Hello Everyone,
The scaling factors used for Collection 2 and Level 2 Landsat data includes a multiplicative (0.0000275) and an additive (-0.2) term. When these factors are used to convert to non-scaled surface reflectance values for each band, and these data are used in various processing procedures (like the ratio used to compute the NDVI), it has both noise problems (pixels with water or clouds) and the data are smoothed so it appears that the spatial resolution is lowered.
I don't understand why this problem has been around so long and not fixed at this stage. Not sure what the benefit is to spread the range of digital numbers way beyond the original range to create an artificially enhanced dynamic range of numbers. The 'empty spaces' from valid number to valid number is then filled in with a smoothing type of procedure (perhaps the resampling using cubic or bi-linear methods), so when zoomed up the image looks smooth and appears to have lost resolution compared to the original image (get level 1 and level 2 data and compare them). This combined with the 'noise' problem introduced by the 'scaling factor corrections' for pixels with water or clouds is one reason why many users are downloading level 1 data and doing their own corrections instead.
Generating the NDVI with the not scaled corrected data (the data you download) DOES NOT give valid NDVI values. They are in the range of -1 to +1, however, they are not correct; the values will be quite a bit smaller than they should be. If only a multiplicative scaling was used (e.g., 0.0000275) and not an additive also (e.g., -0.2) then the scaling would not matter because they would cancel out in the ratio process; this does not happen when an additive term is included.
I think it is time to re-think the scaling of the data and use a method that does not create problems that were not there to begin with !
Pat Chavez
Northern Arizona University (retired USGS)
Thought I'd do an update to my comments about scaling factors for the Landsat C2L2 data product. It appears that perhaps the problems seen with the NDVI images at pixels with dark reflectance (water and cloud shadows) and bright reflectance (clouds) after applying the scaling corrections to the C2L2 data may be a function of the atmospheric correction. The relationship between the red and nir bands ends up being such that it might be over correcting the red band and / or under correcting the nir band for the dark and bright pixels (water, cloud shadows, clouds). This can happen when a non realistic atmospheric model is applied to the data. I discuss the fact that realistic vs non realistic atmospheric scattering models can affect the haze values selected and impact the results:
Article An improved dark-object subtraction technique for atmospheri...
More food for thought.
Pat