focal | R Documentation |

Calculate focal ("moving window") values for each cell.

## S4 method for signature 'SpatRaster' focal(x, w=3, fun="sum", ..., na.policy="all", fillvalue=NA, expand=FALSE, silent=TRUE, filename="", overwrite=FALSE, wopt=list())

`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 numeric vector (one or multiple numbers). For example mean, modal, min or max |

`...` |
additional arguments passed to |

`na.policy` |
character. Can be used to determine the cells of |

`fillvalue` |
numeric. The value of the cells in the virtual rows and columns outside of the raster |

`expand` |
logical. If |

`silent` |
logical. If |

`filename` |
character. Output filename |

`overwrite` |
logical. If |

`wopt` |
additional arguments for writing files as in |

`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, for example, the minimum or maximum value for a non-rectangular area.

The "mean" function is a special case, as zero weights are ignored automatically.

The "sum" function returns `NA`

if all focal cells are `NA`

and `na.rm=TRUE`

. R would normally return a zero in these cases. See the difference between `focal(x, fun=sum, na.rm=TRUE`

and `focal(x, fun=\(i) sum(i, na.rm=TRUE))`

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`

, `focal3D`

, `focalCor`

, `focalReg`

, `focalCpp`

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, c(.25, .5, .75), ...), 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) ## illustrating the effect of different ## combinations of na.rm and na.policy v <- vect(system.file("ex/lux.shp", package="terra")) r <- rast(system.file("ex/elev.tif", package="terra")) r[45:50, 45:50] <- NA # also try "mean" or "min" f <- "sum" # na.rm=FALSE plot(focal(r, 5, f) , fun=lines(v)) # na.rm=TRUE plot(focal(r, 5, f, na.rm=TRUE), fun=lines(v)) # only change cells that are NA plot(focal(r, 5, f, na.policy="only", na.rm=TRUE), fun=lines(v)) # do not change cells that are NA plot(focal(r, 5, f, na.policy="omit", na.rm=TRUE), fun=lines(v)) # does not do anything # focal(r, 5, f, na.policy="only", na.rm=FALSE)

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