Hello again,

Apparently my original posting has generated a bit of confusion. I'll try to
explain better this time.

The analysis I'm pursuing involves a landscape change assessment. Data were
collected from 1513 townships across the entire state of Michigan, USA.
These data inlcude social-economic information from 1990 and 2000, and they
are georeferenced to each of the unique reporting townships.  In addition,
my colleagues and I had produced a statewide landscape fragmentation
analysis using a TM satellite image also using the same 1513 townships for
the reporting units.  So we have a series of landscape fragmentation metrics
and a series of social-economic measures.  The model(s) we are developing
will use the fragmentation analysis as a response to the independent social
economic parameters.

I'm running GWR models in the GWR program (not R) and need to associate
several items from the GWR output back to the shapefile.  The Z values I
referred to are predicted(response), residuals, and influence.  I'd like to
be able relate these values to the polygonal features of the shapefile.
Graphically I'd like to produce a series of maps integrating both vectors
and a continuous surface represented by the Z value.

If anyone can offer suggestions I'd be very happy.

Thanks
Steve



On 11/8/07, Tom Hengl <hengl@science.uva.nl> wrote:
>
>
> Another option to generate land surface models is the package gstat. You
> can even use the position of streams/ridges to force physiographic breaks
> in your output DEM.
>
> The methodology and a sample dataset is available here:
> http://geomorphometry.org/view_scripts.asp?id=6
>
> The paper explaining the processing steps is still in review, but a
> preprint can always be ordered.
>
> Tom Hengl
> http://spatial-analyst.net
>
> > Here's one simple way, using package akima:
> >
> >
> > library(sp)
> >
> > data(meuse)
> >
> > ## assume your data is Spatial*
> >
> > coordinates(meuse) <- ~x+y
> >
> >
> >
> > ## use "elev" column in akima
> > library(akima)
> >
> > ## define a grid
> > xx <- coordinates(meuse)[,1]
> > yy <- coordinates(meuse)[,2]
> > ## modify offset of 100 to match your data, or use a proportion
> > grd <- expand.grid(x = seq(min(xx) - 200,  max(xx) + 200, length = 100),
> >           y = seq(min(yy) - 200, max(yy) + 200, length = 100))
> >
> >
> > res <- interpp(xx, yy, meuse$elev, grd$x, grd$y)
> > res <- as.data.frame(res) ## akima output is a list of 3 equal-length
> > vectors like grd passed in
> >
> >
> > ## if you want to interpolate on another "Z", repeat as desired, adding
> > to output
> > res$cadmium <- interpp(xx, yy, meuse$cadmium, grd$x, grd$y)$z
> >
> >
> > coordinates(res) <- ~x+y
> > gridded(res) <- TRUE
> >
> > ## if you don't have a lot of empty cells
> > fullgrid(res) <- TRUE
> >
> > image(res, "z")
> >
> > ## confirm where the high values were
> > points(meuse$x, meuse$y, cex = meuse$elev/5)
> >
> > image(res, "cadmium")  ## etc
> >
> > spplot(res)
> >
> >
> >
> >
> > Steve Friedman wrote:
> >> Hi,
> >>
> >> I have a spatial data set consisting of several z values and UTM
> >> coordinates.  Can someone direct me to documentation describing how I
> >> can
> >> plot specific z values using the coordinates to develop a continuous
> >> surface
> >> map?
> >>
> >> Thanks
> >> Steve
> >>
> >>      [[alternative HTML version deleted]]
> >>
> >> _______________________________________________
> >> R-sig-Geo mailing list
> >> R-sig-Geo@stat.math.ethz.ch
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >>
> >>
> >>
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > R-sig-Geo@stat.math.ethz.ch
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >
>
>
>


-- 
Steve Friedman
Phone 561 - 744  - 4642
Cell 517 - 648 - 6290

	[[alternative HTML version deleted]]


