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Statistics on cells of a GRaster stratified by cells of another raster

Source: R/zonal.r
zonal.Rd

Function zonal() calculates statistics (mean, sum, etc.) on cells of a GRaster by "zones" created by cells of another GRaster or GVector.

Usage

# S4 method for class 'GRaster,ANY'
zonal(x, z, fun = "mean", probs = 0.5)

Arguments

x

A GRaster for which to calculate summary statistics.

z

A GRaster or GVector used to define zones:

  • If z is a GRaster, then it must be of type integer or factor. Zones will be established based on cells that have the same value in this raster.

  • If z is a GVector, zones will be created for each geometry. If geometries overlap, then the zonal statistics will be calculated for the ones on top. Thus statistics for the zones defined by geometries below these may not represent all the cells covered by that geometry.

fun

Character vector: Name of the function(s) to summarize x with. These can include:

  • "*": All of the functions below.

  • "cv": Sample coefficient of variation (expressed as a proportion of the mean).

  • "cvpop": Population coefficient of variation (expressed as a proportion of the mean).

  • "max" and "min": Highest and lowest values across non-NA cells.

  • "mean" (default): Average.

  • "meanAbs": Mean of absolute values.

  • "median": Median.

  • "quantile": Quantile (see also argument probs).

  • "range": Range.

  • "sd": Sample standard deviation.

  • "sdpop": Population standard deviation.

  • "sum": Sum.

  • "var": Sample variance.

  • "varpop": Population variance.

probs

Numeric: Quantile at which to calculate quantile. Only a single value between 0 and 1 is allowed.

Value

A data.frame or data.table.

Examples

if (grassStarted()) {

# Setup
library(terra)

# Elevation SpatRaster:
madElev <- fastData("madElev")

# Convert a SpatRaster to a GRaster:
elev <- fast(madElev)

### Calculate zonal statistics using a GRaster as zones
#######################################################

# Generate a "zones" GRaster by dividing raster into areas based on
# high/low elevation.
names(elev) # Use this name in app() formula.
fun <- "= if (madElev <200, 0, if (madElev <400, 1, 2))"
zones <- app(elev, fun = fun)

# Calculate zonal statistics using a raster as zones
zonal(elev, zones, fun = "mean")
zonal(elev, zones, fun = "*") # all statistics

# Calculate zonal statistics on multi-layered GRaster
elev2 <- c(elev, log10(elev))
zonal(elev2, zones, fun = c("mean", "sum", "sdpop"))

### Calculate zonal statistics using a GVector as zones
#######################################################

madCoast4 <- fastData("madCoast4")
coast <- fast(madCoast4)

zonal(elev, z = coast, fun = "mean")

}