Question

I have multiple sets of points (for different years ~20)

I want to generate thiessen polygons for each set of points using r spatial packages.

I know this can be done using GIS but as i want a batch process something in R would be

helpful.

Answer 1

You haven’t given us access to your data, but here’s an example for points representing cities of the world, using an approach described by Carson Farmer on his blog. Hopefully it’ll get you started…

# Carson's Voronoi polygons function
voronoipolygons <- function(x) {
  require(deldir)
  require(sp)
  if (.hasSlot(x, 'coords')) {
    crds <- x@coords  
  } else crds <- x
  z <- deldir(crds[,1], crds[,2])
  w <- tile.list(z)
  polys <- vector(mode='list', length=length(w))
  for (i in seq(along=polys)) {
    pcrds <- cbind(w[[i]]$x, w[[i]]$y)
    pcrds <- rbind(pcrds, pcrds[1,])
    polys[[i]] <- Polygons(list(Polygon(pcrds)), ID=as.character(i))
  }
  SP <- SpatialPolygons(polys)
  voronoi <- SpatialPolygonsDataFrame(SP, data=data.frame(x=crds[,1],
    y=crds[,2], row.names=sapply(slot(SP, 'polygons'), 
    function(x) slot(x, 'ID'))))
}

Example 1: Input is a SpatialPointsDataFrame:

# Read in a point shapefile to be converted to a Voronoi diagram
library(rgdal)
dsn <- system.file("vectors", package = "rgdal")[1]
cities <- readOGR(dsn=dsn, layer="cities")

v <- voronoipolygons(cities)

plot(v)

Example 2: Input is vectors of x, y coordinates:

dat <- data.frame(x=runif(100), y=runif(100))
v2 <- voronoipolygons(dat)
plot(v2)