Zonal statistics

Compute zonal statistics, that is summarized values of a Raster* object for each "zone" defined by a RasterLayer.

If stat is a true function, zonal will fail (gracefully) for very large Raster objects, but it will in most cases work for functions that can be defined as by a character argument ('mean', 'sd', 'min', 'max', or 'sum'). In addition you can use 'count' to count the number of cells in each zone (only useful with na.rm=TRUE, otherwise freq(z) would be more direct.

If a function is used, it should accept a na.rm argument (or at least a ... argument)

# S4 method for class 'RasterLayer,RasterLayer'
zonal(x, z, fun='mean', digits=0, na.rm=TRUE, ...) 

# S4 method for class 'RasterStackBrick,RasterLayer'
zonal(x, z, fun='mean', digits=0, na.rm=TRUE, ...)

Arguments

x

Raster* object

z

RasterLayer with codes representing zones

fun

function to be applied to summarize the values by zone. Either as character: 'mean', 'sd', 'min', 'max', 'sum'; or, for relatively small Raster* objects, a proper function

digits

integer. Number of digits to maintain in 'zones'. By default averaged to an integer (zero digits)

na.rm

logical. If TRUE, NA values in x are ignored

...

additional arguments. One implemented: progress, as in writeRaster

Value

A matrix with a value for each zone (unique value in zones)

See also

See cellStats for 'global' statistics (i.e., all of x is considered a single zone), and extract for summarizing values for polygons

Examples

r <- raster(ncols=10, nrows=10)
values(r) <- runif(ncell(r)) * 1:ncell(r)
z <- r
values(z) <- rep(1:5, each=20)
# for large files, use a character value rather than a function
zonal(r, z, 'sum')
#>      zone      sum
#> [1,]    1 106.8764
#> [2,]    2 332.4794
#> [3,]    3 576.8979
#> [4,]    4 831.4907
#> [5,]    5 987.6777

# for smaller files you can also provide a function
if (FALSE) { # \dontrun{
zonal(r, z, mean)
zonal(r, z, min)
} # }

# multiple layers
zonal(stack(r, r*10), z, 'sum')
#>      zone  layer.1  layer.2
#> [1,]    1 106.8764 1068.764
#> [2,]    2 332.4794 3324.794
#> [3,]    3 576.8979 5768.979
#> [4,]    4 831.4907 8314.907
#> [5,]    5 987.6777 9876.777