I am going to do a project based on kriging. The targeted area would be as big as United States and my grid would be 10km*10km. I am wondering the differences of efficiencies for the methods implemented in geoR package and ArcGIS. Have anyone done any research on the performance yet. I would prefer geoR if it works well.

  • 6
    Usually, the big issue is capabilities rather than performance, unless you are doing extensive compute-intensive simulation. A 10 km grid in the US would be fairly small (it should need only about 75,000 nodes). geoR (along with geoRglm) implements a wider variety of models (such as generalized linear stochastic fields and Bayes priors) than anything available for ArcGIS; by means of its integration with R, it also supports far more exploratory and diagnostic tools (which are essential for defensible modeling). geoR is harder to use than Geostatistical Analyst. – whuber Feb 12 '12 at 0:00

I would also suggest to consider the gstat package (either standalone or the R package), which -in my experience - is a bit between geoR and Geostatistical Analyst: you do not have the very advanced models of geoR but it's more efficient from a computing perspective (its core is in C).

Also, you might be interested in the automap and intamap packages.

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.