Nick Jachowski:
I have been working a lot with SLC-Off imagery lately. Some people in my
department have used the gap filling programs floating around the net, but
I'm not familiar with them personally. I've settled on using r.patch as
well, although you have to be careful how you apply it. I found that even
if I used radiometrically corrected landsat images (using i.landsat.toar)
from the same season often the patched parts of the image did not fit
smoothly with the rest of the image (i.e. you could see striations where
the gaps had been).
Right. The same here. But I used the composites only for visual interpretation
which was ok. It's always interesting how different tasks pose different
challenges.
I'm using the imagery for land classification, so
I've found it works better if I do the classification on each landsat
image separately and then patch them. Using this method you can't tell
where the former gaps are, at least in my experience working with imagery
from the dry season in southeast asia.
Interesting. Yet, I guess, you had to use independent training areas (in case
you performed supervised classifications), right?
[...]
Nikos A