On Thursday 18 May 2006 01:07, orkun wrote:
THANK YOU
Dylan Beaudette wrote:
>On Wednesday 17 May 2006 00:42, orkun wrote:
>>Dylan Beaudette wrote:
>>>On Tuesday 16 May 2006 02:59, orkun wrote:
>>>>hello
>>>>
>>>>can I produce stream map using r.terraflow maps ?
>>>>
>>>>regards
>>>
>>>here is one such example:
>>>
>>>http://casoilresource.lawr.ucdavis.edu/drupal/node/166
>>>
>>>cheers,
>>
>>thank you
>>
>>I looked the site you directed me.
>>Compared to r.watershed, r.terraflow produced stream map much faster. But
>>there seems to be broken streams. Although I lowered the accumulation
>>threshold value, broken streams still exist.
>>How can I get unbroken streams using r.terraflow.
>
>Hi,
>
>You could try computing the line lengths, and throwing out features that
> are less that a given length:
>
>v.to.db ...
>v.extract ...
In fact, I want to join broken lines to continuous lines, which are from
head of
upstream to downstream.
Hmm.. that might be a little bit harder. It might be simpler to extract _more_
lines than required, from the output of r.terraflow, and then remove the
extra lines that you do not want.
one possible way with with some raster commands:
r.terraflow elev=elev direction=dir filled=filled tci=tci acc=acc
swatershed=watershed
#get the watersheds
r.to.vect in=watershed out=watershed feature=area -s -v
#
#two possible ways to extract a very rough stream network
r.mapcalc "streams = if(tci >= 10, 1, null())"
#once you have your streams, then experiment with r.grow / r.thin to get the
best looking stream network.
>Or.. it would be even better to characterize stream networks according to
>their "order" , based on the number of contributaries feed into the main
>channel. Then, keep all streams of order _n_ or greater.
>
>>Since I worked on DEM quality, I saw some interesting features
>>in the other part of the site. Does "DEM vs. Field Slope" show
>>DEM's quality.
>
>I think that you might be referring to this image:
>http://casoilresource.lawr.ucdavis.edu/drupal/node/189?size=_original
>
>The title is a little confusing, as it is a comparison between slope
> values measured in the field with a clinometer compared with slope values
> computed from a DEM via r.slope.aspect . The take-home message from that
> graph was that the DEM-computed slope values tended to under estimate
> field measured values [1]. Also that a comparison between DEM and field
> slope seemed to work best when comparing average slope within a 20 meter
> radius as compared to using the DEM derived slope value at the exact
> location of the field measurement.
simply ground truth ? if so, what a coincidence !
All I want to do is to choose terrain models that are
produced with different parameters and methods
reflect real ground conditions.
that is to say:
which interpolation method for contour elevation data?
and which grid spacing ?
that is the topic of _many_ articles in the literature. I would suggest the
book Terrain Analysis for a good background:
Hutchinson, M.F. & Gallant, J.C. Wilson, J.P. & Gallant, J.C. (ed.) Digital
elevation models and representation of terrain shape Terrain Analysis, John
Wiley and Sons Inc., 2000 .
>[1] note that field measurement of slope is not an exact science, and is
>certainly not conducted at the same scale at which the DEM for this area
> was created (10 meter grid) .
Is "10 m grid" your preference to create slope map. Actually it
is my preference. As far as I see coarser grid than 10 m cannot
some morphological features such as slope, curvature, streams
and etc.
If you have time, I want to know your ideas.
All I had to work with was a 10 meter grid... you might try r.resamp.rst for a
finer grid ... however your results may vary.
I hope, grass will have krig interpolation feature
in next version.
you should be able to do this via the GRASS->R interface described in the
GRASS Newsletter vol. 3 (http://grass.itc.it/newsletter/GRASSNews_vol3.pdf)
cheers,
--
Dylan Beaudette
Soils and Biogeochemistry Graduate Group
University of California at Davis
530.754.7341