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I see lots of references for Tasseled Cap transformation for Landsat-8 Top of Atmosphere reflectance. Is the Tasseled Cap approach applicable for Landsat 5, 7, and 8 surface reflectance data as well?

Landsat 5, 7, and 8 surface reflectance Tasseled cap transformation

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I have found these Tasseled Cap coefficients for use with Landsat Surface reflectance data. Please refer to the source article for applicability to your work. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0147121 enter image description here

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No. It is not. The parameters for Tasseled Cap transformation are only applicable to top-of-atmosphere data.
Applying the transformation to atmospherically corrected data would not be considered 'correct' / 'intended', but that doesn't mean that it wouldn't work reasonably well. You'd have to try it out and evaluate the results.
As for the multi-sensor part of the question - yes, there are parameters for Landsat 5 & 7 - see Tasseled Cap Transformation coefficient and Bias Value

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  • Thank you for your answer! Actually, I tried and I applied the Tasseled Cap transformation to Landsat 8 surface reflectance. How to evaluate my result?. I used this article as reference tandfonline.com/doi/pdf/10.1080/2150704X.2014.915434
    – Soil 2015
    Dec 6, 2017 at 18:55
  • @Soil2015 - for something like this, you'll likely have to base it on a qualitative assessment, as in, does the 'Greenness' parameter reflect where you see vegetation and similarly for the 'Wetness' parameter.
    – Mikkel Lydholm Rasmussen
    Dec 7, 2017 at 10:26
  • I have used the parameters in land use change detection
    – Soil 2015
    Dec 7, 2017 at 14:07
  • @Soil2015 - then compare the detected changes with each of the input images. Are the identified features actually changes occuring, or not? If you didn't end up with too many incorrect classifications, then it all worked out in the end and using Tasseled Cap on atmospherically corrected data didn't cause any significant problems.
    – Mikkel Lydholm Rasmussen
    Dec 7, 2017 at 17:32

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