spatSample() randomly locates points across a GRaster or GVector. It can return a GVector, the coordinates, values associated with the points, or all of these. If you want to generate a raster with randomly-sampled cells, see sampleRast().
Usage
# S4 method for class 'GRaster'
spatSample(
x,
size,
as.points = FALSE,
values = TRUE,
cats = TRUE,
xy = FALSE,
strata = NULL,
byStratum = FALSE,
zlim = NULL,
seed = NULL,
verbose = FALSE
)
# S4 method for class 'GVector'
spatSample(
x,
size,
as.points = FALSE,
values = TRUE,
xy = FALSE,
byStratum = FALSE,
zlim = NULL,
seed = NULL
)Arguments
- x
A
GRasterorGVector.- size
Numeric value > 0: Number of points to create.
- as.points
Logical: If
FALSE(default), the output is adata.frameordata.table. IfTRUE, the output is a "points"GVector.- values
Logical: If
TRUE(default), values of theGRasterat points are returned.- cats
Logical: If
TRUE(default) and theGRasteris categorical, then return the category label of each cell. Ifvaluesis alsoTRUE, then the cell value will also be returned.- xy
Logical: If
TRUE, return the longitude and latitude of each point. Default isFALSE.- strata
Either
NULL(default), or aGVectordefining strata. If supplied, thesizeargument will be interpreted as number of points to place per geometry instrata. Note that using strata can dramatically slow the process.- byStratum
Logical: If
FALSE(default), thensizenumber of points will be placed within the entire area delineated bystrata. IfTRUE, thensizepoints will be placed within each subgeometry ofstrata.- zlim
Either
NULL(default), or a vector of two numbers defining the lower and upper altitudinal bounds of coordinates. This cannot be combined withvalues = TRUEorcats = TRUE.- seed
Either
NULL(default) or an integer: Random number seed. If this isNULL, the a seed will be set randomly. Values will be rounded to the nearest integer.- verbose
Logical: If
TRUE, display progress. Default isFALSE.
See also
sampleRast(), terra::spatSample(), tool v.random in GRASS (see grassHelp("v.random"))
Examples
if (grassStarted()) {
# Setup
library(sf)
library(terra)
# Example data
madElev <- fastData("madElev") # raster
# Convert to GRasters and GVectors
elev <- fast(madElev)
### spatSample()
# Random points as data.frame or data.table:
randVals <- spatSample(elev, size = 20, values = TRUE)
randVals
# Random points as a points GVector:
randPoints <- spatSample(elev, size = 20, as.points = TRUE)
randPoints
plot(elev)
plot(randPoints, add = TRUE)
# Random points in a select area:
madCoast <- fastData("madCoast4") # vector
coast <- fast(madCoast)
ant <- coast[coast$NAME_4 == "Antanambe"] # subset
restrictedPoints <- spatSample(elev, size = 20, as.points = TRUE,
strata = ant)
plot(elev)
plot(ant, add = TRUE)
plot(restrictedPoints, add = TRUE) # note 20 points for entire geometry
# Random points, one set per subgeometry:
stratifiedPoints <- spatSample(elev, size = 20, as.points = TRUE,
strata = ant, byStratum = TRUE)
plot(elev)
plot(ant, add = TRUE)
plot(stratifiedPoints, pch = 21, bg = "red", add = TRUE) # note 20 points per subgeometry
# Random categories:
madCover <- fastData("madCover") # raster
cover <- fast(madCover)
randCover <- spatSample(cover, size = 20, values = TRUE,
cat = TRUE, xy = TRUE)
randCover
### sampleRast()
# Random cells in non-NA cells:
rand <- sampleRast(elev, 10000)
plot(rand)
nonnacell(rand)
# Use custom values for the mask:
randCustomMask <- sampleRast(elev, 10000, maskvalues = 1:20)
plot(randCustomMask)
# Force selected values to a custom value:
randCustomUpdate <- sampleRast(elev, 10000, updatevalue = 7)
plot(randCustomUpdate)
# Custom values for mask and set selected cells to custom value:
randAll <- sampleRast(elev, 10000, maskvalues = 1:20, updatevalue = 7)
plot(randAll)
}
