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

Thomas Adams tea3rd at gmail.com
Thu Oct 11 08:15:11 PDT 2018

Hello Rich,

Few (if any) of the spatial interpolation algorithms require "evenly
spaced" data. Ultimately, you want spatial estimates that produce the least
bias and where the errors are gaussian distributed, which can only be
determined using some process of bootstrapping where stations are removed
from the spatial interpolation process and are then used to evaluate error
at those locations; and then, repeated, with a new set of stations. This
should be done with several spatial interpolation algorithms that are
generally known to produce the best estimates.

If you are trying to produce estimates over an entire county, you really
need stations well outside the county boundary to avoid having problems
near the county periphry (interior of the county boundary). GRASS and R
play really well together through spgrass7, so that open the use of many R
based geostatistical packages.


On Thu, Oct 11, 2018 at 10:45 AM Rich Shepard <rshepard at appl-ecosys.com>

> 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. 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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