rasterize.RdTransfer values associated with 'object' type spatial data (points, lines, polygons) to raster cells.
For polygons, values are transferred if the polygon covers the center of a raster cell. For lines, values are transferred to all cells that are touched by a line. You can combine this behaviour by rasterizing polygons as lines first and then as polygons.
If x represents points, each point is assigned to a grid cell. Points that fall on a border between cells are placed in the cell to the right and/or in the cell below. The value of a grid cell is determined by the values associated with the points and function fun.
# S4 method for class 'matrix,Raster'
rasterize(x, y, field, fun='last', background=NA,
mask=FALSE, update=FALSE, updateValue='all', filename="", na.rm=TRUE, ...)
# S4 method for class 'SpatialPoints,Raster'
rasterize(x, y, field, fun='last', background=NA,
mask=FALSE, update=FALSE, updateValue='all', filename="", na.rm=TRUE, ...)
# S4 method for class 'SpatialLines,Raster'
rasterize(x, y, field, fun='last', background=NA,
mask=FALSE, update=FALSE, updateValue='all', filename="", ...)
# S4 method for class 'SpatialPolygons,Raster'
rasterize(x, y, field, fun='last', background=NA,
mask=FALSE, update=FALSE, updateValue='all', filename="",
getCover=FALSE, silent=TRUE, ...)points (a SpatialPoints* object, or a two-column matrix (or data.frame)), SpatialLines*, SpatialPolygons*, or an Extent object
Raster* object
numeric or character. The value(s) to be transferred. This can be a single number, or a vector of numbers that has the same length as the number of spatial features (points, lines, polygons). If x is a Spatial*DataFrame, this can be the column name of the variable to be transferred. If missing, the attribute index is used (i.e. numbers from 1 to the number of features). You can also provide a vector with the same length as the number of spatial features, or a matrix where the number of rows matches the number of spatial features
function or character. To determine what values to assign to cells that are covered by multiple spatial features. You can use functions such as min, max, or mean, or one of the following character values: 'first', 'last', 'count'. The default value is 'last'. In the case of SpatialLines*, 'length' is also allowed (currently for planar coordinate systems only).
If x represents points, fun must accept a na.rm argument, either explicitly or through the ellipses ('dots'). This means that fun=length fails, but fun=function(x,...)length(x) works, although it ignores the na.rm argument. To use the na.rm argument you can use a function like this: fun=function(x, na.rm){if (na.rm) length(na.omit(x)) else (length(x)}, or use a function that removes NA values in all cases, like this function to compute the number of unique values per grid cell "richness": fun=function(x, ...) {length(unique(na.omit(x)))} . If you want to count the number of points in each grid cell, you can use fun='count' or fun=function(x,...){length(x)}.
You can also pass multiple functions using a statement like fun=function(x, ...) c(length(x),mean(x)), in which case the returned object is a RasterBrick (multiple layers).
numeric. Value to put in the cells that are not covered by any of the features of x. Default is NA
logical. If TRUE the values of the input Raster object are 'masked' by the spatial features of x. That is, cells that spatially overlap with the spatial features retain their values, the other cells become NA. Default is FALSE. This option cannot be used when update=TRUE
logical. If TRUE, the values of the Raster* object are updated for the cells that overlap the spatial features of x. Default is FALSE. Cannot be used when mask=TRUE
numeric (normally an integer), or character. Only relevant when update=TRUE. Select, by their values, the cells to be updated with the values of the spatial features. Valid character values are 'all', 'NA', and '!NA'. Default is 'all'
character. Output filename (optional)
If TRUE, NA values are removed if fun honors the na.rm argument
logical. If TRUE, the fraction of each grid cell that is covered by the polygons is returned (and the values of field, fun, mask, and update are ignored. The fraction covered is estimated by dividing each cell into 100 subcells and determining presence/absence of the polygon in the center of each subcell
Logical. If TRUE, feedback on the polygon count is suppressed. Default is FALSE
Additional arguments for file writing as for writeRaster
RasterLayer or RasterBrick
###############################
# rasterize points
###############################
r <- raster(ncols=36, nrows=18)
n <- 1000
set.seed(123)
x <- runif(n) * 360 - 180
y <- runif(n) * 180 - 90
xy <- cbind(x, y)
# get the (last) indices
r0 <- rasterize(xy, r)
# presence/absensce (NA) (is there a point or not?)
r1 <- rasterize(xy, r, field=1)
# how many points?
r2 <- rasterize(xy, r, fun=function(x,...)length(x))
vals <- runif(n)
# sum of the values associated with the points
r3 <- rasterize(xy, r, vals, fun=sum)
# with a SpatialPointsDataFrame
vals <- 1:n
p <- data.frame(xy, name=vals)
coordinates(p) <- ~x+y
r <- rasterize(p, r, 'name', fun=min)
#r2 <- rasterize(p, r, 'name', fun=max)
#plot(r, r2, cex=0.5)
###############################
# rasterize lines
###############################
cds1 <- rbind(c(-180,-20), c(-140,55), c(10, 0), c(-140,-60))
cds2 <- rbind(c(-10,0), c(140,60), c(160,0), c(140,-55))
cds3 <- rbind(c(-125,0), c(0,60), c(40,5), c(15,-45))
lines <- spLines(cds1, cds2, cds3)
r <- raster(ncols=90, nrows=45)
r <- rasterize(lines, r)
if (FALSE) { # \dontrun{
plot(r)
plot(lines, add=TRUE)
r <- rasterize(lines, r, fun='count')
plot(r)
values(r) <- 1:ncell(r)
r <- rasterize(lines, r, mask=TRUE)
plot(r)
values(r) <- 1
r[lines] <- 10
plot(r)
} # }
###############################
# rasterize polygons
###############################
p1 <- rbind(c(-180,-20), c(-140,55), c(10, 0), c(-140,-60), c(-180,-20))
hole <- rbind(c(-150,-20), c(-100,-10), c(-110,20), c(-150,-20))
p1 <- list(p1, hole)
p2 <- rbind(c(-10,0), c(140,60), c(160,0), c(140,-55), c(-10,0))
p3 <- rbind(c(-125,0), c(0,60), c(40,5), c(15,-45), c(-125,0))
pols <- spPolygons(p1, p2, p3)
r <- raster(ncol=90, nrow=45)
r <- rasterize(pols, r, fun=sum)
if (FALSE) { # \dontrun{
plot(r)
plot(pols, add=T)
# add a polygon
p5 <- rbind(c(-180,10), c(0,90), c(40,90), c(145,-10),
c(-25, -15), c(-180,0), c(-180,10))
addpoly <- SpatialPolygons(list(Polygons(list(Polygon(p5)), 1)))
addpoly <- as(addpoly, "SpatialPolygonsDataFrame")
addpoly@data[1,1] <- 10
r2 <- rasterize(addpoly, r, field=1, update=TRUE, updateValue="NA")
plot(r2)
plot(pols, border="blue", lwd=2, add=TRUE)
plot(addpoly, add=TRUE, border="red", lwd=2)
# get the percentage cover of polygons in a cell
r3 <- raster(ncol=36, nrow=18)
r3 <- rasterize(pols, r3, getCover=TRUE)
} # }