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I am trying to calculate surface reflectance values from raw Landsat DN data downloaded from GLOVIS. I have imported Landsat data in GRASS 6 with header by i.landsat.import and reprojected the scene into different PCS. Then I can convert DN to at-sensor radiance/reflectance values using i.landsat.toar.

Subsequently, I would like to convert at-sensor values to at-surface values (needed for further i.topo.corr minnaert correction because of the mountainous area). The simple metod is implemented by DOS[1-4] methods in i.landsat.toar. However, there are 4 DOS methods (http://grass.osgeo.org/grass65/manuals/i.landsat.toar.html):

  • DOS1: TAUv = 1.0, TAUz = 1.0 and Esky = 0.0
  • DOS2: TAUv = 1.0, Esky = 0.0, and TAUz = sin(e) for all bands with maximum wave length less than 1. (i.e. bands 4-6 MSS, 1-4 TM, and 1-4 ETM+) other bands TAUz = 1.0
  • DOS3: TAUv = exp[-t/cos(sat_zenith)], TAUz = exp[-t/sin(e)], Esky = rayleigh
  • DOS4: TAUv = exp[-t/cos(sat_zenith)], TAUz = exp[-t/sin(e)], Esky = PI * radiance_dark

Do you have some experiences, which one of DOS methods is the simpliest one and provides the most reliable results in mountainous area? My area of interest is varying from 800-2500 a.s.l. in Central Europe, surface about 1050 km2 (only a fraction of whole Landsat scene).

  • Please add also your ultimate goal to your posting: visualization or classification? Here screenshots of what I got in the southern Alps from Landsat8: courses.neteler.org/landsat-8-captures-trentino-november-2014 (I also performed pansharpening). – markusN Dec 21 '14 at 10:54
  • HI markusN, my ultimate goal is the classification of bark beetle outbreak spots and forest cover identification – maycca Dec 26 '14 at 14:57
  • Hi Maria, which sensor? – BillyWill Dec 28 '14 at 10:31
  • Hi BillyWill, sensors are TM5, and ETM7 (I am working with landsat images from 1980 to 2014) – maycca Dec 28 '14 at 20:19
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I have found Dos3 to be more relistic for Landsat 5 on the plains for green crops. No experience in other situations.

Landsat 8 will respond differently to the various correction methods, compared to L5.

I haven't used GRASS in a while, have migrated to the plugin for QGIS - see http://fromgistors.blogspot.com/

  • Thank you BillyWill, I have found the same in this article: Song, C., Woodcock, C. E., Seto, K. C., Lenney, M. P., & Macomber, S. A. (2000). Classification and Change Detection Using Landsat TM Data : When and How to Correct Atmospheric Effects ?, 4257(00) so I will try this one and hope that is what I am looking for :) – maycca Dec 26 '14 at 14:55

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