[GRASS-user] Estimating Albedo from Landsat

[Nikos Alexandris]

[ back again... :-) ]

Nikos wrote:

> > > Downloaded:
> > > - extra: LT50160351988258XXX03 (includes visible clouds - maybe good for 
testing?)

Hamish:

> in the GloVis preview I only see a few clouds in the NE corner
> for that date. (Sept 14, 1988)

Right. I specifically selected a scene with a few visible clouds. Isn't this a 
"good" quality test for the module (instead of using an "easy" scene full with 
clouds)?


> Maybe 1991/10/25 is another good scene for a cloud test? (looks
> like 20% high cumulus with shadows)

Yep, why not. Will order.
 

> Note the % cloud cover in the GloVis previewer is (AFAIU) using
> the same ACCA algorithm as i.landsat.acca, so the result should
> be similar. (??)

hmmm... have to check.


> For the Sept 14, 1998 example the GloVis info says 0% cloud
> cover, but maybe that data is old and the latest ACCA says
> something else?

> > # rgb colors for 742
> > i.landsat.rgb r=lsat5_1988.2 g=lsat5_1988.4 b=lsat5_1988.7
> > strength=96
> > d.rgb r=lsat5_1988.2 g=lsat5_1988.4 b=lsat5_1988.7 #
> > obvious clouds

> maybe i.landsat.dehaze is worth trying before i.landsat.rgb?
 
> > # toar
> > i.landsat.toar band_prefix=lsat5_1988 method=uncorrected \
> > 
> >   sensor=5 product_date=1988-09-14 date=1988-09-14 \
> >   solar_elevation=48.6773844
> 
> do not assume production date is the same as acq. date; check
> metadata values against values in the source code.
> For the Mar 31, 2000 sample data it made a difference.

ok!

 
> > # acca
> > i.landsat.acca -5f2 band_prefix=lsat5_1988.toar \
> >     output=lsat5_1988.toar.acca

> > # how many cats?
> > r.info lsat5_1988.toar.acca -r
> > min=6
> > max=9
 
> see r.category, r.stats -c, or d.legend for meaning of category
> numbers. (6=cold cloud, 9=warm cloud, 2=shadow)

> i.landsat.acca is in flux today, best to wait a few days ..
> (some earlier improvements just got clobbered and new ones
> introduced, so I'm unsure of where we are now)

> > In the "acca" result:
> > 
> > - clouds are detected (cat=6), not that bad(ly) I suppose.
> > Some filtering could push away the (rest of the) "noise".
> 
> the cloud despeckle filter can remove some lone non-cloud cells
> which are surrounded by cloud. after that I guess it's
> r.neighbors or r.mfilter.

--%<-----
> > - obvious mis-detections (commission errors) found within
> > 
> >   - n=188310 s=168270 w=618870 e=636150 (bare ground?
> > 
> > urban area? not sure
> > about the confusing land cover/class here...)
> > 
> >   - n=219030 s=180510 w=646410 e=655740 (road)
> 
> ? maybe google maps satellite view helps if the landsat is too
> coarse to ID features.
> 
> >   - in the borders due to the non-identical extent of all bands (!?)
> 
> I've seen something similar, maybe r.series to accumulate NULLs
> in all input bands and use that as a MASK?
> 
> > - categories 7 and 8 seem to be empty, category 9 looks
> > very messy
> 
> cat 7,8 are undefined, cat 9 probably has more false positives
> in warm land, cat 6 (cold cloud) probably has more problems in
> snowy areas.

> > Could it be that non-cloudy acquisitions are mistreated by
> > the algorithm?
> 
> The paper by Irish listed in the i.landsat.acca man page is
> worth reading, it explains a lot and points out where the
> algorithm does not do well.
> 
> > I can't clearly recognise clouds in the landsat
> > scenes included in NC data set
> > (both the 1987 and the 2000 scenes).
> 
> I'd guess that they were specifically chosen to avoid days with
> obscuring clouds.
> 
> > Will (then) the algorithm work (only) with (very) cloudy
> > data?
> 
> One thing the paper mentions, and I've observed, is that it does
> not do well with thin wispy cirrus clouds. Apparently MODIS does
> a bit better there because it has a detector in the needed 2um
> range to pick those up, while the Landsat only has 11um which
> misses those cloud tops. (IIRC)
--%<-----

Will check the above at some point.


> fyi, I've just added what we know about the NC 2008 dataset
> Landsat images to the grass wiki:
>  http://grass.osgeo.org/wiki/LANDSAT#Sample_data

Thanks, Nikos

 
> I'm downloading them now.. I expect they'll be reprocessed
> versus the metadata calibration values shipped with the dataset.
> (??)
> Hamish