#3283: i.landsat.acca - cloud/shadow detection (vs. fmask)
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Reporter: martinl | Owner: grass-dev@…
Type: enhancement | Status: new
Priority: normal | Milestone: 7.4.0
Component: Imagery | Version: unspecified
Keywords: i.landsat.acca | CPU: Unspecified
Platform: Unspecified |
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Recently I was working with Landsat data and performed cloud detection
using G72:i.landsat.acca. It gave me quite reasonable results at least for
clouds (see attachment:landsat_acca.png, yellow color). Much more worst
results gave the module 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?
(1) https://grass.osgeo.org/grass72/manuals/i.landsat.acca.html
(2)
https://trac.osgeo.org/grass/browser/grass/trunk/imagery/i.landsat.acca/algorithm.c#L76
(3)
https://trac.osgeo.org/grass/browser/grass/trunk/imagery/i.landsat.acca/algorithm.c#L465
(4) https://github.com/prs021/fmask/blob/master/README.md
(5) http://pythonfmask.org/en/latest/
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Ticket URL: <https://trac.osgeo.org/grass/ticket/3283>
GRASS GIS <https://grass.osgeo.org>