terra (version 1.8-80)

extract: Extract values from a SpatRaster

Description

Extract values from a SpatRaster for a set of locations. The locations can be a SpatVector (points, lines, polygons), a data.frame or 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).

Usage

# 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), small=TRUE,
	layer=NULL, bind=FALSE, raw=FALSE, search_radius=0, ...)
# 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, raw=FALSE)
# S4 method for SpatVector,SpatVector
extract(x, y, count=FALSE)

Value

data.frame, matrix or SpatVector

See Also

values, zonal, extractAlong, extractRange, rapp

Examples

r <- rast(ncols=5, nrows=5, xmin=0, xmax=5, ymin=0, ymax=5)
values(r) <- 1:25
xy <- cbind(lon=c(0.5,2.5), lat=c(0.5,2.5))
p <- vect(xy, crs="+proj=longlat +datum=WGS84")

extract(r, xy)
extract(r, p)

r[1,]
r[5]
r[,5]

r[c(0:2, 99:101)]

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)

p <- vect(xy)
g <- geom(p)
g

extract(r, p)

x <- r + 10
extract(x, p)

i <- cellFromXY(r, xy)
x[i]
r[i]

y <- c(x,x*2,x*3)
y[i]

## extract with a polygon
f <- system.file("ex/lux.shp", package="terra")
v <- vect(f)
v <- v[1:2,]

rf <- system.file("ex/elev.tif", package="terra")
x <- rast(rf)
extract(x, v, mean, na.rm=TRUE)

z <- rast(v, resolution=.1, names="test")
values(z) <- 1:ncell(z)
e <- extract(z, v, ID=TRUE)
e
tapply(e[,2], e[,1], mean, na.rm=TRUE)

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)