splitRaster divides up a raster into an arbitrary number of pieces (tiles). Split rasters can be recombined using do.call(merge, y) or mergeRaster(y), where y <- splitRaster(x).

mergeRaster(x)

# S4 method for list
mergeRaster(x)

splitRaster(r, nx = 1, ny = 1, buffer = c(0, 0),
path = file.path(getwd(), names(r)), cl)

# S4 method for RasterLayer
splitRaster(r, nx = 1, ny = 1, buffer = c(0, 0),
path = file.path(getwd(), names(r)), cl)

## Arguments

x

A list of split raster tiles (i.e., from splitRaster).

r

The raster to be split.

nx

The number of tiles to make along the x-axis.

ny

The number of tiles to make along the y-axis.

buffer

Numeric vector of length 2 giving the size of the buffer along the x and y axes. If these values less than or equal to 1 are used, this is interpreted as the number of pixels (cells) to use as a buffer. Values between 0 and 1 are interpreted as proportions of the number of pixels in each tile (rounded up to an integer value). Default is c(0, 0), which means no buffer.

path

Character specifying the directory to which the split tiles will be saved. If missing, the function creates a subdirectory in the current working directory based on the raster's name (i.e., using names(x)).

cl

A cluster object. Optional. This would generally be created using parallel::makeCluster or equivalent. This is an alternative way, instead of beginCluster(), to use parallelism for this function, allowing for more control over cluster use.

## Value

mergeRaster returns a RasterLayer object. splitRaster returns a list (length nx*ny) of cropped raster tiles.

## Details

mergeRaster differs from merge in how overlapping tile regions are handled: merge retains the values of the first raster in the list. This has the consequence of retaining the values from the buffered region in the first tile in place of the values from the neighbouring tile. On the other hand, mergeRaster retains the values of the tile region, over the values in any buffered regions. This is useful for reducing edge effects when performing raster operations involving contagious processes. To use the average of cell values, or do another computation, use mosaic.

This function is parallel-aware, using the same mechanism as used in the raster package. Specifically, if you start a cluster using beginCluster, then this function will automatically use that cluster. It is always a good idea to stop the cluster when finished, using endCluster.

merge, mosaic do.call, merge.

## Examples

library(raster)

# an example with dimensions:
# nrow: 77
# ncol: 101
# nlayers: 3
b <- brick(system.file("external/rlogo.grd", package = "raster"))
r <- b[[1]] # use first layer only
nx <- 1
ny <- 2

tmpdir <- file.path(tempdir(), "splitRaster-example")
dir.create(tmpdir)

y0 <- splitRaster(r, nx, ny, path = file.path(tmpdir, "y0")) # no buffer

# buffer: 10 pixels along both axes
y1 <- splitRaster(r, nx, ny, c(10, 10), path = file.path(tmpdir, "y1"))

# buffer: half the width and length of each tile
y2 <- splitRaster(r, nx, ny, c(0.5, 0.5), path = file.path(tmpdir, "y2"))

# parallel cropping
if (interactive()) {
n <- pmin(parallel::detectCores(), 4) # use up to 4 cores
beginCluster(n)
y3 <- splitRaster(r, nx, ny, c(0.7, 0.7), path = file.path(tmpdir, "y3"))
endCluster()
}

# the original raster:
if (interactive()) plot(r) # may require a call to dev() if using RStudio
# the split raster:
layout(mat = matrix(seq_len(nx * ny), ncol = nx, nrow = ny))
plotOrder <- c(4, 8, 12, 3, 7, 11, 2, 6, 10, 1, 5, 9)
if (interactive()) invisible(lapply(y0[plotOrder], plot))#> Warning: no non-missing arguments to min; returning Inf#> Warning: no non-missing arguments to max; returning -Inf#> Warning: no non-missing arguments to min; returning Inf#> Warning: no non-missing arguments to max; returning -Inf#> Error in plot.window(...): need finite 'xlim' values
# can be recombined using raster::merge
m0 <- do.call(merge, y0)
all.equal(m0, r) ## TRUE#> [1] TRUE
m1 <- do.call(merge, y1)
all.equal(m1, r) ## TRUE#> [1] TRUE
m2 <- do.call(merge, y2)
all.equal(m2, r) ## TRUE#> [1] TRUE
# or recombine using mergeRaster
n0 <- mergeRaster(y0)
all.equal(n0, r) ## TRUE#> [1] TRUE
n1 <- mergeRaster(y1)
all.equal(n1, r) ## TRUE#> [1] TRUE
n2 <- mergeRaster(y2)
all.equal(n2, r) ## TRUE#> [1] TRUE
unlink(tmpdir, recursive = TRUE)