sample.grid: Sample spatial points by grids

In landmap: Automated Spatial Prediction using Ensemble Machine Learning

Description

Get a subset of a object of class "SpatialPoints" or "SpatialPointsDataFrame" avoiding spatial clustering.

Usage

## S4 method for signature 'SpatialPointsDataFrame'
sample.grid(obj, cell.size, n, bbox, ...)

Arguments

obj	"SpatialPoints*" object,
cell.size	numeric; the cell size of the overlayed "SpatialGridDataFrame" in the form of c(x,y),
n	integer; specifies maximum number points in each grid,
bbox	matrix; the bounding box of output "SpatialPoints" or "SpatialPointsDataFrame"; it is set the same as the obj if missing
...	other optional arguments that can be passed to over

Value

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.

Note

Spatial points are overlaid 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 different combinations of cell.size and n.

Author(s)

Wei Shangguan

References

• Shangguan, W., Hengl, T., de Jesus, J. M., Yuan, H., & Dai, Y. (2017). Mapping the global depth to bedrock for land surface modeling. Journal of Advances in Modeling Earth Systems, 9(1), 65-88. doi: 10.1002/2016MS000686

Examples

library(sp)
data(edgeroi)
profs <- edgeroi[["sites"]]
coordinates(profs) <- ~  LONGDA94 + LATGDA94
proj4string(profs) <- CRS("+proj=longlat +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +no_defs")
## sample SpatialPointsDataFrame:
prof1 <- sample.grid(profs, cell.size = c(0.02,0.02), 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 in percent:
round(length(prof1$subset)/length(profs)*100, 1)

landmap documentation built on Oct. 14, 2021, 5:24 p.m.