sp (version 0.9-78)

spsample: sample point locations in (or on) a spatial object

Description

sample point locations within a square area, a grid, a polygon, or on a spatial line, using regular or random sampling methods; the methods used assume that the geometry used is not spherical, so objects should be in planar coordinates

Usage

spsample(x, n, type, ...)
sample.Spatial(x, n, type, bb = bbox(x), offset = runif(nrow(bb)), cellsize, ..., nclusters = 1)
sample.Line(x, n, type, offset = runif(1), proj4string=CRS(as.character(NA)), ...)
sample.Polygon(x, n, type = "random", bb = bbox(x), offset = runif(2), proj4string=CRS(as.character(NA)), iter = 4, ...)
sample.Polygons(x, n, type = "random", bb = bbox(x), offset = runif(2), proj4string=CRS(as.character(NA)), iter = 4, ...)
sample.Sgrid(x, n, type = "random", bb = bbox(x), offset = runif(nrow(bb)), ...)
makegrid(x, n = 10000, nsig = 2, cellsize, offset = rep(0.5, nrow(bb)))

Arguments

x

Spatial object; spsample(x,...) is a generic method for the existing sample.Xxx fumctions

...

optional arguments, passed to the appropriate sample.Xxx functions

n

(approximate) sample size

type

character; "random" for completely spatial random; "regular" for regular (systematically aligned) sampling; "stratified" for stratified random (one single random location in each "cell"); "nonaligned" fo

bb

bounding box of the sampled domain; setting this to a smaller value leads to sub-region sampling

offset

for regular sampling only: the offset (position) of the regular grid; the default for spsample methods is a random location in the unit cell [0,1] x [0,1], leading to a different grid after each call; if this is set to c(0.5,0.5)

cellsize

if missing, a cell size is derived from the sample size n; otherwise, this cell size is used for all sampling methods except "random"

nclusters

Number of clusters (strata) to sample from

proj4string

Object of class "CRS"; holding a valid proj4 string

nsig

for "pretty" coordinates; spsample does not result in pretty grids

iter

default = 4: number of times to try to place sample points in a polygon before giving up and returning NULL - this may occur when trying to hit a small and awkwardly shaped polygon in a large bounding box with a small number of points

Value

• an object of class SpatialPoints-class. The number of points is only guaranteed to equal n when sampling is done in a square box, i.e. (sample.Spatial). Otherwise, the obtained number of points will have expected value n.

  When x is of a class deriving from Spatial-class for which no spsample-methods exists, sampling is done in the bounding box of the object, using spsample.Spatial. An overlay may be necessary to select afterwards.

  Sampling type "nonaligned" is not implemented for line objects.

  Some methods may return NULL if no points could be successfully placed.

  makegrid makes a regular grid, deriving cell size from the number of grid points requested (approximating the number of cells).

References

Chapter 3 in B.D. Ripley, 1981. Spatial Statistics, Wiley

Fibonacci sampling: Alvaro Gonzalez, 2010. Measurement of Areas on a Sphere Using Fibonacci and Latitude-Longitude Lattices. Mathematical Geosciences 42(1), p. 49-64

See Also

overlay-methods, point.in.polygon, sample

Examples

data(meuse.riv)
meuse.sr = SpatialPolygons(list(Polygons(list(Polygon(meuse.riv)), "x")))

plot(meuse.sr)
points(spsample(meuse.sr, n = 1000, "regular"), pch = 3)

plot(meuse.sr)
points(spsample(meuse.sr, n = 1000, "random"), pch = 3)

plot(meuse.sr)
points(spsample(meuse.sr, n = 1000, "stratified"), pch = 3)

plot(meuse.sr)
points(spsample(meuse.sr, n = 1000, "nonaligned"), pch = 3)

plot(meuse.sr)
points(spsample(meuse.sr@polygons[[1]], n = 100, "stratified"), pch = 3, cex=.5)

data(meuse.grid)
gridded(meuse.grid) = ~x+y
image(meuse.grid)
points(spsample(meuse.grid,n=1000,type="random"), pch=3, cex=.5)
image(meuse.grid)
points(spsample(meuse.grid,n=1000,type="stratified"), pch=3, cex=.5)
image(meuse.grid)
points(spsample(meuse.grid,n=1000,type="regular"), pch=3, cex=.5)
image(meuse.grid)
points(spsample(meuse.grid,n=1000,type="nonaligned"), pch=3, cex=.5)

fullgrid(meuse.grid) = TRUE
image(meuse.grid)
points(spsample(meuse.grid,n=1000,type="stratified"), pch=3,cex=.5)