NAME

       v.kernel  - Generates a raster density map from vector points map.
       Density is computed using a moving kernel. Optionally generates a vector density map on a vector network.

KEYWORDS

       vector, kernel density, point density, heatmap, hotspot

SYNOPSIS

       v.kernel
       v.kernel --help
       v.kernel  [-oqnm] input=name  [net=name]   [output=name]   [net_output=name]  radius=float  [dsize=float]
       [segmax=float]   [distmax=float]   [multiplier=float]   [node=string]    [kernel=string]    [--overwrite]
       [--help]  [--verbose]  [--quiet]  [--ui]

   Flags:
       -o
           Try to calculate an optimal radius with given ’radius’ taken as maximum (experimental)

       -q
           Only calculate optimal radius and exit (no map is written)

       -n
           In  network  mode,  normalize values by sum of density multiplied by length of each segment. Integral
           over the output map then gives 1.0 * mult

       -m
           In network mode, multiply the result by number of input points

       --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 vector map with training points

       net=name
           Name of input network vector map

       output=name
           Name for output raster map

       net_output=name
           Name for output vector density map
           Outputs vector map if network map is given

       radius=float [required]
           Kernel radius in map units

       dsize=float
           Discretization error in map units
           Default: 0.

       segmax=float
           Maximum length of segment on network
           Default: 100.

       distmax=float
           Maximum distance from point to network
           Default: 100.

       multiplier=float
           Multiply the density result by this number
           Default: 1.

       node=string
           Node method
           Options: none, split
           Default: none
           none: No method applied at nodes with more than 2 arcs
           split: Equal split (Okabe 2009) applied at nodes

       kernel=string
           Kernel function
           Options: uniform, triangular, epanechnikov, quartic, triweight, gaussian, cosine
           Default: gaussian

DESCRIPTION

       v.kernel generates a raster density map from vector points data using a moving kernel.  Available  kernel
       density functions are uniform, triangular, epanechnikov, quartic, triweight, gaussian, cosine, default is
       gaussian.

       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 kernel option and can be enabled with node=split.

NOTES

       The multiplier 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.

       For the gaussian kernel, standard deviation for the gaussian function is set to 1/4 of the radius.

       With  the -o flag (experimental) the command tries to calculate an optimal radius. The value of radius is
       taken as maximum value. The radius is calculated based on the gaussian function, using  ALL  points,  not
       just those in the current region.

EXAMPLES

       Compute density of points (using vector map of schools from North Carolina sample dataset):
       g.region region=wake_30m
       v.kernel input=schools_wake output=schools_density radius=5000 multiplier=1000000
       r.colors map=schools_density color=bcyr
       School density

KNOWN ISSUES

       The module only considers the presence of points, but not (yet) any attribute values.

REFERENCES

           •   Okabe,  A.,  Satoh, T., Sugihara, K. (2009). A kernel density estimation method for networks, its
               computational method and a GIS-based tool.  International  Journal  of  Geographical  Information
               Science, Vol 23(1), pp. 7-32.
               DOI: 10.1080/13658810802475491

SEE ALSO

       v.surf.rst

       Overview: Interpolation and Resampling in GRASS GIS

AUTHORS

       Stefano Menegon, ITC-irst, Trento, Italy
       Radim Blazek (additional kernel density functions and network part)

SOURCE CODE

       Available at: v.kernel source code (history)

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       © 2003-2019 GRASS Development Team, GRASS GIS 7.8.2 Reference Manual