPUT> <OUTPUT>
Compute the value of each pixel from its neighbors (focal statistics)
Positional arguments:
-i, --input <INPUT> Input raster datasets [required]
-o, --output <OUTPUT> Output raster dataset [required]
Common Options:
-h, --help Display help message and exit
--json-usage Display usage as JSON document and exit
--config <KEY>=<VALUE> Configuration option [may be repeated]
-q, --quiet Quiet mode (no progress bar)
Options:
-f, --of, --format, --output-format <OUTPUT-FORMAT> Output format ("GDALG" allowed)
--co, --creation-option <KEY>=<VALUE> Creation option [may be repeated]
--overwrite Whether overwriting existing output is allowed
Mutually exclusive with --append
--append Append as a subdataset to existing output
Mutually exclusive with --overwrite
-b, --band <BAND> Input band (1-based index)
--method <METHOD> Method to combine weighed source pixels. METHOD=mean|sum|min|max|stddev|median|mode [may be repeated]
--size <SIZE> Neighborhood size
--kernel <KERNEL> Convolution kernel(s) to apply [1.. values] [required]
--ot, --datatype, --output-data-type <OUTPUT-DATA-TYPE> Output data type. OUTPUT-DATA-TYPE=Byte|Int8|UInt16|Int16|UInt32|Int32|UInt64|Int64|CInt16|CInt32|Float16|Float32|Float64|CFloat32|CFloat64 (default: Float64)
--nodata <NODATA> Assign a specified nodata value to output bands ('none', numeric value, 'nan', 'inf', '-inf')
Advanced Options:
--if, --input-format <INPUT-FORMAT> Input formats [may be repeated]
--oo, --open-option <KEY>=<VALUE> Open options [may be repeated]
DESCRIPTION
gdal raster neighbors applies a kernel (convolution matrix) and a
method to compute the target pixel value from a neighbourhood of the
source pixel value.
At the top edge, the values of the first row are replicated to
virtually extend the source window by a number of rows equal to the
radius of the kernel. And similarly for the bottom, left and right
edges. This strategy may potentially lead to unexpected results
depending on the applied kernel.
For a given target cell, if the corresponding source value (the one
at the center of the kernel) is nodata, the resulting pixel is
nodata. For other source values in the neighborhood defined by the
kernel, source nodata values are ignored.
This algorithm can be part of a gdal pipeline or gdal raster
pipeline.
OPTIONS
The following options are available:
-f, --of, --format, --output-format <OUTPUT-FORMAT>
Which output raster format to use. Allowed values may be given
by gdal --formats | grep raster | grep rw | sort
--co, --creation-option <NAME>=<VALUE>
Many formats have one or more optional creation options that
can be used to control particulars about the file created. For
instance, the GeoTIFF driver supports creation options to
control compression, and whether the file should be tiled.
May be repeated.
The creation options available vary by format driver, and some
simple formats have no creation options at all. A list of
options supported for a format can be listed with the
--formats command line option but the documentation for the
format is the definitive source of information on driver
creation options. See Raster drivers format specific
documentation for legal creation options for each format.
--overwrite
Allow program to overwrite existing target file or dataset.
Otherwise, by default, gdal errors out if the target file or
dataset already exists.
--band <BAND>
Source band number (indexing starts at one). If it is not
specified, all input bands are used.
--kernel
Convolution kernel to apply to source pixels in a neighborhood
of each pixel.
+o either the name of a well-known kernel, among edge1, edge2,
sharpen, gaussian, or unsharp-masking, corresponding to
those kernels (convolution matrix), with the addition of:
+o equal corresponding to a kernel with all coefficients at
one kernel size can be any odd number between 3 and 99):
\begin{align}
\begin{bmatrix} 1 & 1 & 1\\ 1 & 1 & 1 \\ 1 & 1 & 1
\end{bmatrix} \end{align}
For method mean, this corresponds to a box blur filter.
+o u corresponding to an horizontal derivative with
coefficients:
\begin{align}
\begin{bmatrix} 0 & 0 & 0\\ -0.5 & 0 & 0.5 \\ 0 & 0 &
0 \end{bmatrix} \end{align}
+o v corresponding to a vertical derivative with
coefficients:
\begin{align}
\begin{bmatrix} 0 & -0.5 & 0\\ 0 & 0 & 0 \\ 0 & 0.5 &
0 \end{bmatrix} \end{align}
edge1, edge2, sharpen, u and v are only supported for a
kernel size equal to 3.
gaussian is supported for a kernel size equal to 3 or 5.
unsharp-masking is supported for a kernel size equal to
5.
+o or the values of the coefficients of the kernel as a square
matrix of width and height N, where N is an odd number, as
[[val00, val01, ..., val0N],[val10, val11, ...,
val1N],...,[valN0, valN1, ..., valNN]].
If --method is set to mean, this has the effect of adding
the sum of the (contributing, i.e. non nodata) weighted
source pixels and dividing it by the sum of the coefficients
in the kernel.
If --kernel is specified several times, there will one output
band for each combination of kernel and input band.
--size <SIZE>
Size of the kernel. Odd number between 3 and 99.
NOTE:
Computation time is proportional to the square of the
kernel size.
For kernels edge1, edge2, sharpen, u, v, gaussian, equal,
defaults to 3.
For kernel unsharp-masking, defaults to 5.
For kernels specified through their coefficient values, it is
deduced from the shape of the matrix.
--method sum|mean|min|max|stddev|median|mode
Function to apply to the weighted source pixels in the
neighborhood defined by the kernel. Defaults to mean, except
when --kernel is set to u, v, edge1, edge2, or a user defined
kernel whose sum of coefficients is zero, in which case sum is
used.
+o sum: computes the sum of the value of contributing source
pixels multiplied by the corresponding weight of the kernel.
This corresponds to a kernel with un-normalized sum of
coefficients.
+o mean: computes the average of the value of contributing
source pixels multiplied by the corresponding weight of the
kernel. This has the effect of normalizing kernel
coefficients so their sum is one.
+o min: computes the minimum of the value of contributing
source pixels multiplied by the corresponding weight of the
kernel
+o max: computes the maximum of the value of contributing
source pixels multiplied by the corresponding weight of the
kernel
+o stddev: computes the standard deviation of the value of
contributing source pixels multiplied by the corresponding
weight of the kernel
+o median: computes the median of the value of contributing
source pixels multiplied by the corresponding weight of the
kernel
+o mode (majority): computes the most frequent of the value of
contributing source pixels multiplied by the corresponding
weight of the kernel
--nodata
Set the NoData value for the output dataset. May be set to
none to leave the NoData value undefined. If --nodata is not
specified, gdal raster neighbors will use a NoData value from
the first source dataset to have one.
GDALG OUTPUT (ON-THE-FLY / STREAMED DATASET)
This program supports serializing the command line as a JSON file
using the GDALG output format. The resulting file can then be opened
as a raster dataset using the GDALG: GDAL Streamed Algorithm driver,
and apply the specified pipeline in a on-the-fly / streamed way.
EXAMPLES
Example 1: Compute the horizontal and vertical derivative of a
single-band raster
gdal raster neighbors --kernel u --kernel v in.tif uv.tif
Example 2: Compute the average value around each pixel in a 3x3
neighborhood
gdal raster neighbors --kernel equal --method mean in.tif mean.tif
Example 3: Compute the maximum value around each pixel in a 5x5
neighborhood
gdal raster neighbors --kernel equal --size 5 --method max in.tif max.tif
Example 4: Compute a sharpen filter of a single-band raster, by manually
specifying the kernel coefficients.
gdal raster neighbors "--kernel=[[0,-1,0],[-1,5,-1],[0,-1,0]]" in.tif sharpen.tif
AUTHOR
Even Rouault <even.rouault@spatialys.com>
COPYRIGHT
1998-2026
March 20, 2026 GDAL-RASTER-NEIGHBORS(1)