Hi Giovanni,
could you please check out
svn checkout https://svn.osgeo.org/grass/grass-addons/raster/r.univar2.zonal
and let me know if the results and the speed are ok?
r.univar2.zonal does zonal statistics if I understood the concept all
right. You have to give a zoning map as input. That would be in your
case the rasterized vector areas. The output can be very long, as in
your case, so I added an option to dump the stats in a file, that way
it's easier to scrutinize.
In my tests, the stats were identical to r.univar2 in develbranch_6,
only that I had to run r.univar2.zonal only once and not several times.
This r.univar2.zonal is not polished: 3D support is missing and the
output is not shell style although it should be, no idea why not. I
would like to leave the polishing to the experts.
I haven't added an entry in wiki addons, because I don't know if this is
an unpolished gem or unnecessary with your current solution or a pile of
trash (well, not completely trash, results are at least identical to
r.univar2).
Regards,
Markus M
G. Allegri wrote:
The rasterizing method gives comparable performances to ArcGIS. I
confirm that it does the same.
The bottleneck is the r.univar limitation to CELL. I have to
investigate why, as it is based on r.stats which works with
DCELL/FCELL too
The final join would be an improvement respect to Zonal Statistics in
ArcGIS which simply produce a dbf with OIDs from polygon IDs but
doesn't merge it into the original vectorial.
2009/2/19 Markus Metz <[email protected]>:
Markus Neteler wrote:
On Thu, Feb 19, 2009 at 2:20 PM, G. Allegri <[email protected]> wrote:
Thanks for the ideas.
I've just tried Starspan but it's performance is still too slow. I've
let it run for 15 minutes...
Can you please try GRASS 7?
grass70/scripts/v.rast.stats/v.rast.stats.py
grass70/scripts/v.rast.stats/v.rast.stats.py also uses r.mapcalc in every
pass:
for i in cats:
...
grass.mapcalc("MASK = if(...)
if v.rast.stats is faster in grass7, then probably because of improved
raster libs. A speed increase from >5 hours to 40 seconds is unlikely since
grass.mapcalc is still called 1793 times (assuming each area has a unique
category) for a region with 4415x6632 cells...
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