[R-sig-Geo] Newbie Questions

GRETA G. GRAMIG gggramig at students.wisc.edu
Wed Dec 20 17:57:07 CET 2006

I have limited experience with spatial analysis, but I am trying to learn. Perhaps someone with patience for a newbie will field my questions? If this is not the appropriate forum for such questions perhaps someone could suggest a more appropriate forum. 

I have a small dataset that consists of 128 x and y coordinates (latitude and longitude, on a small field scale). At each coordinate there are measurements for various soil properties along with a biomass yield measurement for each x,y.

Via spdep, using k=4 nearest neighbors for the weights, I have calculated Moran's I and Geary's C for the univariate relationships. For most of the measured variables there is statistically significant spatial autocorrelation.

I have also used Rgeo to plot some quintile scatterplots for each variable. Just from looking at these quintile plots I can see that, although the soil variables and yield are spatially autocorrelated, there does not seem to be a relationship between the patterns observed in soil variables vs. the patterns observed in the yield. 

In other words, I would like to know if there is a relationship between yield and phosphorus, taking into account the spatial dependence. But how can I test this? I have used GeoDa to compute the multivariate Moran's but I don't really understand what the program is doing or if this is the correct approach. 

Another thing I would like to be able to do is, for each variable, interpolate between measurements to create 2D maps of the response surface. 

I've searched everywhere I could think of but can't find any clear (and simple) examples to follow. This site: http://leg.ufpr.br/geoR/geoRdoc/geoRintro.html was some help but still kind of beyond me. 

Can someone  suggest a starting point (a book, article, or website) that might point me in the right direction? It would be especially great to have some examples using R to follow. 

I would really appreciate any advice on these matters! 


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