i.oif.html 2.7 KB

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  1. <h2>DESCRIPTION</h2>
  2. <em>i.oif</em> calculates the Optimum Index Factor for
  3. multi-spectral satellite imagery.
  4. <p>
  5. The Optimum Index Factor (OIF) determines the three-band combination
  6. that maximizes the variability (information) in a multi-spectral
  7. scene. The index is a ratio of the total variance (standard
  8. deviation) within and the correlation between all possible band
  9. combinations. The bands that comprise the highest scoring
  10. combination from <em>i.oif</em> are used as the three color channels
  11. required for <em>d.rgb</em> or <em>r.composite</em>.
  12. <p>The analysis is saved to a file in the current directory called "i.oif.result".
  13. <h2>NOTES</h2>
  14. Landsat 1-7 TM:
  15. Colour Composites in BGR order as important Landsat TM band combinations
  16. (example: 234 in BGR order means: B=2, G=3, R=4):
  17. <ul>
  18. <li> 123: near natural ("true") colour; however, because of
  19. correlation of the 3 bands in visible spectrum, this combination
  20. contains not much more info than is contained in single band.</li>
  21. <li> 234: sensitive to green vegetation (portrayed as red),
  22. coniferous as distinctly darker red than deciduous forests. Roads
  23. and water bodies are clear.</li>
  24. <li> 243: green vegetation is green but coniferous forests aren't as
  25. clear as the 234 combination.</li>
  26. <li> 247: one of the best for info pertaining to forestry. Good for
  27. operation scale mapping of recent harvest areas and road
  28. construction.</li>
  29. <li> 345: contains one band from each of the main reflective units
  30. (vis, nir, shortwave infra). Green vegetation is green and the
  31. shortwave band shows vegetational stress and mortality. Roads are
  32. less evident as band 3 is blue.</li>
  33. <li> 347: similar to 345 but depicts burned areas better.</li>
  34. <li> 354: appears more like a colour infrared photo.</li>
  35. <li> 374: similar to 354.</li>
  36. <li> 457: shows soil texture classes (clay, loam, sandy).</li>
  37. </ul>
  38. <p>
  39. By default the module will calculate standard deviations for all bands in
  40. parallel. To run serially use the <b>-s</b> flag. If the <tt>WORKERS</tt>
  41. environment variable is set, the number of concurrent processes will be
  42. limited to that number of jobs.
  43. <h2>EXAMPLE</h2>
  44. North Carolina sample dataset:
  45. <div class="code"><pre>
  46. g.region raster=lsat7_2002_10 -p
  47. i.oif input=lsat7_2002_10,lsat7_2002_20,lsat7_2002_30,lsat7_2002_40,lsat7_2002_50,lsat7_2002_70
  48. </pre></div>
  49. <h2>REFERENCES</h2>
  50. Jensen, 1996. Introductory digital image processing. Prentice Hall,
  51. p.98. ISBN 0-13-205840-5
  52. <h2>SEE ALSO</h2>
  53. <em>
  54. <a href="d.rgb.html">d.rgb</a>,
  55. <a href="r.composite.html">r.composite</a>,
  56. <a href="r.covar.html">r.covar</a>,
  57. <a href="r.univar.html">r.univar</a>
  58. </em>
  59. <h2>AUTHORS</h2>
  60. Markus Neteler, ITC-Irst, Trento, Italy<br>
  61. Updated to GRASS 5.7 by Michael Barton, Arizona State University
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