This is a general purpose R programming help list. Your post appears to be a very specific, subject matter question that should go to the R-Sig-geo list, where you are likely to get better and prompter responses.
Cheers, Bert Bert Gunter "Data is not information. Information is not knowledge. And knowledge is certainly not wisdom." -- Clifford Stoll On Tue, Dec 1, 2015 at 9:58 AM, Ateljevich, Eli@DWR <eli.ateljev...@water.ca.gov> wrote: > Hi, > I have point values of elevations on land (high resolution lidar) and in the > water (some are lower resolution single beam soundings or even just prior > elevation maps, others are high res multibeam). Let's say high resolution is > 1m and low is 10m, although the coarse case can be worse. > > >From this data I want to produce two smoothed datasets, one at 2m resolution > >where it is justified by the data and the other at 10m. Everywhere there is > >a 2m map there will be a corresponding 10m map, but not vice versa. > > To do this in a mutually compatible way, I envision producing a GAM that does > this: > 1. partition the surface into variations at higher and lower frequencies, so > that the 2m map could be considered the sum of a 10m general shape of the > channel plus a zero mean higher frequency fluctuation due to features. The > partition could be imperfect ... I'm sure frequencies will bleed and the > terrain is inherently anisotropic (channels with long length scales in the > downstream direction). > 2. somehow deal with the fact that the data come from different collections, > and are likely to be different in terms of bias, variance and point density. > I'd be willing to call one of the datasets "true" and declare a collection > effect for the others, but it would only be identifiable in a narrow region. > > Any recommendations? I am most familiar with mgcv but flexible on approach. > The GAM with tensors splines in the alongstream and cross-stream direction > have worked well for us at 10m in similar terrain without the added twist. > > Thanks! > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
