Thanks for the response. I used to determine the presence of strong spatial
trend by visualizing the semivariogram plot of empirical data. If the plot
increases without level off, then I assume there is a strong spatial trend.
Am I right with this approach? Is there a better way of detecting if there
is a *strong spatial trend*?

Thank you.


On Tue, Feb 18, 2014 at 10:19 AM, Edzer Pebesma <
edzer.pebesma@uni-muenster.de> wrote:

>
>
> On 02/18/2014 06:11 PM, Moshood Agba Bakare wrote:
> > Dear All,
> > In my yield data, I have longitude and latitude as spherical coordinates
> > which are converted into projected coordinates - easting and northing for
> > variogram modelling, yield as attribute variable, and elevation.
> > I fitted my empirical variogram as
> > empvar<-variogram(yield~1,canmod.sp,cutoff=600,width=3, cressie=TRUE).
> > In some documents I come across, some fitted the model using easting and
> > northing as covariate to yield as
> > yield ~easting+northing rather than yield ~1.
> > which one do you advise me to use yield ~easting+northing or yield ~1.
>
> If there is a strong spatial trend, general advice is to work on the
> residuals (~easting+northing), and use the same equation in the kriging
> step (universal or regression kriging).
>
> You could try both, if the difference is small, I'd suggest to not
> detrend (ie., use ~1)
>
> --
> Edzer Pebesma
> Institute for Geoinformatics (ifgi), University of Münster
> Heisenbergstraße 2, 48149 Münster, Germany. Phone: +49 251
> 83 33081 http://ifgi.uni-muenster.de GPG key ID 0xAC227795
>
>
> _______________________________________________
> R-sig-Geo mailing list
> R-sig-Geo@r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>
>

	[[alternative HTML version deleted]]

