focal: Focal values
In terra: Spatial Data Analysis

Description Usage Arguments Details Value See Also Examples

Calculate focal ("moving window") values for the neighborhood of focal cells using a matrix of weights, perhaps in combination with a function.

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## S4 method for signature 'SpatRaster'
focal(x, w=3, fun="sum", na.rm=TRUE, na.only=FALSE, 
		fillvalue=NA, expand=FALSE, filename="", ...)

`x`	SpatRaster
`w`	window. The window can be defined as one (for a square) or two numbers (row, col); or with an odd-sized weights matrix. See Details.
`fun`	function that takes multiple numbers, and returns a single number. For example mean, modal, min or max. It should also accept a `na.rm` argument, either as actual argument or through use of `...`
`na.rm`	logical. Should missing values be removed?
`na.only`	logical. Should only missing values in `x` be changed?
`fillvalue`	numeric. The value of the cells in the virtual rows and columns outside of the raster
`expand`	logical. If `TRUE` The value of the cells in the virtual rows and columns outside of the raster are set to be the same as the value on the border
`filename`	character. Output filename
`...`	additional arguments for writing files as in `writeRaster`

focal

The window used must have odd dimensions. If you need even sides, you can use a matrix and add a column or row with weights of zero.

Window values are typically 0 or 1, or a value between 0 and 1 if you are using a rectangular area and/or the "sum" function. They can also be NA; these are ignored in the computation. That can be useful to compute the mean, min, or max value for a non-rectangular area.

Example weight matrices

Laplacian filter: filter=matrix(c(0,1,0,1,-4,1,0,1,0), nrow=3)

Sobel filters (for edge detection): fx=matrix(c(-1,-2,-1,0,0,0,1,2,1), nrow=3) fy=matrix(c(1,0,-1,2,0,-2,1,0,-1), nrow=3)

SpatRaster

focalMat, focalValues

r <- rast(ncols=10, nrows=10, ext(0, 10, 0, 10))
values(r) <- 1:ncell(r)

#f <- focal(r, w=3, fun=function(x, ...) quantile(x, .25, ...), na.rm=TRUE) 

f <- focal(r, w=3, fun="mean") 

# the following two statements are equivalent:
a <- focal(r, w=matrix(1/9, nc=3, nr=3))
b <- focal(r, w=3, fun=mean, na.rm=FALSE)

# but this is different
d <- focal(r, w=3, fun=mean, na.rm=TRUE)