NAME

       i.oif  - Calculates Optimum-Index-Factor table for LANDSAT TM bands 1-5, & 7

KEYWORDS

       raster, imagery, statistics

SYNOPSIS

       i.oif
       i.oif help
       i.oif   [-g]   image1=string   image2=string   image3=string  image4=string  image5=string
       image7=string  [--verbose]  [--quiet]

   Flags:
       -g
           Print in shell script style

       --verbose
           Verbose module output

       --quiet
           Quiet module output

   Parameters:
       image1=string
           LANDSAT TM band 1.

       image2=string
           LANDSAT TM band 2.

       image3=string
           LANDSAT TM band 3.

       image4=string
           LANDSAT TM band 4.

       image5=string
           LANDSAT TM band 5.

       image7=string
           LANDSAT TM band 7.

DESCRIPTION

       i.oif calculates the Optimum Index Factor for LANDSAT TM bands 1,2,3,4,5 and 7.

       The Optimum Index Factor is calculated to determine the band combination which  shows  the
       maximum information when combined into a composite image. The bands comprising 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

       Colour  Composites  in  BGR  order: important band combinations (example: 234 in BGR order
       means: B=2, G=3, R=4):

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

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

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

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

                      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.

                      347: similar to 345 but depicts burned areas better.

                      354: appears more like a colour infrared photo.

                      374: similar to 354.

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

EXAMPLE

       North Carolina sample dataset:
       g.region rast=lsat7_2002_10 -p
       i.oif image1=lsat7_2002_10 image2=lsat7_2002_20 image3=lsat7_2002_30 \
             image4=lsat7_2002_40 image5=lsat7_2002_50 image7=lsat7_2002_70

REFERENCE

       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

AUTHOR

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

       Last changed: $Date: 2011-09-04 06:23:30 -0700 (Sun, 04 Sep 2011) $

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       © 2003-2013 GRASS Development Team