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NAME

r.pi.enn - Analysis of n-th Euclidean Nearest Neighbor distance.

KEYWORDS

raster

SYNOPSIS

r.pi.enn
r.pi.enn --help
r.pi.enn [-a] input=name output=name keyval=integer method=string[,string,...] number=num[-num][,num[-num],...] statmethod=string [dmout=string] [adj_matrix=string] [title="phrase"] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

-a
Set for 8 cell-neighbors. 4 cell-neighbors are default
--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 raster map
output=name [required]
Name for output raster map
keyval=integer [required]
Key value
method=string[,string,...] [required]
Operation to perform on fragments
Options: distance, path_distance, area, perimeter, shapeindex
number=num[-num][,num[-num],...] [required]
Number of nearest neighbors to analyse
statmethod=string [required]
Statistical method to perform on the values
Options: average, variance, standard deviation, value, sum
dmout=string
Output name for distance matrix and id-map (performed if not empty)
adj_matrix=string
Output name for adjacency matrix (performed if not empty)
title="phrase"
Title for resultant raster map

Table of contents

DESCRIPTION

r.pi.enn computes the euclidean distance between patches (1-n NN). Analysis of n-th euclidean nearest neighbour distance.

NOTES

The user must specify the names of the raster map layers to be used for input and output, the keyval the method (e.g. distance, area) and statmethod used (i.e., average).

Within r.pi.enn the following setting have to be set:

keyval setting:

The keyval operator determines which category value is taken for the Patch Index analysis.

Method setting:

The method operators determine what measure is applied on the nth NN.

Distance
The Average computes the average distance of the n NN.
Path distance
The path_distance computes the actual distance to the n NN.
Area
The area computes the area of the n NN.
Perimeter
The perimeter computes the perimeter of the n NN.
SHAPE Index
The shapeindex computes the SHAPE Index of the n NN.

Statmethod setting:

The statmethod operators determine what statistic measure is applied on the nth NN.

Average
The Average computes the average distance of the n NN.
Variance
The Variance computes the variance of the distance of the n NN.
Std. Dev.
The Std. Dev computes the std. dev. of the distance of the n NN.

Number:

The keyval operator determines which or how many Nearest Neighbour are analysed. 1,2,5 will analyse the 1, 2 and 5th Nearest Neigbour. 1-10 will analyse the 1, 2, 3, ... 10th Nearest Neighbour. 0 will analyse all Nearest Neighbours.

Distancematrix:

The dmout operator is optional and determines if a distance matrix is written (first NN only). 1,2,5 will analyse the 1, 2 and 5th Nearest Neigbour. 1-10 will analyse the 1, 2, 3, ... 10th Nearest Neighbour. 0 will analyse all Nearest Neighbours.

EXAMPLE

An example for the North Carolina sample dataset:
r.pi.enn input=landclass96 output=dist1.c5 keyval=5 method=distance number=1 statmethod=average 
# -> gives a map of patches (all of category of 5) with the average distance to their first NN

r.pi.enn input=landclass96 output=dist10.c5 keyval=5 method=distance number=10 statmethod=average 
# -> gives a map of patches (all of category of 5) with the average distance to their first-10th NN

r.pi.enn input=landclass96 output=dist1.5.10.c5 keyval=5 method=distance number=1,5,10 statmethod=average 
# -> gives a map of patches (all of category of 5) with the average distance to their first, first-to-fifth and first-to-10th NN

r.pi.enn input=landclass96 output=dist10b.c5 keyval=5 method=path_distance number=10 statmethod=average 
# -> gives a map of patches (all of category of 5) with the actual distance to the 10th NN

SEE ALSO

r.pi.index, r.fragment.dist, r.pi.enn, r.pi.enn.pr, r.fragment.neighbors, r.li

AUTHORS

Programming: Elshad Shirinov
Scientific concept: Dr. Martin Wegmann
Department of Remote Sensing
Remote Sensing and Biodiversity Unit
University of Wuerzburg, Germany

Port to GRASS GIS 7: Markus Metz

SOURCE CODE

Available at: r.pi.enn source code (history)


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© 2003-2020 GRASS Development Team, GRASS GIS 7.8.4dev Reference Manual