[GRASS-user] r.resamp.rst dynamic tension?

[Dylan Beaudette]

Did you folks make any progress on this matter? I am interested in the 
addition of variable tension to the RST suite of tools. Already we have had 
great success with the variable smoothness option.

Cheers,
Dylan

On Wednesday, March 30, 2011, Hamish wrote:
> Hi,
> 
> I am working with some u,v component wind data on a ~30 km grid which I
> wish to resample to a 3 km grid before r.what extractions at various
> fixed points. Often the winds have smooth transitions, so the small
> smoothing towards the mean that the spline does is not really a problem.
> Results so far with overlap=5 and tension=10 are very very nice.
> Stunning actually.. most of the time.
> 
> One thing I am worried about though is that it will smooth out the peaks,
> which can be very important and who's effects are non-linear - e.g. in
> fronts or the eye-wall of a hurricane. Conserving the area under the
> curve is not enough, it must preserve the peaks as well (due to dramatic
> effects of velocity^2, etc.).
> 
> the r.resamp.rst module has a smooth=raster_map option, I thought to
> maybe take the r.slope.aspect slope (1st deriv) of the overall magnitude
> map and apply it as dynamic smoothing, so calm areas allow a relaxed fit
> while areas of great change pull tighter. I guess that's more dynamic
> tension than dynamic smoothing though.
> 
> the manual says:
> """
>        For noisy data it is possible to define spatially variable
> smoothing by providing  a raster  map  named  by  the smooth option
> containing smoothing parameters.  With the smoothing parameter set to
> zero (smooth is not given or  contains  zero  data),  the resulting
> surface passes exactly through the data points.
> """
> 
> which sounds like it should already try to pass through outliers exactly
> as long as I don't use a smooth= map? As mentioned above, currently I'm
> using tension=10 and overlap=5 to get rid of outliers, probably
> introduced from an earlier resampling..
> 
> 
> a comparison of r.univar mean and std.dev. shows a slight reduction in
> overall range in the RST output map, but still closer to the original
> than a r.resamp.interp bilinear or bicubic interpolation.
> 
> 
> Losing the localized peaks due to grid aliasing is another concern, but
> there's less I can do about that AFAICT.
> 
> 
> any ideas?
> 
> 
> thanks,
> Hamish
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-- 
Dylan E. Beaudette
USDA-NRCS Soil Scientist
California Soil Resource Lab
http://casoilresource.lawr.ucdavis.edu/