# cellStats

0th

Percentile

##### Statistics across cells

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

Keywords
spatial, univar
##### Usage
# S4 method for RasterLayer
cellStats(x, stat='mean', na.rm=TRUE, asSample=TRUE, ...)# S4 method for 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)

...

##### 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 )

##### Value

Numeric

freq, quantile, minValue, maxValue, setMinMax

##### Aliases
• cellStats
• cellStats,RasterLayer-method
• cellStats,RasterStackBrick-method
##### Examples
# NOT RUN {
r <- raster(nrow=18, ncol=36)
r[] <- runif(ncell(r)) * 10
# works for large files
cellStats(r, 'mean')
# same, but does not work for very large files
cellStats(r, mean)
# multi-layer object
cellStats(brick(r,r), mean)
# }

Documentation reproduced from package raster, version 2.9-5, License: GPL (>= 3)

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