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NAME

v.nnstat - Indicates clusters, separations or random distribution of point set in 2D or 3D space.

KEYWORDS

vector, nearest neighbour analysis

SYNOPSIS

v.nnstat
v.nnstat --help
v.nnstat [-2] input=name [area=float] [layer=string] [zcolumn=name] [--help] [--verbose] [--quiet] [--ui]

Flags:

-2
Force 2D NNA even if input is 3D
--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
Or data source for direct OGR access
area=float
2D: Area. If not specified, area of Minimum Enclosing Rectangle will be used.
3D: Volume. If not specified, volume of Minimum Enclosing Box will be used.
layer=string
Layer number or name
Vector features can have category values in different layers. This number determines which layer to use. When used with direct OGR access this is the layer name.
Default: 1
zcolumn=name
Column with z coordinate (set for 2D vectors only if 3D NNA is required to be performed)

Table of contents

DESCRIPTION

v.nnstat indicates clusters, separations or random distribution of point dataset in 2D or 3D space using Nearest Neighbour Analysis (NNA). The method is based on comparison of observed average distance between the nearest neighbours and the distance which would be expected if points in the dataset are distributed randomly. More detailed information about theoretical background is provided in (Clark and Evans, 1954), (Chandrasekhar, 1943, p. 86-87). Details about the module and testing are summarized in (Stopkova, 2013).

EXAMPLES

Comparison of 2D and 3D NNA

On the example of dataset that contains 2000 randomly distributed points, basic settings of analysis dimension (2D or 3D) will be examined:

Comparison of various datasets

In (Stopkova, 2013), there might be seen other examples (also clustered and dispersed datasets).

TODO

SEE ALSO

v.hull

REQUIREMENTS

AUTHOR

Eva Stopkova
functions for computation of Minimum Bounding Box volume (Minimum Bounding Rectangle area) are based on functions for computing convex hull from the module v.hull (Aime, A., Neteler, M., Ducke, B., Landa, M.)

SOURCE CODE

Available at: v.nnstat source code (history)

Latest change: Wednesday Jun 05 18:04:57 2024 in commit: b9e19dc7f2b8b77d0a51d86980db6c13baf20570


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