Tara, I think you need to 'rasterize' function

library(raster)

r <- raster(ncol=10, nrow=10)

x <- c(-25, -148, 46, 23, 0, -69)

y <- c(-45, 30, 20, -10, 50, -7)

value <- c(1, 2, 3, 4, 5, 6)

# you can do this:

r1 <- rasterize(cbind(x, y), r, value)

plot(r1)

# or

sp <- SpatialPointsDataFrame(cbind(x,y), data.frame(v=value))

r2 <- rasterize(sp, r, 'v')

# or a more "manual" approach

cells <- cellFromXY(r, cbind(x,y))

r[cells] <- value

# safer would be:

# r[cells[!is.na(cells)]] <- value[!is.na(cells)]

This is not in the Bivand et al book ( which was written before the raster

package was released ).

Robert

On Sat, Sep 17, 2011 at 4:48 PM, Tara Bridwell <

[hidden email]>wrote:

> I have a dataset that consists of point coordinates and values

> associated with the points. I want to be able to grid the values, and

> then do calulations using the values using the various raster

> functions. I am, however, finding this difficult to do. I have tried

> a number of functions including rasterize, SpatialGridDataFrame, and

> SpatialGridDataFrame but I think I am missing a bit of the theory

> behind this that I can't seem to piece together. I have the Applied

> Spatial Data Analysis (Bivand) but couldn't seem to find an

> appropriate section. Here is an example data set:

>

> require(raster)

>

> r <- raster(ncol=10, nrow=10)

>

> r[]=1:ncell(r)

>

> x <- c(-45, 30, 20, -10, 50, -7)

>

> y <- c(-25, -148, 46, 23, 0, -69)

>

> value <- c(1, 2, 3, 4, 5, 6)

>

> coord.plus.value <- cbind(x, y, value)

>

> coord.plus.value_sp <- SpatialPoints(coord.plus.value)

>

> >From here I want to plot 'value' using the raster 'r'.

>

> Suggests on how to do this, as well as thoughts on the basic theory I

> seem to be missing (or where in the Bivand book I should be reading

> that I have missed) would be appreciated.

>

> Thank you,

>

> Tara Bridwell

>

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