Zonal statistics
zonal.Rd
Compute zonal statistics, that is summarize values of a SpatRaster for each "zone" defined by another SpatRaster, or by a SpatVector with polygon geometry.
If fun
is a true R function
, the <SpatRaster,SpatRaster> method may fail when using very large SpatRasters, except for the functions ("mean", "min", "max", "sum", "isNA", and "notNA").
You can also summarize values of a SpatVector for each polygon (zone) defined by another SpatVector.
Usage
# S4 method for class 'SpatRaster,SpatRaster'
zonal(x, z, fun="mean", ..., w=NULL, wide=TRUE,
as.raster=FALSE, filename="", overwrite=FALSE, wopt=list())
# S4 method for class 'SpatRaster,SpatVector'
zonal(x, z, fun="mean", na.rm=FALSE, w=NULL, weights=FALSE,
exact=FALSE, touches=FALSE, small=TRUE, as.raster=FALSE,
as.polygons=FALSE, wide=TRUE, filename="", wopt=list())
# S4 method for class 'SpatVector,SpatVector'
zonal(x, z, fun=mean, ..., weighted=FALSE, as.polygons=FALSE)
Arguments
- x
SpatRaster or SpatVector
- z
SpatRaster with cell-values representing zones or a SpatVector with each polygon geometry representing a zone.
z
can have multiple layers to define intersecting zones- fun
function to be applied to summarize the values by zone. Either as character: "mean", "min", "max", "sum", "isNA", and "notNA" and, for relatively small SpatRasters, a proper function
- ...
additional arguments passed to fun, such as
na.rm=TRUE
- w
SpatRaster with weights. Should have a single-layer with non-negative values
- wide
logical. Should the values returned in a wide format? For the
SpatRaster, SpatRaster
method this only affects the results whennlyr(z) == 2
. For theSpatRaster, SpatVector
method this only affects the results whenfun=table
- as.raster
logical. If
TRUE
, a SpatRaster is returned with the zonal statistic for each zone- filename
character. Output filename (ignored if
as.raster=FALSE
- overwrite
logical. If
TRUE
,filename
is overwritten- wopt
list with additional arguments for writing files as in
writeRaster
- weights
logical. If
TRUE
andy
has polygons, the approximate fraction of each cell that is covered is returned as well, for example to compute a weighted mean- exact
logical. If
TRUE
andy
has polygons, the exact fraction of each cell that is covered is returned as well, for example to compute a weighted mean- touches
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 consideredTRUE
whenweights=TRUE
orexact=TRUE
- small
logical. If
TRUE
, values for all cells in touched polygons are extracted if none of the cells center points is within the polygon; even iftouches=FALSE
- weighted
logical. If
TRUE
, a weighted.mean is computed andfun
is ignored. Weights are based on the length of the lines or the area of the polygons inx
that intersect withz
. This argument is ignored ofx
is a SpatVector or points- as.polygons
logical. Should the zonal statistics be combined with the geometry of
z
?- na.rm
logical. If
TRUE
,NA
s are removed
Examples
### SpatRaster, SpatRaster
r <- rast(ncols=10, nrows=10)
values(r) <- 1:ncell(r)
z <- rast(r)
values(z) <- rep(c(1:2, NA, 3:4), each=20)
names(z) <- "zone"
zonal(r, z, "sum", na.rm=TRUE)
#> zone lyr.1
#> 1 1 210
#> 2 2 610
#> 3 3 1410
#> 4 4 1810
# with weights
w <- init(r, "col")
zonal(r, z, w=w, "mean", na.rm=TRUE)
#> zone lyr.1
#> 1 1 12
#> 2 2 32
#> 3 3 72
#> 4 4 92
# multiple layers
r <- rast(system.file("ex/logo.tif", package = "terra"))
# zonal layer
z <- rast(r, 1)
names(z) <- "zone"
values(z) <- rep(c(1:2, NA, c(3:4)), each=ncell(r)/5, length.out=ncell(r))
zonal(r, z, "mean", na.rm = TRUE)
#> zone red green blue
#> 1 1 197.9486 198.0103 193.5556
#> 2 2 173.2219 176.7717 185.2585
#> 3 3 168.2952 172.6232 184.6939
#> 4 4 193.5859 197.0019 206.5717
# raster of zonal values
zr <- zonal(r, z, "mean", na.rm = TRUE, as.raster=TRUE)
### SpatRaster, SpatVector
x <- rast(ncol=2,nrow=2, vals=1:4, xmin=0, xmax=1, ymin=0, ymax=1, crs="+proj=utm +zone=1")
p <- as.polygons(x)
pp <- shift(p, .2)
r <- disagg(x, 4)
zonal(r, p)
#> lyr.1
#> 1 1
#> 2 2
#> 3 3
#> 4 4
zonal(r, p, sum)
#> lyr.1
#> 1 16
#> 2 32
#> 3 48
#> 4 64
zonal(x, pp, exact=TRUE)
#> lyr.1
#> 1 1.4
#> 2 2.0
#> 3 3.4
#> 4 4.0
zonal(c(x, x*10), pp, w=x)
#> lyr.1 lyr.1
#> 1 1 10
#> 2 2 20
#> 3 3 30
#> 4 4 40
### SpatVector, SpatVector
f <- system.file("ex/lux.shp", package="terra")
v <- vect(f)[,c(2,4)]
p <- spatSample(v, 100)
values(p) <- data.frame(b2=1:100, ssep1=100:1)
zonal(p, v, mean)
#> zone b2 ssep1
#> 1 1 45.60000 55.40000
#> 2 2 45.66667 55.33333
#> 3 3 49.00000 52.00000
#> 4 4 66.66667 34.33333
#> 5 5 50.66667 50.33333
#> 6 6 59.33333 41.66667
#> 7 7 59.16667 41.83333
#> 8 8 48.88889 52.11111
#> 9 9 55.40000 45.60000
#> 10 10 49.42857 51.57143
#> 11 11 40.85714 60.14286
#> 12 12 48.16667 52.83333