res,missing-method | R Documentation |
Spatial resolution of a GRaster
:
res()
: 2-dimensional resolution (x and y).
res3d()
: 3-dimensional resolution (z, y, and z).
xres()
, yres()
, and zres()
: East-west resolution, north-south resolution, and top-bottom resolution.
## S4 method for signature 'missing'
res(x)
## S4 method for signature 'GRegion'
res(x)
## S4 method for signature 'missing'
xres(x)
## S4 method for signature 'GRegion'
xres(x)
## S4 method for signature 'missing'
yres(x)
## S4 method for signature 'GRegion'
yres(x)
## S4 method for signature 'missing'
zres(x)
## S4 method for signature 'GRegion'
zres(x)
## S4 method for signature 'missing'
res3d(x)
## S4 method for signature 'GRegion'
res3d(x)
x |
A |
A numeric vector. For both res()
and res3d()
, the first value is the length of cells in the x-direction and the second the length of cells in the y-direction. For res3d()
the third value is height of a voxel (the z-direction). xres()
, yres()
, and zres()
each return a single value.
terra::res()
if (grassStarted()) {
# Setup
library(terra)
# Example data
madElev <- fastData("madElev")
madForest2000 <- fastData("madForest2000")
# Convert SpatRasters to GRasters
elev <- fast(madElev)
forest <- fast(madForest2000)
### GRaster properties
# plotting
plot(elev)
# dimensions
dim(elev) # rows, columns, depths, layers
nrow(elev) # rows
ncol(elev) # columns
ndepth(elev) # depths
nlyr(elev) # layers
res(elev) # resolution (2D)
res3d(elev) # resolution (3D)
zres(elev) # vertical resolution
xres(elev) # vertical resolution
yres(elev) # vertical resolution
zres(elev) # vertical resolution (NA because this is a 2D GRaster)
# cell counts
ncell(elev) # cells
ncell3d(elev) # cells (3D rasters only)
# number of NA and non-NA cells
nacell(elev)
nonnacell(elev)
# topology
topology(elev) # number of dimensions
is.2d(elev) # is it 2-dimensional?
is.3d(elev) # is it 3-dimensional?
minmax(elev) # min/max values
# "names" of the object
names(elev)
# coordinate reference system
crs(elev)
st_crs(elev)
coordRef(elev)
# extent (bounding box)
ext(elev)
# vertical extent (not defined for this raster)
zext(elev)
# data type
datatype(elev) # fasterRaster type
datatype(elev, "GRASS") # GRASS type
datatype(elev, "terra") # terra type
datatype(elev, "GDAL") # GDAL type
is.integer(elev)
is.float(elev)
is.double(elev)
is.factor(elev)
# convert data type
as.int(elev) # integer; note that "elev" is already of type "integer"
as.float(elev) # floating-precision
as.doub(elev) # double-precision
# assigning
pie <- elev
pie[] <- pi # assign all cells to the value of pi
pie
# concatenating multiple GRasters
rasts <- c(elev, forest)
rasts
# subsetting
rasts[[1]]
rasts[["madForest2000"]]
# replacing
rasts[[2]] <- 2 * forest
rasts
# adding layers
rasts[[3]] <- elev > 500 # add a layer
rasts <- c(rasts, sqrt(elev)) # add another
add(rasts) <- ln(elev)
rasts
# names
names(rasts)
names(rasts) <- c("elev_meters", "2_x_forest", "high_elevation", "sqrt_elev", "ln_elev")
rasts
# remove a layer
rasts[["2_x_forest"]] <- NULL
rasts
# number of layers
nlyr(rasts)
# correlation and covariance matrices
madLANDSAT <- fastData("madLANDSAT")
landsat <- fast(madLANDSAT) # projects matrix
layerCor(landsat) # correlation
layerCor(landsat, fun = 'cov') # covariance
}
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