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i.oif(1)		    GRASS GIS User's Manual		      i.oif(1)

NAME
       i.oif  -	Calculates Optimum-Index-Factor	table for spectral bands

KEYWORDS
       imagery,	multispectral, statistics

SYNOPSIS
       i.oif
       i.oif --help
       i.oif   [-gs]   input=name[,name,...]	[output=name]	 [--overwrite]
       [--help]	 [--verbose]  [--quiet]	 [--ui]

   Flags:
       -g
	   Print in shell script style

       -s
	   Process bands serially (default: run	in parallel)

       --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[,name,...]A [required]
	   Name	of input raster	map(s)

       output=name
	   Name	for output file	(if omitted or "-" output to stdout)

DESCRIPTION
       i.oif calculates	the Optimum Index Factor for multi-spectral  satellite
       imagery.

       The  Optimum  Index  Factor (OIF) determines the	three-band combination
       that maximizes the variability (information) in a multi-spectral	scene.
       The  index is a ratio of	the total variance (standard deviation)	within
       and the correlation between all possible	band combinations.  The	 bands
       that  comprise  the  highest scoring combination	from i.oif are used as
       the three color channels	required for d.rgb or r.composite.

       The analysis is saved  to  a  file  in  the  current  directory	called
       "i.oif.result".

NOTES
       Landsat	1-7 TM:	Colour Composites in BGR order as important Landsat TM
       band combinations (example: 234 in BGR order means: B=2,	G=3, R=4):

	   o   123: near natural ("true") colour; however, because of correla-
	       tion  of	the 3 bands in visible spectrum, this combination con-
	       tains not much more info	than is	contained in single band.

	   o   234: sensitive to green vegetation (portrayed as	red), conifer-
	       ous  as distinctly darker red than deciduous forests. Roads and
	       water bodies are	clear.

	   o   243: green vegetation is	green but coniferous forests aren't as
	       clear as	the 234	combination.

	   o   247:  one of the	best for info pertaining to forestry. Good for
	       operation scale mapping of recent harvest areas and  road  con-
	       struction.

	   o   345:  contains  one band	from each of the main reflective units
	       (vis, nir, shortwave infra). Green vegetation is	green and  the
	       shortwave  band	shows vegetational stress and mortality. Roads
	       are less	evident	as band	3 is blue.

	   o   347: similar to 345 but depicts burned areas better.

	   o   354: appears more like a	colour infrared	photo.

	   o   374: similar to 354.

	   o   457: shows soil texture classes (clay, loam, sandy).

       By default the module will calculate standard deviations	for all	 bands
       in  parallel.  To run serially use the -s flag. If the WORKERS environ-
       ment variable is	set, the number	of concurrent processes	will  be  lim-
       ited to that number of jobs.

EXAMPLE
       North Carolina sample dataset:
       g.region	raster=lsat7_2002_10 -p
       i.oif input=lsat7_2002_10,lsat7_2002_20,lsat7_2002_30,lsat7_2002_40,lsat7_2002_50,lsat7_2002_70

REFERENCES
       Jensen,	1996.  Introductory  digital  image processing.	Prentice Hall,
       p.98. ISBN 0-13-205840-5

SEE ALSO
	d.rgb, r.composite, r.covar, r.univar

AUTHORS
       Markus Neteler, ITC-Irst, Trento, Italy
       Updated to GRASS	5.7 by Michael Barton, Arizona State University

SOURCE CODE
       Available at: i.oif source code (history)

       Main index | Imagery index | Topics index | Keywords index |  Graphical
       index | Full index

       A(C) 2003-2020 GRASS Development	Team, GRASS GIS	7.8.3 Reference	Manual

GRASS 7.8.3							      i.oif(1)

NAME | KEYWORDS | SYNOPSIS | DESCRIPTION | NOTES | EXAMPLE | REFERENCES | SEE ALSO | AUTHORS | SOURCE CODE

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