Hi all,

I've got a georeferenced grid with elevation data (height of land, depth below sea level). I have loaded it into R in various formats.

I would like to coarsen it to match other environmental datasets for species distribution modeling purposes, but I feel that the coarsened grid should include some of the information from the finer-resolution layer -- e.g., if a coarse grid cell has an island in it, the depth should not simply be the mean of the finer pixels, there should be a layer than says "min depth=0" for that pixel.

So, I would like to have 3 coarse layers, with max(depth), min(depth), and mean(depth).

What would be the most efficient method/R function for coarsening a grid in this fashion?

Help much appreciated!!

Cheers!
Nick


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====================================================
Nicholas J. Matzke
Ph.D. Candidate, Graduate Student Researcher

Huelsenbeck Lab
Center for Theoretical Evolutionary Genomics
4151 VLSB (Valley Life Sciences Building)
Department of Integrative Biology
University of California, Berkeley

Graduate Student Instructor, IB200B
Principles of Phylogenetics: Ecology and Evolution
http://ib.berkeley.edu/courses/ib200b/
http://phylo.wikidot.com/


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Cell phone: 510-301-0179
Email: mat...@berkeley.edu

Mailing address:
Department of Integrative Biology
3060 VLSB #3140
Berkeley, CA 94720-3140

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"[W]hen people thought the earth was flat, they were wrong. When people thought the earth was spherical, they were wrong. But if you think that thinking the earth is spherical is just as wrong as thinking the earth is flat, then your view is wronger than both of them put together."

Isaac Asimov (1989). "The Relativity of Wrong." The Skeptical Inquirer, 14(1), 35-44. Fall 1989.
http://chem.tufts.edu/AnswersInScience/RelativityofWrong.htm

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