On 2012/08/24 21:29, Micha Silver wrote:
Hello Sam:
On 24/08/2012 14:14, Samantha Goodchild-Brown wrote:
Mischa
I am working on those commands but In Linux side I have got the
training map to raster format with all visible.
More issues I overcame (for students benefit) is:
I imported a shape file made in Qgis with the RGB column and label
column. To get this to work I had to select 'command dialog' button
in 'import vector data' box and not just use' ivd' box gui.
In the' import vector data' gui I ticked 'override dataset projection
(use locations projection)' and 'limit import to the currect region'
and made no other changes in the
That's unusual that you had to specify "override dataset projection".
Are you sure that the original is projected in the same coordinate
system as the GRASS LOCATION??
Yes I am sure. However the Raster is a new geotiff and the shape file is
old style. Evidently Grass doesn't recognise them as the same. When you
read the metadata in QGIS you can understand why but it is still quite
frustrating.
command dialog box except to repeat input and output dataset names!
Now v.to rast works but it doesn't allow out to specify the attribute
columns - looks greyed out, so you just type them as you know them,
it works!
In windows grass I imported the same shp file, in the same way,
successfully. (this using grass not grass plugin in QGIS) In the
v.to.rast I can specify / select the attribute columns but when I
'run' it, I get the following:
(Fri Aug 24 12:46:44 2012)
v.to.rast input=qgis_lclu_trainingmap2@3420new
output=trainingmap_raster column=cat_ rgbcolumn=RGB labelcolumn=label
Loading data...
Reading areas...
Reading features...
Writing raster map...
Converted areas: 6 of 6
Converted points/lines: 0 of 0
v.to.rast complete.
(Fri Aug 24 12:46:45 2012) Command finished (0 sec)
Which one would think means everything is fine but now can see no
data - the entire dataset created is the same colour (white).
Is the data most likely still there and just not displaying
correctly, or has some of the attribute info all been lost and it all
does have the same value?
Did you set the current region to match the vector or raster of
training areas? ("Settings->Region->Set Region" and choose the
imported raster). Then in the map display use the zoom button to "Zoom
to computational region".
Yup. Ah, no wait. There is a problem here.
OK, now I see. Set the computational region to be the import raster
before working. I didn't see that the project region is different from
the computational region.
I definitely had g.region set but 'Then in the map display use the zoom
button to "Zoom to computational region"' I had completely missed.
I think it will always be a good idea to have 'show comp. extent' ticked on!
Many thanks.
You can also try "Vector->Query vector map->Query attribute data" to
see what you've got as far as attributes, and "Vector->Reports and
statistics->Basic metadata" to make sure that you have as many
polygons as you expect.
On 2012/08/16 18:48, Micha Silver wrote:
On 16/08/2012 18:11, Samantha Goodchild-Brown wrote:
Thank you
In my frustration I have reverted to linux version which has proved
useful - seeing more messages is helpful.
Mischa, your tip of g.region vect as well as finding reference to
v.in.region has proved helpful. This is likely to be my critical
mistake.
In using the 'grass interface' I have again hit the RRR:GGG:BBB
field request (as I did with windows).
It is very frustrating to find this now again when I can find no
other reference to it anywhere (not even in tuts cautioning to make
label column).
Is it absolutely neccessary to go into this at this point (go all
the way back and begin again) or is there a way to 'bypass' it?
Or some quick shortcut?
Can you copy into an email the commands you are running, and the
results (errors) you are getting?
If you're using the Linux terminal, then copy/paste the commands and
output, and post here.
Sam
On 2012/08/15 19:52, Paolo Cavallini wrote:
Or use OTB, also through sextante.
--
http://faunalia.eu/pc
Sent from mobile, sorry for being short
richard burcher <[email protected]> ha scritto:
Another option is to create training polygons& use [1] SAGA for the
supervised classification (either standalone or through the Sextante
plugin). I've recently gone this way for a maximum likelihood
classification.
[1]http://www.saga-gis.org/en/index.html
Cheers,
Richard
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