r.pi.graph - GRASS GIS manual

Note: This document is for an older version of GRASS GIS that has been discontinued. You should upgrade, and read the current manual page.

NAME

r.pi.graph - Graph Theory for connectivity analysis.

KEYWORDS

raster, landscape structure analysis, connectivity analysis

SYNOPSIS

r.pi.graph

r.pi.graph --help

r.pi.graph [-a] input=name output=string keyval=integer distance=float neighborhood=string index=string [--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=string [required]: Name of the new raster file
keyval=integer [required]: Key value
distance=float [required]: Bounding distance [0 for maximum distance]
neighborhood=string [required]: Neighborhood definition; Options: nearest_neighbor, relative_neighbor, gabriel, spanning_tree
index=string [required]: Cluster index; Options: connectance_index, gyration_radius, cohesion_index, percent_patches, percent_area, number_patches, number_links, mean_patch_size, largest_patch_size, largest_patch_diameter, graph_diameter

DESCRIPTION
NOTES
EXAMPLE
SEE ALSO
AUTHORS

DESCRIPTION

Graph Theory for connectivity analysis.

NOTES

...

EXAMPLE

An example for the North Carolina sample dataset using class 5 (forest): Computing a graph of all patches (4 neighbourhood rule) using a maximum distance of 10 pixel, the Gabriel method and as resulting index the largest patch diameter:

r.pi.graph input=landclass96 output=landclass96_graph keyval=5 distance=10 neighborhood=gabriel index=largest_patch_diameter

the results are 2 files:
landclass96_graph: the information of the index are provided (here a range of 3-589 of patch diameter)
landclass96_graph_clusters: the generated cluster IDs are provided (here 16 clusters are identified), doing it with a distance of 5 pixel is resulting in a total of 66 clusters.

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.graph source code (history)

Latest change: Tuesday Sep 19 09:59:22 2023 in commit: e76c325998c8cd9053ce012a5adbb79f33ab0779