# spsample

##### sample point locations in (or on) a spatial object

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).

##### Note

If an Polygon-class object has zero area (i.e. is a line), samples on this line element are returned. If the area is very close to zero, the algorithm taken here (generating points in a square area, selecting those inside the polygon) may be very resource intensive. When numbers of points per polygon are small and type="random", the number searched for is inflated to ensure hits, and the points returned sampled among these.

##### 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

##### 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)
```

*Documentation reproduced from package sp, version 0.9-92, License: GPL (>= 2)*