Go from multiple rasters to R compatible table

Question

I have a set of geocoded, pixel-aligned rasters which I would like to use in a model in R. I would like to produce a table of data that can be imported to R, in which there are as many columns as rasters, and as many rows as points at which data is extracted from the rasters. Say I have 3 rasters: r1, r2, r3. I would end up with a table that has r1, r2, r3 as the column headers. The rows would be point1, point2, point3 - and there would be as many rows as points in the layer used to define which points to extract data from. Forgive the bad table:

------r1---r2---r3

point1-1----4---2

point2-4----3---1

How can I do this? I've tried some Arc tools but they have failed or hung. I can use QGIS, Arc or Idrisi.

Is the Raster package for R a good approach?

Answer 1

I think what you are after is:

library(raster)
library(rgdal)

s <- stack('r1.tif', 'r2.tif', 'r3.tif')
d <- values(s)

Avoid exporting grids to ascii, that only slows things down, and you loose information on the coordinate reference system.

Answer 2

Yes, use Raster. Here is an example using five coincident raster objects r.a ... r.e. In practice, you would read these from (say) ASCII exports of the grids:

data <- vapply(list(r.a,r.b,r.c,r.d,r.e), "[", rep(0.0, ncol(r.a)*nrow(r.a)))

The purpose of the "0.0" is to indicate you want an array of floats. If the data are integral, use an integer for this value instead.