Note: This document is for an older version of GRASS GIS that will be discontinued soon. You should upgrade, and read the current manual page.
NAME
r.pi.import - Import and generation of patch raster data
KEYWORDS
raster
SYNOPSIS
r.pi.import
r.pi.import --help
r.pi.import [-a] input=string raster=name output=name keyval=integer id_col=integer val_col=integer [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=string [required]
- Name of the input ASCII-file
- raster=name [required]
- Name of input raster map
- output=name [required]
- Name for output raster map
- keyval=integer [required]
- Category value of the patches
- id_col=integer [required]
- Number of the column with patch IDs
- val_col=integer [required]
- Number of the column with patch values
- title="phrase"
- Title for resultant raster map
Import and generation of patch raster data based on individual patch
based raster data.
...
An example for the North Carolina sample dataset:
In order to run
r.pi.import we need an exported patch index
raster:
r.pi.index input=landclass96 output=landclass96_forestclass5_area keyval=5 method=area
export this resulting map:
r.pi.export input=landclass96_forestclass5_area output=patch_area_out values=patch_area_values id_raster=forestclass5_ID stats=average,variance,min
modify it with R or just import the file again and assign the
percentage coverage to each fragment. You need the
patch_area_values file and the previously used input file
forestclass96 raster (important: the same patch coverage is
mandatory otherwise patch ID in the text file and raster are not
congruent!):
r.pi.import input=patch_area_values raster=landclass96 output=imported_values keyval=5 id_col=1 val_col=2
if you want to export the patch values to R and do e.g. a linear
regression of two patch values and import them again in GRASS, do:
apply r.pi.export with two indices (A and B), in
R, do:
resid.AB <- resid(lm(A[,3]~B[,3])) #write residuals of a linear regression
df.resid.AB <- data.frame(A[,1],resid.AB) #merge patch IDs and resid into same data frame
write.table(df.resid.AB,"resid.for.GRASS",row.names=F,col.names=F)
exit R and run in GRASS:
r.pi.import input=resid.for.GRASS raster=landclass96 output=resid.AB keyval=5 id_col=1 val_col=2
r.pi.export,
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.import source code
(history)
Latest change: Monday Jun 28 07:54:09 2021 in commit: 1cfc0af029a35a5d6c7dae5ca7204d0eb85dbc55
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© 2003-2023
GRASS Development Team,
GRASS GIS 7.8.9dev Reference Manual