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<h2>NAME</h2>
<em><b>i.oif</b></em> - Calculates Optimum-Index-Factor table for LANDSAT TM bands 1-5, & 7
<h2>KEYWORDS</h2>
raster, imagery, statistics
<h2>SYNOPSIS</h2>
<b>i.oif</b><br>
<b>i.oif help</b><br>
<b>i.oif</b> [-<b>g</b>] <b>image1</b>=<em>string</em> <b>image2</b>=<em>string</em> <b>image3</b>=<em>string</em> <b>image4</b>=<em>string</em> <b>image5</b>=<em>string</em> <b>image7</b>=<em>string</em> [--<b>verbose</b>] [--<b>quiet</b>]
<h3>Flags:</h3>
<DL>
<DT><b>-g</b></DT>
<DD>Print in shell script style</DD>
<DT><b>--verbose</b></DT>
<DD>Verbose module output</DD>
<DT><b>--quiet</b></DT>
<DD>Quiet module output</DD>
</DL>
<h3>Parameters:</h3>
<DL>
<DT><b>image1</b>=<em>string</em></DT>
<DD>LANDSAT TM band 1.</DD>
<DT><b>image2</b>=<em>string</em></DT>
<DD>LANDSAT TM band 2.</DD>
<DT><b>image3</b>=<em>string</em></DT>
<DD>LANDSAT TM band 3.</DD>
<DT><b>image4</b>=<em>string</em></DT>
<DD>LANDSAT TM band 4.</DD>
<DT><b>image5</b>=<em>string</em></DT>
<DD>LANDSAT TM band 5.</DD>
<DT><b>image7</b>=<em>string</em></DT>
<DD>LANDSAT TM band 7.</DD>
</DL>
<h2>DESCRIPTION</h2>
<em>i.oif</em> calculates the Optimum Index Factor for LANDSAT TM bands 1,2,3,4,5 and 7.
<p>
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 <em>i.oif</em> are used as the
three color channels required for <em>d.rgb</em> or <em>r.composite</em>.
<p>
The analysis is saved to a file in the current directory called "i.oif.result".
<h2>NOTES</h2>
Colour Composites in BGR order: important band combinations (example:
234 in BGR order means: B=2, G=3, R=4):
<ul>
<li> 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.
<li> 234: sensitive to green vegetation (portrayed as red), coniferous as
distinctly darker red than deciduous forests. Roads and water bodies are clear.
<li> 243: green vegetation is green but coniferous forests aren't as clear as
the 234 combination.
<li> 247: one of the best for info pertaining to forestry. Good for operation
scale mapping of recent harvest areas and road construction.
<li> 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.
<li> 347: similar to 345 but depicts burned areas better.
<li> 354: appears more like a colour infrared photo.
<li> 374: similar to 354.
<li> 457: shows soil texture classes (clay, loam, sandy).
</ul>
<h2>EXAMPLE</h2>
North Carolina sample dataset:
<div class="code"><pre>
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
</pre></div>
<h2>REFERENCE</h2>
Jensen, 1996. Introductory digital image processing. Prentice Hall, p.98. ISBN 0-13-205840-5
<h2>SEE ALSO</h2>
<em>
<a href="d.rgb.html">d.rgb</a>,
<a href="r.composite.html">r.composite</a>,
<a href="r.covar.html">r.covar</a>,
<a href="r.univar.html">r.univar</a>
</em>
<h2>AUTHOR</h2>
Markus Neteler, ITC-Irst, Trento, Italy<br>
Updated to GRASS 5.7 by Michael Barton, Arizona State University
<p><i>Last changed: $Date: 2011-09-04 06:23:30 -0700 (Sun, 04 Sep 2011) $</i>
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