[GRASS-user] Interpolating rainfall data across area from points

[Markus Metz]

On Thu, Oct 11, 2018 at 4:45 PM Rich Shepard <rshepard at appl-ecosys.com>
wrote:
>
> On Mon, 24 Sep 2018, Rich Shepard wrote:
>
> > Please provide some thoughts on the work flow to do this within GRASS.
I'm
> > digging into the gstat docs to get a sense of how to do this within R
(and
> > I have the rgrass7 package working well; it imported the GRASS county
> > boundary map which I converted to a SpatialPolygonDataFrame.)
>
>    I have run v.surf.tps on the point map of 58 reporting stations and am
> having difficulty understanding the output.

With only 58 points, you will not get a lot of spatial detail, no matter
what interpolation method you use. For example, using 58 points to create a
surface with e.g. 1 million points is a waste of time: there is simply not
enough spatial detail in the input. You can check, as you have done, by
changing the resolution of the current region for the output and comparing
the results. The only solution for more spatial detail is to get more input
points.

Markus M

> I suspect that because my data
> does not consist of evenly spaced sparsed points, I've accepted the
default
> thinning of 1.5, and I don't (yet) have a DEM covering the entire county
the
> output is not as usable as it could be. (I've changed the region's
> resolution to 100m.)
>
>    Regardless, I'm asking for input from those who have experience with
the
> geostatistical modules on how to determine the most appropriate one for a
> given data set. I see that v.krige[1], v.kriging, and v.surf.tps are
available
> and my lack of experiences with all of these hinders my making an informed
> decision.
>
>    Pointers to relevant documentation, as well as other advice, will be
much
> appreciated.
>
> TIA,
>
> Rich
>
> [1] The rpy2 dependency for v.krige is not yet available for R-3.5.1.
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