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 * multiplier

       -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)

       Accessed: Tuesday Jun 27 11:13:50 2023

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       © 2003-2023 GRASS Development Team, GRASS GIS 8.3.0 Reference Manual