A TIN cannot represent that data structure, the plot shows multiple
surfaces that wrap around in 3D. (A TIN cannot do that). The plot is made
by "contouring" (isosurfaces) from a 3D array.

You can represent the array in NetCDF, and maybe your GIS can read that.
Otherwise you could do the same as here but create a 2D raster for every
slice in the 3rd dimension and reconstruct over there.

Bare bones using raster to NetCDF:

library(raster)
r <- brick(UD$estimate, xmn = min(UD$eval.points[[1]]), xmx =
max(UD$eval.points[[1]]),
  ymn = min(UD$eval.points[[2]]), ymx = max(UD$eval.points[[2]]))

## Plot each 3D slice
plot(r)

## write to NetCDF, you need ncdf or ncdf4 package
writeRaster(r, "file.nc")

See ?writeRaster for further options to add descriptors to the file, and
you will likely need to worry about the orientation when making the raster
object.



On Sat, Apr 13, 2013 at 4:29 AM, Duff, Andrew A (DFW) <
Andrew.Duff@dfw.wa.gov> wrote:

> I am interested in being able to export the results of a 3 dimensional
> kernel density estimate from the ks package in R to a format that could be
> viewed in 3D GIS application such as ESRI's ArcScene or ArcGlobe.  I want
> to example the use of airspace in relation to terrain features.  A TIN
> seems to be the most logical geospatial data structure that would support
> taking the 3D kde output into GIS.  Does anybody have any ideas on how to
> get from a 3D kde output in ks to a tin.  A self-contained sample of
> generating the kde is below.
>
> ###sample
> library(ks)
> df <- data.frame("x"=sample(1:200, 10), "y"=sample(1:200, 10),
> "z"=sample(1:500, 10))
> Hpi1 <- Hpi(x = df)
> UD <- kde(x=df, H=Hpi1)
> plot(UD)
>
> Thanks in advance.
>
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>
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>



-- 
Michael Sumner
Hobart, Australia
e-mail: mdsumner@gmail.com

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