[GRASS-dev] Landsat 5TM pre-processing - histogram matching - problem

[joanna mardas]

Thanks Nikos!

> > I'm not sure that for Landsat 5 the loss is so important, but you can
> > visually compare an image recoded to 0-255 with the one coming out of
> > i.landsat.toar...
> 
> Nor am I sure about it.  Landsat5 is 8-bit.  But one should definitively 
> consider it, and mention the
> decisions taken while documenting the process.
> 
I did both, r.recode to 0-255 and r.mapcalc int(oldmap*100000). Both output images and also histograms look ok I think. The histograms have the same shapes and visually images are the same, maybe just slight differences but it's impossible to notice. 

> There is a paper, also, suggested by Moritz quite some time ago:
> <http://www.opticsinfobase.org/ao/abstract.cfm?uri=ao-34-15-2765>. In
> it, there is "Table 4. Rayleigh Optical Depths at 0-km Altitude for Six
> Different Atmosphere Models". Perhaps useful.

I'll definitelly look at this.

> joanna, once again, the easy "other way" is posted in my first reply, I
> think.  You just need to multiply with 1000, perform the histogram
> matching, then divide by 1000.0 to get back to floats.

I'll do DOS3, cuz I have to read more about aerosol depth etc. So for now, I think that DOS will be better. And I'll do the histogram matching. I've tried to do this once (after r.recode) but I think (well I'm sure) that I did this in a wrong way cuz I've matched all bands from both 1984 and 2007. It looked really bad haha :D I guess I should match band to band, for example landsat07B2 to landsat84B2, landsat07B3 to landsat84B3 etc.  
 
> 
> As we all know, if one tries to compare scenes over the same area, 
> aqcuired at different
> times, it's necessary to relatively normalise'em (different dates,
> different solar geometries, variations in the spectral response of the
> same surfaces).  The same, I think, is valid if one combines multiple
> scenes acquired at the same date but cover adjacent areas.
> A relative normalisation can help, in such cases, a lot to make 
> classification
> results comparable.  For the latter, perhaps it is not necessary in flat
> areas!?

 I agree, that it should be done. Well my area is flat almost like a table, there are just "tells" (artificial settlement hills, ancient).

> Of course, if the approach is going to be one, independent,
> classification per scene, and then try to compare the outcomes, things
> are very different.  It might work well without undergoing relative
> normalisation actions.

That is what I was going to do, an independent classification per scene. I have only two so it's not a big problem.

> Histogram matching could be used as a mean for relative atmospheric 
> correction.

That is interesting.
 
> Also, there is an effort to do something more sophisticated in this 
> direction
> by Tomas Brunclik:
> <http://www.researchgate.net/publication/275020325_i.grid.correl.atcor_version_0.91b>.
> 
> I haven't checked what's the latest status of it, nor had I any contact
> with the author recently (we did discuss something in the past).
> 
> I am very interested in his work as I have
> performed similar computations in the past using messy scripts in GRASS
> combined with some linear regressions in R.  Maybe his tool is more
> mature now?

Next time maybe, now I'm too green for this :)  R... I've heard about this and that's the end of my knowledge about R (sorry, I'm just an archaeologist).
Joanna :)