i.landsat.acca - cloud/shadow detection (vs. fmask)
|Reported by:||martinl||Owned by:|
Description (last modified by )
Recently I was working with Landsat data and performed cloud detection
using G72:i.landsat.acca. The module produced quite reasonable results at least for clouds (see attachment:landsat_acca.png, yellow color), but much more worst results for shadows (orange color, see
-s flag (1)), also
-2f flags have been used. Please compare with RGB composition
(attachment:landsat_rgb.png and attachment:landsat_acca_comp.png).
The module uses basically map algebra for cloud detection (2) and for shadows (3). Shadows detection seems to be somehow unfinished (or very simple).
I tested fmask (4) which gives much more better results (attachment:landsat_fmask.png, attachment:landsat_fmask_comp.png). I didn't studied the algorithm, but it seems to me that it's based on object segmentation approach.
Do you think that new better implementation of G72:i.landsat.acca would be topic for GSOC or student project? The fmask algorithm seems to be well-known, I also found Python library (5).
For now I would suggest to disable shadow detection or at least to add big fat warning about results. What do you think?