trusty (1) v.kernel.1grass.gz

NAME

       v.kernel   -  Generates  a  raster density map from vector point data using a moving kernel or optionally
       generates a vector density map on a vector network.

KEYWORDS

       vector, kernel density

SYNOPSIS

       v.kernel
       v.kernel help
       v.kernel [-oqnmv] input=name  [net=name]  output=name stddeviation=float  [dsize=float]    [segmax=float]
       [distmax=float]   [mult=float]   [node=string]   [kernel=string]   [--verbose]  [--quiet]

   Flags:
       -o
           Try to calculate an optimal standard deviation with 'stddeviation' taken as maximum (experimental)

       -q
           Only calculate optimal standard deviation 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.

       -v
           Verbose module output (retained for backwards compatibility)

       --verbose
           Verbose module output

       --quiet
           Quiet module output

   Parameters:
       input=name
           Input vector with training points

       net=name
           Input network vector map

       output=name
           Output raster/vector map

       stddeviation=float
           Standard deviation 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.

       mult=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  mult  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.

       With  the  -o flag (experimental) the command tries to calculate an optimal standard deviation. The value
       of stddeviation is taken as maximum value. Standard deviation is calculated using ALL  points,  not  just
       those in the current region.

LIMITATIONS

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

SEE ALSO

       v.surf.rst

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

AUTHORS

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

       Last changed: $Date: 2011-11-08 03:29:50 -0800 (Tue, 08 Nov 2011) $

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