Here's a different approach. It works by:
- Converting the world map from the
maps
package into a SpatialLines
object with a geographical (lat-long) CRS.
- Projecting the
SpatialLines
map into the Plate Carée (aka Equidistant Cylindrical) projection centered on the Prime Meridian. (This projection is very similar to a geographical mapping).
- Cutting in two segments that would otherwise be clipped by left and right edges of the map. (This is done using topological functions from the
rgeos
package.)
- Reprojecting to a Plate Carée projection centered on the desired meridian (
lon_0
in terminology taken from the PROJ_4
program used by spTransform()
in the rgdal
package).
- Identifying (and removing) any remaining 'streaks'. I automated this by searching for lines that cross g.e. two of three widely separated meridians. (This also uses topological functions from the
rgeos
package.)
This is obviously a lot of work, but leaves one with maps that are minimally truncated, and can be easily reprojected using spTransform()
. To overlay these on top of raster images with base
or lattice
graphics, I first reproject the rasters, also using spTransform()
. If you need them, grid lines and labels can likewise be projected to match the SpatialLines
map.
library(sp)
library(maps)
library(maptools) ## map2SpatialLines(), pruneMap()
library(rgdal) ## CRS(), spTransform()
library(rgeos) ## readWKT(), gIntersects(), gBuffer(), gDifference()
## Convert a "maps" map to a "SpatialLines" map
makeSLmap <- function() {
llCRS <- CRS("+proj=longlat +ellps=WGS84")
wrld <- map("world", interior = FALSE, plot=FALSE,
xlim = c(-179, 179), ylim = c(-89, 89))
wrld_p <- pruneMap(wrld, xlim = c(-179, 179))
map2SpatialLines(wrld_p, proj4string = llCRS)
}
## Clip SpatialLines neatly along the antipodal meridian
sliceAtAntipodes <- function(SLmap, lon_0) {
## Preliminaries
long_180 <- (lon_0 %% 360) - 180
llCRS <- CRS("+proj=longlat +ellps=WGS84") ## CRS of 'maps' objects
eqcCRS <- CRS("+proj=eqc")
## Reproject the map into Equidistant Cylindrical/Plate Caree projection
SLmap <- spTransform(SLmap, eqcCRS)
## Make a narrow SpatialPolygon along the meridian opposite lon_0
L <- Lines(Line(cbind(long_180, c(-89, 89))), ID="cutter")
SL <- SpatialLines(list(L), proj4string = llCRS)
SP <- gBuffer(spTransform(SL, eqcCRS), 10, byid = TRUE)
## Use it to clip any SpatialLines segments that it crosses
ii <- which(gIntersects(SLmap, SP, byid=TRUE))
# Replace offending lines with split versions
# (but skip when there are no intersections (as, e.g., when lon_0 = 0))
if(length(ii)) {
SPii <- gDifference(SLmap[ii], SP, byid=TRUE)
SLmap <- rbind(SLmap[-ii], SPii)
}
return(SLmap)
}
## re-center, and clean up remaining streaks
recenterAndClean <- function(SLmap, lon_0) {
llCRS <- CRS("+proj=longlat +ellps=WGS84") ## map package's CRS
newCRS <- CRS(paste("+proj=eqc +lon_0=", lon_0, sep=""))
## Recenter
SLmap <- spTransform(SLmap, newCRS)
## identify remaining 'scratch-lines' by searching for lines that
## cross 2 of 3 lines of longitude, spaced 120 degrees apart
v1 <-spTransform(readWKT("LINESTRING(-62 -89, -62 89)", p4s=llCRS), newCRS)
v2 <-spTransform(readWKT("LINESTRING(58 -89, 58 89)", p4s=llCRS), newCRS)
v3 <-spTransform(readWKT("LINESTRING(178 -89, 178 89)", p4s=llCRS), newCRS)
ii <- which((gIntersects(v1, SLmap, byid=TRUE) +
gIntersects(v2, SLmap, byid=TRUE) +
gIntersects(v3, SLmap, byid=TRUE)) >= 2)
SLmap[-ii]
}
## Put it all together:
Recenter <- function(lon_0 = -100, grid=FALSE, ...) {
SLmap <- makeSLmap()
SLmap2 <- sliceAtAntipodes(SLmap, lon_0)
recenterAndClean(SLmap2, lon_0)
}
## Try it out
par(mfrow=c(2,2), mar=rep(1, 4))
plot(Recenter(-90), col="grey40"); box() ## Centered on 90w
plot(Recenter(0), col="grey40"); box() ## Centered on prime meridian
plot(Recenter(90), col="grey40"); box() ## Centered on 90e
plot(Recenter(180), col="grey40"); box() ## Centered on International Date Line

maps
package or a high-resolution version "world2Hires" in themapdata
package are already centered on 180 deg. The rest of your code works fine. – user666993sp
and related packages, but don't know anything about convertingsp
'sSpatial*
objects (especially the raster-representing ones) to ggplot... – Josh O'Brien