sample.grid {GSIF}  R Documentation 
Get a subset of a object of class "SpatialPoints"
or "SpatialPointsDataFrame"
avoiding spatial clustering.
## S4 method for signature 'SpatialPoints' sample.grid(obj, cell.size, n, bbox, ...) ## S4 method for signature 'SpatialPointsDataFrame' sample.grid(obj, cell.size, n, bbox, ...)
obj 

cell.size 
numeric; the cell size of the overlayed 
n 
integer; specifies maximum number points in each grid 
bbox 
matrix; the bounding box of output 
... 
other optional arguments that can be passed to 
Returns a list of two objects: (1) an object of type "SpatialPoints"
or "SpatialPointsDataFrame"
that contains a subset of the obj, and (2) resulting grid.
Spatial points are overlayed with spatial grids with a specified cell size and then get a subset from each grid with a specified number at most. If one grid has less points than the specified number, all the points are taken. If one grid has more points than the specified number, only this number of points are taken by sample
. This function can be used when there are too much point observations to be handled, especially for spatially clustered observations. The total number of sampled points are determined by cell.size
and n
together. You will get fewer the sampled points when cell.size
is larger, or/and when n
is smaller. Similar sample sizes can be achieved by differen combination of cell.size
and n
.
Wei Shangguan
library(sp) data(isis) profs < isis[["sites"]] coordinates(profs) < ~ LONWGS84 + LATWGS84 proj4string(profs) < CRS("+proj=longlat +datum=WGS84") ## sample SpatialPointsDataFrame: #bbox < matrix(c(180, 90, 180, 90), nrow=2) prof1 < sample.grid(profs, cell.size = c(5,5), n = 1) l0 < list("sp.points", profs, pch=1, col="red") l1 < list("sp.points", prof1$subset, pch="+", col="black", cex=1.2) spplot(prof1$grid, scales=list(draw=TRUE), col.regions="grey", sp.layout=list(l0, l1)) ## Subsampling ratio: round(length(prof1$subset)/length(profs)*100, 1)