extract.RdExtract values from a SpatRaster for a set of locations. The locations can be a SpatVector (points, lines, polygons), a matrix with (x, y) or (longitude, latitude -- in that order!) coordinates, or a vector with cell numbers.
When argument y is a SpatVector the first column has the ID (record number) of the SpatVector used (unless you set ID=FALSE).
Alternatively, you can use zonal after using rasterize with a SpatVector (this may be more efficient in some cases).
# S4 method for SpatRaster,SpatVector
extract(x, y, fun=NULL, method="simple", cells=FALSE, xy=FALSE,
ID=TRUE, weights=FALSE, exact=FALSE, touches=is.lines(y),
layer=NULL, bind=FALSE, raw=FALSE, ...)
# S4 method for SpatRaster,SpatExtent
extract(x, y, cells=FALSE, xy=FALSE)
# S4 method for SpatRaster,matrix
extract(x, y, cells=FALSE, method="simple")
# S4 method for SpatRaster,numeric
extract(x, y, xy=FALSE)
# S4 method for SpatVector,SpatVector
extract(x, y)SpatRaster or SpatVector of polygons
SpatVector (points, lines, or polygons). Alternatively, for points, a 2-column matrix or data.frame (x, y) or (lon, lat). Or a vector with cell numbers
function to summarize the data by geometry. You can use fun=table to tabulate raster values for each line or polygon geometry. If weights=TRUE or exact=TRUE only mean, sum, min, max and table are accepted)
character. method for extracting values with points ("simple" or "bilinear"). With "simple" values for the cell a point falls in are returned. With "bilinear" the returned values are interpolated from the values of the four nearest raster cells
logical. If TRUE the cell numbers are also returned, unless fun is not NULL. Also see cells
logical. If TRUE the coordinates of the cells are also returned, unless fun is not NULL. Also see xyFromCell
logical. Should an ID column be added? If so, the first column returned has the IDs (record numbers) of input SpatVector y
logical. If TRUE and y has polygons, the approximate fraction of each cell that is covered is returned as well, for example to compute a weighted mean
logical. If TRUE and y has polygons, the exact fraction of each cell that is covered is returned as well, for example to compute a weighted mean
logical. If TRUE, values for all cells touched by lines or polygons are extracted, not just those on the line render path, or whose center point is within the polygon. Not relevant for points; and always considered TRUE when weights=TRUE or exact=TRUE
character or numeric to select the layer to extract from for each geometry. If layer is a character it can be a name in y or a vector of layer names. If it is numeric, it must be integer values between 1 and nlyr(x)
logical. If TRUE, a SpatVector is returned consisting of the input SpatVector y and the cbind-ed extracted values
logical. If TRUE, a matrix is returned with the "raw" numeric cell values. If FALSE, a data.frame is returned and the cell values are transformed to factor, logical, or integer values, where appropriate
additional arguments to fun if y is a SpatVector. For example na.rm=TRUE. Or arguments passed to the SpatRaster,SpatVector method if y is a matrix (such as the method and cells arguments)
data.frame, matrix or SpatVector
r <- rast(ncols=5, nrows=5, xmin=0, xmax=5, ymin=0, ymax=5)
values(r) <- 1:25
xy <- rbind(c(0.5,0.5), c(2.5,2.5))
p <- vect(xy, crs="+proj=longlat +datum=WGS84")
extract(r, xy)
#> lyr.1
#> 1 21
#> 2 13
extract(r, p)
#> ID lyr.1
#> 1 1 21
#> 2 2 13
r[1,]
#> lyr.1
#> 1 1
#> 2 2
#> 3 3
#> 4 4
#> 5 5
r[5]
#> lyr.1
#> 1 5
r[,5]
#> lyr.1
#> 1 5
#> 2 10
#> 3 15
#> 4 20
#> 5 25
r[c(0:2, 99:101)]
#> lyr.1
#> 1 1
#> 2 2
#> 3 NA
#> 4 NA
#> 5 NA
f <- system.file("ex/meuse.tif", package="terra")
r <- rast(f)
xy <- cbind(179000, 330000)
xy <- rbind(xy-100, xy, xy+1000)
extract(r, xy)
#> test
#> 1 378
#> 2 251
#> 3 208
p <- vect(xy)
g <- geom(p)
g
#> geom part x y hole
#> [1,] 1 1 178900 329900 0
#> [2,] 2 1 179000 330000 0
#> [3,] 3 1 180000 331000 0
extract(r, p)
#> ID test
#> 1 1 378
#> 2 2 251
#> 3 3 208
x <- r + 10
extract(x, p)
#> ID test
#> 1 1 388
#> 2 2 261
#> 3 3 218
i <- cellFromXY(r, xy)
x[i]
#> test
#> 1 388
#> 2 261
#> 3 218
r[i]
#> test
#> 1 378
#> 2 251
#> 3 208
y <- c(x,x*2,x*3)
y[i]
#> test test test
#> 1 388 776 1164
#> 2 261 522 783
#> 3 218 436 654
## extract with a polygon
f <- system.file("ex/lux.shp", package="terra")
v <- vect(f)
v <- v[1:2,]
z <- rast(v, resolution=.1, names="test")
values(z) <- 1:ncell(z)
rf <- system.file("ex/elev.tif", package="terra")
x <- rast(rf)
extract(x, v, mean, na.rm=TRUE)
#> ID elevation
#> 1 1 467.1052
#> 2 2 333.8629
e <- extract(z, v, ID=TRUE)
e
#> ID test
#> 1 1 2
#> 2 1 3
#> 3 1 6
#> 4 1 7
#> 5 1 8
#> 6 2 13
#> 7 2 17
#> 8 2 18
#> 9 2 19
tapply(e[,2], e[,1], mean, na.rm=TRUE)
#> 1 2
#> 5.20 16.75
x <- c(z, z*2, z/3)
names(x) <- letters[1:3]
e <- extract(x, v, ID=TRUE)
de <- data.frame(e)
aggregate(de[,2:4], de[,1,drop=FALSE], mean)
#> ID a b c
#> 1 1 5.20 10.4 1.733333
#> 2 2 16.75 33.5 5.583333