Sample points on or in (sets of) spatial features. By default, returns a pre-specified number of points that is equal to size (if type = "random") or an approximation of size (for other sampling types). spatstat methods are interfaced and do not use the size argument.

st_sample(x, size, ...)

# S3 method for sf
st_sample(x, size, ...)

# S3 method for sfc
st_sample(x, size, ..., type = "random", exact = TRUE)

# S3 method for sfg
st_sample(x, size, ...)

Arguments

x

object of class sf or sfc

size

sample size(s) requested; either total size, or a numeric vector with sample sizes for each feature geometry. When sampling polygons, the returned sampling size may differ from the requested size, as the bounding box is sampled, and sampled points intersecting the polygon are returned.

...

passed on to sample for multipoint sampling, or to spatstat functions for spatstat sampling types (see details)

type

character; indicates the spatial sampling type; one of random, hexagonal (triangular really), regular, or one of the spatstat methods such as Thomas for calling spatstat::rThomas (see Details).

exact

logical; should the length of output be exactly the same as specified by size? TRUE by default. Only applies to polygons, and when type = "random".

Value

an sfc object containing the sampled POINT geometries

Details

The function is vectorised: it samples size points across all geometries in the object if size is a single number, or the specified number of points in each feature if size is a vector of integers equal in length to the geometry of x.

if x has dimension 2 (polygons) and geographical coordinates (long/lat), uniform random sampling on the sphere is applied, see e.g. http://mathworld.wolfram.com/SpherePointPicking.html

For regular or hexagonal sampling of polygons, the resulting size is only an approximation.

As parameter called offset can be passed to control ("fix") regular or hexagonal sampling: for polygons a length 2 numeric vector (by default: a random point from st_bbox(x)); for lines use a number like runif(1).

Sampling methods from package spatstat are interfaced (see examples), and need their own parameters to be set. For instance, to use spatstat::rThomas(), set type = "Thomas".

Examples

nc = st_read(system.file("shape/nc.shp", package="sf"))
#> Reading layer `nc' from data source `/tmp/Rtmp6L49NN/temp_libpath64c667a0cdba/sf/shape/nc.shp' using driver `ESRI Shapefile' #> Simple feature collection with 100 features and 14 fields #> geometry type: MULTIPOLYGON #> dimension: XY #> bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965 #> CRS: 4267
p1 = st_sample(nc[1:3, ], 6)
#> although coordinates are longitude/latitude, st_relate_pattern assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
p2 = st_sample(nc[1:3, ], 1:3)
#> although coordinates are longitude/latitude, st_relate_pattern assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_relate_pattern assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_relate_pattern assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_relate_pattern assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_relate_pattern assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_relate_pattern assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_relate_pattern assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_relate_pattern assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
#> although coordinates are longitude/latitude, st_intersects assumes that they are planar
plot(st_geometry(nc)[1:3])
plot(p1, add = TRUE)
plot(p2, add = TRUE, pch = 2)
x = st_sfc(st_polygon(list(rbind(c(0,0),c(90,0),c(90,90),c(0,90),c(0,0)))), crs = st_crs(4326)) plot(x, axes = TRUE, graticule = TRUE)
if (sf_extSoftVersion()["proj.4"] >= "4.9.0") plot(p <- st_sample(x, 1000), add = TRUE) x2 = st_transform(st_segmentize(x, 1e4), st_crs("+proj=ortho +lat_0=30 +lon_0=45")) g = st_transform(st_graticule(), st_crs("+proj=ortho +lat_0=30 +lon_0=45")) plot(x2, graticule = g)
if (sf_extSoftVersion()["proj.4"] >= "4.9.0") { p2 = st_transform(p, st_crs("+proj=ortho +lat_0=30 +lon_0=45")) plot(p2, add = TRUE) } x = st_sfc(st_polygon(list(rbind(c(0,0),c(90,0),c(90,10),c(0,90),c(0,0))))) # NOT long/lat: plot(x)
p_exact = st_sample(x, 1000, exact = TRUE) p_not_exact = st_sample(x, 1000, exact = FALSE) length(p_exact); length(p_not_exact)
#> [1] 1000
#> [1] 974
plot(st_sample(x, 1000), add = TRUE)
x = st_sfc(st_polygon(list(rbind(c(-180,-90),c(180,-90),c(180,90),c(-180,90),c(-180,-90)))), crs=st_crs(4326)) if (sf_extSoftVersion()["proj.4"] >= "4.9.0") { p = st_sample(x, 1000) st_sample(p, 3) } # hexagonal: sfc = st_sfc(st_polygon(list(rbind(c(0,0), c(1,0), c(1,1), c(0,0))))) plot(sfc)
h = st_sample(sfc, 100, type = "hexagonal") h1 = st_sample(sfc, 100, type = "hexagonal") plot(h, add = TRUE)
plot(h1, col = 'red', add = TRUE)
c(length(h), length(h1)) # approximate!
#> [1] 95 105
pt = st_multipoint(matrix(1:20,,2)) ls = st_sfc(st_linestring(rbind(c(0,0),c(0,1))), st_linestring(rbind(c(0,0),c(.1,0))), st_linestring(rbind(c(0,1),c(.1,1))), st_linestring(rbind(c(2,2),c(2,2.00001)))) st_sample(ls, 80)
#> Geometry set for 4 features (with 1 geometry empty) #> geometry type: MULTIPOINT #> dimension: XY #> bbox: xmin: 0 ymin: 0 xmax: 0.09485929 ymax: 1 #> CRS: NA
#> MULTIPOINT ((0 0.9131502), (0 0.6170275), (0 0....
#> MULTIPOINT ((0.08146043 0), (0.02502268 0), (0....
#> MULTIPOINT ((0.07894482 1), (0.07237983 1), (0....
#> MULTIPOINT EMPTY
plot(st_sample(ls, 80))
# spatstat example: if (require(spatstat)) { x <- sf::st_sfc(sf::st_polygon(list(rbind(c(0, 0), c(10, 0), c(10, 10), c(0, 0))))) # for spatstat::rThomas(), set type = "Thomas": pts <- st_sample(x, kappa = 1, mu = 10, scale = 0.1, type = "Thomas") }