Hi Adam,

Here is code for something very similar that I was doing, which should help
with what you want to do. In this case, I made grids of varying resolution
to cover the extent of the area defined by my points, and then collected
the grid ids for each resolution and bound them to the
SpatialPointsDataFrame. I also got the center coordinates from each grid
cell so that I could represent the cells as points.

# Create sampling grid
# Grid template, bumped out 20 km on either side from extent of p
(SpatialPointsDataFrame)
rex <- extent(p)
gr <- raster(xmn = rex@xmin - 20000, xmx = rex@xmax + 20000, ymn =
rex@ymin- 20000, ymx = rex@ymax+ 20000)

# Adjust grid size and collecting grid ids under points for each resolution
polID.l <- c("km1", "km5", "km10", "km20")
res.l <- c(1000, 5000, 10000, 20000)
coord.l <- c("xy1", "xy5", "xy10", "xy20")
grid.l <- vector("list", length(res.l))  # list to hold dummy grids

# Extract
for(i in 1:4) {
 gr.2 <- gr
 res(gr.2) <- res.l[i]
 print(res.l[i])
 projection(gr.2) <- p@proj4string
 gr.2[] <- 1:ncell(gr.2)
 grid.l[[i]] <- gr.2
 xy <- cbind(1:ncell(gr.2), xyFromCell(gr.2, 1:ncell(gr.2)))  # Center
coordinates
 colnames(xy)[1] <- polID.l[i]
 print(coord.l[i])
 assign(coord.l[i], xy)
 p$km <- extract(gr.2, p)
 colnames(p@data)[length(colnames(p@data))] <- polID.l[i]
}

Hope this helps.

Cheers, Lyndon


On Thu, Feb 2, 2012 at 12:13 AM, ADAM PETER CARDILINI
<apcar@deakin.edu.au>wrote:

> G'day All,
>
>
>
> I have been struggling to figure out an answer to this question and wasn't
> sure where else to ask, so here goes. I have a large amount of
> presence/absence point data (~125,000) with lon/lat coordinates. Like this:
>
> Lat                          lon                          abs/pres
>      date
>
> 113.6481              -24.90278             0
>  1/1/1998
>
> 113.6481              -24.90278             1
>  1/2/1998
>
> 113.6481              -24.90278             0
>  1/3/1998
>
> 137.5175              -35.69556             1
>  1/1/1998
>
> 137.5175              -35.69556             1
>  1/2/1998
>
> 137.5175              -35.69556             1
>  1/3/1998
>
>
>
> I have been trying to work out a way to identify the cells that each point
> would fall into if it were mapped onto a raster grid (I am using rasters
> with the same cell resolution as BIOCLIM rasters). That is, for all points
> falling within the same cell, I would like to identify them as being a part
> of the same cell. I am trying to model site occupancy for this species from
> repeated survey data, using the package 'unmarked', which requires records
> to be associated with sites. I don't have site IDs with this data so I need
> to come up with a proxy for this. I thought I could use grid cell id as a
> proxy for site id, so that all records that fall within the same grid cell
> can be considered the same site.
>
> How do I identify the grid cell that each point falls into on a raster
> grid and associate it with my presence/absence data, to produce a dataset
> that looks like this?
>
> Lat                          lon                          abs/pres
>      date                       cellID
>
> 113.6481              -24.90278             0
>  1/1/1998              234
>
> 113.6481              -24.90278             1
>  1/2/1998              234
>
> 113.6481              -24.90278             0
>  1/3/1998              234
>
> 137.5175              -35.69556             1
>  1/1/1998              250
>
> 137.5175              -35.69556             1
>  1/2/1998              250
>
> 137.5175              -35.69556             1
>  1/3/1998              250
>
>
>
> Thanks for your help in advance.
>
>
>
> Kind regards,
>
> Adam Cardilini
>
>
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>
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