.TH v.kernel 1grass "" "GRASS 7.8.5" "GRASS GIS User's Manual"
.SH NAME
\fI\fBv.kernel\fR\fR  \- Generates a raster density map from vector points map.
.br
Density is computed using a moving kernel. Optionally generates a vector density map on a vector network.
.SH KEYWORDS
vector, kernel density, point density, heatmap, hotspot
.SH SYNOPSIS
\fBv.kernel\fR
.br
\fBv.kernel \-\-help\fR
.br
\fBv.kernel\fR [\-\fBoqnm\fR] \fBinput\fR=\fIname\fR  [\fBnet\fR=\fIname\fR]   [\fBoutput\fR=\fIname\fR]   [\fBnet_output\fR=\fIname\fR]  \fBradius\fR=\fIfloat\fR  [\fBdsize\fR=\fIfloat\fR]   [\fBsegmax\fR=\fIfloat\fR]   [\fBdistmax\fR=\fIfloat\fR]   [\fBmultiplier\fR=\fIfloat\fR]   [\fBnode\fR=\fIstring\fR]   [\fBkernel\fR=\fIstring\fR]   [\-\-\fBoverwrite\fR]  [\-\-\fBhelp\fR]  [\-\-\fBverbose\fR]  [\-\-\fBquiet\fR]  [\-\-\fBui\fR]
.SS Flags:
.IP "\fB\-o\fR" 4m
.br
Try to calculate an optimal radius with given \(cqradius\(cq taken as maximum (experimental)
.IP "\fB\-q\fR" 4m
.br
Only calculate optimal radius and exit (no map is written)
.IP "\fB\-n\fR" 4m
.br
In network mode, normalize values by sum of density multiplied by length of each segment. Integral over the output map then gives 1.0 * multiplier
.IP "\fB\-m\fR" 4m
.br
In network mode, multiply the result by number of input points
.IP "\fB\-\-overwrite\fR" 4m
.br
Allow output files to overwrite existing files
.IP "\fB\-\-help\fR" 4m
.br
Print usage summary
.IP "\fB\-\-verbose\fR" 4m
.br
Verbose module output
.IP "\fB\-\-quiet\fR" 4m
.br
Quiet module output
.IP "\fB\-\-ui\fR" 4m
.br
Force launching GUI dialog
.SS Parameters:
.IP "\fBinput\fR=\fIname\fR \fB[required]\fR" 4m
.br
Name of input vector map with training points
.IP "\fBnet\fR=\fIname\fR" 4m
.br
Name of input network vector map
.IP "\fBoutput\fR=\fIname\fR" 4m
.br
Name for output raster map
.IP "\fBnet_output\fR=\fIname\fR" 4m
.br
Name for output vector density map
.br
Outputs vector map if network map is given
.IP "\fBradius\fR=\fIfloat\fR \fB[required]\fR" 4m
.br
Kernel radius in map units
.IP "\fBdsize\fR=\fIfloat\fR" 4m
.br
Discretization error in map units
.br
Default: \fI0.\fR
.IP "\fBsegmax\fR=\fIfloat\fR" 4m
.br
Maximum length of segment on network
.br
Default: \fI100.\fR
.IP "\fBdistmax\fR=\fIfloat\fR" 4m
.br
Maximum distance from point to network
.br
Default: \fI100.\fR
.IP "\fBmultiplier\fR=\fIfloat\fR" 4m
.br
Multiply the density result by this number
.br
Default: \fI1.\fR
.IP "\fBnode\fR=\fIstring\fR" 4m
.br
Node method
.br
Options: \fInone, split\fR
.br
Default: \fInone\fR
.br
\fBnone\fR: No method applied at nodes with more than 2 arcs
.br
\fBsplit\fR: Equal split (Okabe 2009) applied at nodes
.IP "\fBkernel\fR=\fIstring\fR" 4m
.br
Kernel function
.br
Options: \fIuniform, triangular, epanechnikov, quartic, triweight, gaussian, cosine\fR
.br
Default: \fIgaussian\fR
.SH DESCRIPTION
\fIv.kernel\fR generates a raster density map from vector points
data using a moving
kernel. Available kernel
density functions are \fIuniform, triangular, epanechnikov,
quartic, triweight, gaussian, cosine\fR, default
is \fIgaussian\fR.
.PP
The module can also generate a vector density map on a vector network.
Conventional kernel functions produce biased estimates by overestimating
the densities around network nodes, whereas the equal split method of
Okabe et al. (2009) produces unbiased density estimates. The equal split
method uses the kernel function selected with the \fBkernel\fR option
and can be enabled with \fBnode=split\fR.
.SH NOTES
The \fBmultiplier\fR option is needed to overcome the limitation that
the resulting density in case of a vector map output is stored as category
(integer). The density result stored as category may be multiplied by this number.
.PP
For the \fIgaussian\fR kernel, standard deviation for the
gaussian function
is set to 1/4 of the radius.
.PP
With the \fB\-o\fR flag (experimental) the command tries to calculate an
optimal radius. The value of \fIradius\fR is taken
as maximum value. The radius is calculated based on the gaussian function,
using ALL points, not just those in the current region.
.SH EXAMPLES
Compute density of points (using vector map of schools from North Carolina sample dataset):
.br
.nf
\fC
g.region region=wake_30m
v.kernel input=schools_wake output=schools_density radius=5000 multiplier=1000000
r.colors map=schools_density color=bcyr
\fR
.fi
.br
School density
.SH KNOWN ISSUES
The module only considers the presence of points, but not
(yet) any attribute values.
.SH REFERENCES
.RS 4n
.IP \(bu 4n
Okabe, A., Satoh, T., Sugihara, K. (2009). \fIA kernel density estimation
method for networks, its computational method and a GIS\-based tool\fR.
\fBInternational Journal of Geographical Information Science\fR, Vol 23(1),
pp. 7\-32.
.br
DOI: 10.1080/13658810802475491
.RE
.SH SEE ALSO
\fIv.surf.rst\fR
.PP
Overview: Interpolation and Resampling in GRASS GIS
.SH AUTHORS
Stefano Menegon, ITC\-irst, Trento, Italy
.br
Radim Blazek (additional kernel density functions and network part)
.SH SOURCE CODE
.PP
Available at: v.kernel source code (history)
.PP
Main index |
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Keywords index |
Graphical index |
Full index
.PP
© 2003\-2020
GRASS Development Team,
GRASS GIS 7.8.5 Reference Manual