Hi Milton,
A possible approach could be, for example, to do the following with each
map:
r.stats -1 input=map1 output=cellvaluesmap1
It will create a file containing the cell values for each map. Then you
can read this file into R and average the three highest values. Something
like:
[apologies for taking the liberty to re-sort previous posts]
Milton Cezar Ribeiro:
I have a set of 7 raster maps.
I am able to calculate several stats with these mapas using r.series.
Now I need to calculate the mean of the tree highest values of my 7 maps.
Any idea of how can I do that?
Hi Miltinho
I assume you want the mean of the three highest values for each raster
cell? If so, you can do this using another step with r.series
1) If your 7 maps are a1 .. a7:
mapcalc a1 = 1; r.mapcalc a2 = 2; r.mapcalc a3 = 3; r.mapcalc a4
= 4; r.mapcalc a5 = 5; r.mapcalc a6 = 6;
Sorry, some typo's (but the given code should be ok): set all values
4/7 quantile to null(), not 0, and you want to calculate the average,
not the sum
On Fri 15 Mar 2013 10:05:51 AM CET, Paulo van Breugel wrote:
Hi Miltinho
I assume you want the mean of the three highest values for each
Good day,
Is there a way to decrease the number of frames in second for r.out.mpeg.
For example I want to make 1 raster map be visible 1 second (1 frame per
second..)
Thanks in advance!
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Moritz:
If you can't find data, you can always use estimations such as in:
http://dx.doi.org/10.1364/AO.34.002765
..
The idea was not to do your own estimations, but to use those published
in this article (or others). See table 4 on page 6, where you can find
the following values
On Thursday 14 of March 2013 15:48:02 Shaun Langley wrote:
Thanks Nikos,
I'm going to try the G7 approach. I do need both cell values and neighbor
values, but figured I would just run the computation twice.
If it finally works-out, please re-post here -- maybe we can put it in the
wiki?
Dear all,
Thanks for all replies. I will check it out thoughout the weekend.
Just clarifying something, I need to do the estimations focusing on
each pixels, and not for the full map (I was not that clear before).
Also as my raster maps are very large (~50,000x60,000 pixels) maybe R
(at least on
My suggestion does just that, per pixel calculations. And as it is just
simple GRASS functions, you should have no problem running it (perhaps a
bit of patients depending on your computer).
On Fri, Mar 15, 2013 at 12:13 PM, Milton Cezar Ribeiro
miltinho.astrona...@gmail.com wrote:
Dear all,
All,
I am thinking of moving to grass7. I know that the vector back end has
changed and there is a requirement to rebuild vector topology. Once
this is done can grass6 still read the vectors with little error? I
would like to keep grass 6 around to make sure that, if I need to, I can
use
Hi Milton,
On Friday 15 Mar 2013 08:13:16 Milton Cezar Ribeiro wrote:
Dear all,
Thanks for all replies. I will check it out thoughout the weekend.
Just clarifying something, I need to do the estimations focusing on
each pixels, and not for the full map (I was not that clear before).
In
On Friday 15 of March 2013 09:31:06 Stephen Sefick wrote:
All,
I am thinking of moving to grass7. I know that the vector back end has
changed and there is a requirement to rebuild vector topology.
Better Faster (thanks to all and especially to Markus Metz) :-)
Once this is done can grass6
Markus Neteler wrote:
I got thermal band fixes from Jorge and applied them to GRASS 6.4.svn
I guess this is the fix related to the post entitled
i.landsat.toar fails to convert DNs (bands 61 and 62) to temperature for
Landsat 7 scene
Works in G64 -- tested with an L5 (LT51820362009326MTI00)
On Fri, Mar 15, 2013 at 3:31 PM, Stephen Sefick sas0...@auburn.edu wrote:
All,
I am thinking of moving to grass7. I know that the vector back end has
changed and there is a requirement to rebuild vector topology. Once this is
done can grass6 still read the vectors with little error?
No, you
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