Compute statistics for the cells of each layer of a Raster* object. In the raster package, functions such as max, min, and mean, when used with Raster* objects as argument, return a new Raster* object (with a value computed for each cell). In contrast, cellStats returns a single value, computed from the all the values of a layer. Also see layerStats

# S4 method for class 'RasterLayer'
cellStats(x, stat='mean', na.rm=TRUE, asSample=TRUE, ...)

# S4 method for class 'RasterStackBrick'
cellStats(x, stat='mean', na.rm=TRUE, asSample=TRUE, ...)

Arguments

x

Raster* object

stat

The function to be applied. See Details

na.rm

Logical. Should NA values be removed?

asSample

Logical. Only relevant for stat=sd in which case, if TRUE, the standard deviation for a sample (denominator is n-1) is computed, rather than for the population (denominator is n)

...

Numeric

Details

cellStats will fail (gracefully) for very large Raster* objects except for a number of known functions: sum, mean, min, max, sd, 'skew' and 'rms'. 'skew' (skewness) and 'rms' (Root Mean Square) must be supplied as a character value (with quotes), the other known functions may be supplied with or without quotes. For other functions you could perhaps use a sample of the RasterLayer that can be held in memory (see sampleRegular )

freq, quantile, minValue, maxValue, setMinMax

Examples

r <- raster(nrow=18, ncol=36)
values(r) <- runif(ncell(r)) * 10
# works for large files
cellStats(r, 'mean')
#> [1] 5.156144
# same, but does not work for very large files
cellStats(r, mean)
#> [1] 5.156144
# multi-layer object
cellStats(brick(r,r), mean)
#>  layer.1  layer.2
#> 5.156144 5.156144