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
Graph Theory for connectivity analysis.
...
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.
r.pi.corearea,
r.pi.corr.mw,
r.pi.csr.mw,
r.pi.export,
r.pi.graph.dec,
r.pi.graph.pr,
r.pi.graph.red,
r.pi.grow,
r.pi.import,
r.pi.index,
r.pi.lm,
r.pi.odc,
r.pi.prob.mw,
r.pi.rectangle,
r.pi
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
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© 2003-2024
GRASS Development Team,
GRASS GIS 8.4.1dev Reference Manual