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 :) _______________________________________________ grass-dev mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/grass-dev
