GRASS GIS manual: r.pi.graph

NAME

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

KEYWORDS

raster

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] [--verbose] [--quiet]

Flags:

-a: Set for 8 cell-neighbors. 4 cell-neighbors are default
--overwrite: Allow output files to overwrite existing files
--verbose: Verbose module output
--quiet: Quiet module output

Parameters:

input=name: Name of input raster map
output=string: Name of the new raster file
keyval=integer: Key value
distance=float: Bounding distance [0 for maximum distance]
neighborhood=string: Neighborhood definition; Options: nearest_neighbor,relative_neighbor,gabriel,spanning_tree
index=string: 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

Graph Theory for connectivity analysis.

NOTES

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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 cluster.

AUTHORS

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

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