# To parallelize spatial data, you often need to tile the data and process each tile separately.
# Here is a function that will take a bounding box, tile size and generate a tiling system.
# If given an overlap term, it will also add buffers to the tiles to reduce/eliminate edge effects, though this depends on what algorithm/model you are using.
tilebuilder=function(raster,size=10,overlap=NULL){
## get raster extents
xmin=xmin(raster)
xmax=xmax(raster)
ymin=ymin(raster)
ymax=ymax(raster)
xmins=c(seq(xmin,xmax-size,by=size))
ymins=c(seq(ymin,ymax-size,by=size))
exts=expand.grid(xmin=xmins,ymin=ymins)
exts$ymax=exts$ymin+size
exts$xmax=exts$xmin+size
if(!is.null(overlap)){
#if overlapped tiles are requested, create new columns with buffered extents
exts$yminb=exts$ymin
exts$xminb=exts$xmin
exts$ymaxb=exts$ymax
exts$xmaxb=exts$xmax
t1=(exts$ymin-overlap)>=ymin
exts$yminb[t1]=exts$ymin[t1]-overlap
t2=exts$xmin-overlap>=xmin
exts$xminb[t2]=exts$xmin[t2]-overlap
t3=exts$ymax+overlap<=ymax
exts$ymaxb[t3]=exts$ymax[t3]+overlap
t4=exts$xmax+overlap<=xmax
exts$xmaxb[t4]=exts$xmax[t4]+overlap
}
exts$tile=1:nrow(exts)
return(exts)
}
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