[R] evaluating spatial autocorrelation in a raster

[Roger Bivand]

Julie Lee-Yaw <julleeyaw <at> yahoo.ca> writes:

> 
> Hi
> I am attempting to explore the scale of spatial autocorrelation in a
raster (eventually across a stack of 10
> but for now a single layer) and consequently in a potential sample of
points across the landscape (ie. if we
> wanted to know what sampling design in terms of distance would minimize
autocorrelation). 

This could with advantage been posted on R-sig-geo rather than on R-help.

The main problem will be in the raster resolution, as this will most likely
not match the "natural" resolution of the phenomena of interest, thus
spuriously generating apparent spatial autocorrelation. It may be hard to
choose an appropriate sampling design.

> Please forgive me if I’m approaching this problem incorrectly altogether!
I’m eventually hoping to
> say something along the lines of “if we take sites x distance apart, we
can be fairly sure that the amount
> of spatial autocorrelation in our climate data will be minimal”. But maybe
this is completely
> ridiculous? I’d be really happy to have some suggestions. (and on a side
note, I’m currently
> looking for a good introduction to spatial statistics course or
textbook…something for the truly
> uninitiated. Any recommendations?)

Look for work by Werner Mueller on sampling design, and work citing his work.

> Many thanks!
> PS. Online sources for some of the code above:
>
http://www.r-bloggers.com/spatial-correlograms-in-r-a-mini-overview/http://www.bias-project.org.uk/ASDARcourse/unit6_slides.pdf


> 
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> 
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Please do provide a self-contained example.

Roger