[GRASS-user] r.resamp.rst Producing Bad Values

[Carl Brown]

I'm trying to clean up a noisy data set using r.resamp.rst.
I used the following procedure successfully:

tcurv30 is a tangential curvature map generated by r.slope.aspect from the 
data, at 30 meter resolution.

tsmooth30 = abs(tcurv30) * 500
(r.resamp.rst does not accept negative smoothing values)

Range of data in tsmooth30:    min = 0.000000  max = 8.164329

(history) generated by r.resamp.rst
tension=213.504205, smoothing=tsmooth30
dnorm=374.699880, zmult=1.000000
KMAX=50, KMIN=35, errtotal=0.289533
zmin_data=450.160004, zmax_data=500.000000
zmin_int=450.592767, zmax_int=500.449846

The tension was set to 40, and the map was resampled to 10m resolution.
So far, so good.

Now I would like to run a similar procedure on the 10m data map, but without 
changing the resolution:

tcurv10 is a tangential curvature map generated by r.slope.aspect from the 
resampled and smoothed data, at 10 meter resolution.

tsmooth10 = abs(tcurv10) * 500

Range of data in tsmooth10:    min = 0.000000  max = 23.222006

(history) generated by r.resamp.rst
tension=320.256308, smoothing=tsmooth10
dnorm=124.899960, zmult=1.000000
KMAX=50, KMIN=35, errtotal=nan
zmin_data=450.592773, zmax_data=500.449860
zmin_int=nan, zmax_int=nan

(Again, the tension was set to 40)

The "nan" values appear in an unbroken band around the perimeter of the 
region, 6 to 8 cells wide. It should be noted that all the data is well 
inside the perimeter, so the portion of the smoothing map which seems to be 
causing the trouble consists entirely of zero values. The rest of the map, 
which includes all of the data, appears to have been correctly processed.

This problem does not occur if I use constant-value smoothing maps. I tried 
both zero and nonzero (1 and 10) constant values.

I tried changing the tsmooth10 map to:

tsmooth10 = max( 1, abs(tcurv10) * 500 )

And to:

tsmooth10 = abs(tcurv10) * 250

I tried changing the output resolution in r.resamp.rst to 5m.

The problem still occurs in all cases. I would simply work around it, but 
r.mapcalc will not replace "nan" values. I am out of ideas. Any suggestions?

-- 
Carl Brown
Whitefield, NH USA