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i.oif
Langue: en
Version: 370788 (fedora - 01/12/10)
Section: 1 (Commandes utilisateur)
NAME
i.oif - Calculates Optimum-Index-Factor table for LANDSAT TM bands 1-5, & 7KEYWORDS
raster, imagery, statisticsSYNOPSIS
i.oifi.oif help
i.oif image1=string image2=string image3=string image4=string image5=string image7=string [--verbose] [--quiet]
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 Composits 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 in 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).
REFERENCES
Jensen, 1996. Introductory digital image processing, p.98. ISBN 0-13-205840-5SEE ALSO
d.rgbr.composite
r.covar
r.univar
AUTHOR
Markus Neteler, ITC-Irst, Trento, ItalyUpdated to GRASS 5.7 by Michael Barton, Arizona State University
Last changed: $Date: 2007-11-13 12:09:02 +0100 (Tue, 13 Nov 2007) $
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