Advanced users, may I seek for some recommendation on filtering Landsat reflectance outliers?
I have many Landsat scenes pre-processed (DN to Radiance/Reflectance, Cloud- masked, Topo-Corrected, band-wise patched in large maps over Greece) and ready for further explorations. Applying "color=grey -e OR color=grey1.0 -e" doesn't work well for all larger maps (after patching -- call it mosaicking if you prefer). That is, some maps appear too dark (i.e. band 3). I guess that this may be due to abnormally (?) high reflectance values. I guess those are artefacts, or not? The univariate stats of 1+6 bands look fine to me, e.g.: mean: 298.591 mean of absolute values: 298.591 ### this is Temperature in K mean: 0.0453416 mean of absolute values: 0.0453416 mean: 0.0490654 mean of absolute values: 0.0490654 mean: 0.0785879 mean of absolute values: 0.0785879 mean: 0.139015 mean of absolute values: 0.139015 mean: 0.121867 mean of absolute values: 0.121867 mean: 0.0845493 mean of absolute values: 0.0845493 Yet, the max Top-of-Canopy Reflectances: maximum: 326.271 # This is Temperature in K maximum: 172.05 maximum: 117.96 maximum: 775.934 maximum: 1.66005 maximum: 120.506 maximum: 477.744 Is my understanding correct? Is there a safe criterion to filter high reflectance values? Could they be attributed to other sources, e.g. fires? Can I use some different color rules/scheme which will "ignore" too high reflectances? Simply "color=grey1.0" or other based on stddev, quantiles? Thank you in advance for your invaluable time, Nikos
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