I am still beginner in Remote Sensing.

I have asked a GRASS programmer to prepare for me Landsat reflectance values from raw DN values (1 scene per year from 1987 to 2013). I have proposed him (following litterature and p.ex. Is there a way to automate the preprocessing of LANDSAT data?) to run step by step next tools to obtain reflectance values:

  • i.landsat.toar (addon for GRASS 6, included in GRASS 7) - convert DN to top of atmosphere radiance
  • i.atcorr - correct top of atmosphere to surface reflectance

These surface reflectance values were subsequently corrected by topographic normalisation DOS3 by i.topo.corr because of my mountainous AOI.

How is it possible to establish/check if calculated reflectance values are right?

The reason why I am asking is because if the reflectance values (right) are more appropriate for vegetation study.

Why do the raw Landsat data (left) values sees to be better visually distinctive ?

Is it only a question of appearance?

"False colours of raw (left) and reflectance (right) landsat data"


Your question is two-fold.

With regards to the actual atmospherically corrected data: there is no simple method for testing if the calculated reflectance values are right. However, the simplest approach is to compare the resulting spectras to known spectras from the literature. Which bit of literature you need to find depends on your area / local ecosystem of interest.

The second part of the question is the visual interpretation of the images: it seems likely that the issue is with how you stretch the values in the RGB display. The atmospherically corrected data seems to have some issues in the shadows north of the mountain, which may have influenced the band statistics used in the RGB stretch. You could try to use local statistics to stretching the image from the area just south of the road covering the field and the forest.

A recent development (as of late January 2015): Landsat 8 Surface Reflectance products are now available from USGS, see this link . This product can be used for validation in the overlapping period.

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