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.)

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