How can you crop raster layers in R in a batch and

I was working with spatial data to get ready for analyses - I have a DEM at the desired extent of my study area, though I have ~39 other layers at the national scale (US). Is there a way to crop all of these 39 layers to the same extent as the DEM at once?

Also, I will be overlaying the output with other layers in a different projection. Is it possible to adjust the projection and pixel size of the output layers?

I am trying to use freeware as much as possible for my data manipulation...

I had the problem above, but have written a function in R to do all of this in a batch - see below. I had 39 climate data layers at the scale of the continental U.S. (from PRISM Climate Data group; http://www.prism.oregonstate.edu/), and wanted to clip them to the extent of a DEM, in southern California, reproject them, and export them for easy import and use with other layers in SAGA GIS. Below is the code, with an example of how it would be run, setting the working directory to the folder that has the layers that you want to crop, and only those layers.

During the processing, all data are stored in memory, so with huge datasets, it might get hung up because of lack of memory... that would probably be something that would be good to improve.

Also, a response on the R Forum provided a shorter, more elegant way to do it too: http://permalink.gmane.org/gmane.comp.lang.r.geo/18320

I hope somebody finds it useful!

#########################################
#BatchCrop Function ###
#by Mike Treglia, mtreglia@gmail.com ###
###Tested in R Version 3.0.0 (64-bit), using 'raster' version 2.1-48 and 'rgdal' version 0.8-10
########################################
#This function crops .asc raster files in working directory to extent of another layer (referred to here as 'reference' layer), converts to desired projection, and saves as new .asc files in the working directory. It is important that the original raster files and the reference layer are all in the same projection, though different pixel sizes are OK. The function can easily be modified to use other raster formats as well
#Note, Requires package 'raster'
#Function Arguments:
#'Reference'  refers to name of the layer with the desired extent; 'OutName' represents the intended prefix for output files; 'OutPrj' represents the desired output projection; and 'OutRes' represents the desired Output Resolution
BatchCrop<-function(Reference,OutName,OutPrj,OutRes){
        filenames <- list.files(pattern="*.asc", full.names=TRUE)   #Extract list of  file names from working directory
        library(raster) #Calls 'raster' library
        #Function 'f1' imports data listed in 'filenames' and assigns projection
            f1<-function(x,z) {
            y <- raster(x)
            projection(y) <- CRS(z)
            return(y)
            }
            import <- lapply(filenames,f1,projection(Reference))
        cropped <- lapply(import,crop,Reference)    #Crop imported layers to reference layer, argument 'x'
        #Function 'f2' changes projectection of cropped layers
            f2<-function(x,y) {
            x<-projectRaster(x, crs=OutPrj, res=OutRes)
            return(x)
            }
            output <- lapply(cropped,f2,OutPrj)
        #Use a 'for' loop to iterate writeRaster function for all cropped layers
        for(i in (1:max(length(filenames)))){           #
            writeRaster(output[[i]],paste(deparse(substitute(OutName)), i), format='ascii')
            }
            }
#############################################
###Example Code using function 'BatchCrop'###
#############################################
#Data layers to be cropped downloaded from: http://www.prism.oregonstate.edu/products/matrix.phtml?vartype=tmax&view=maps [testing was done using 1981-2010 monthly and annual normals; can use any .asc layer within the bounds of the PRISM data, with projection as lat/long and GRS80]
#Set Working Directory where data to be cropped are stored
setwd("D:/GIS/PRISM/1981-2010/TMin")
#Import Reference Layer
reference<-raster("D:/GIS/California/Hab Suitability Files/10m_DEM/10m DEM asc/DEM_10m.asc")
#Set Projection for Reference Layer
projection(reference) <- CRS("+proj=longlat +ellps=GRS80")
#Run Function [desired projection is UTM, zone 11, WGS84; desired output resolution is 800m]
BatchCrop(Reference=reference,OutName=TMinCrop,OutPrj="+proj=utm +zone=11 +datum=WGS84",OutRes=800)