v.kernel(1)

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: Thursday Jul 25 04:42:07 2024

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