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Drawing maps of the polar regions can be done using square spatial maps. A small example says more than a thousand words:

xlim = c(-180,180) ylim = c(60,90) # Some fake grid data dat_grid = expand.grid(x = xlim[1]:xlim[2], y = ylim[1]:ylim[2]) dat_grid$value = runif(nrow(dat_grid)) # Polygons data dum = map(xlim = c(-180,180), ylim = c(60,90), plot = FALSE) ant_ggplot = data.frame(dum[c("x","y")]) ant_ggplot$value = mean(dat_grid$value) # Make the square spatial map ggplot(aes(x = x, y = y, fill = value), data = dat_grid) + geom_tile() + geom_path(data = ant_ggplot)

The final call to ggplot results in the following picture:

A much more natural way of plotting this polar centered data would be to use polar coordinates. This is supported by ggplot2 through the coord_polar() command. In code (with great help from Charlotte Wickham) this results in:

res <- 1 # 1 degree resolution x_cell_lim <- c(180, -180) + c(1, -1) * res/2 y_cell_lim <- c(90, 60) + c(1, -1) * res/2 ggplot(aes(x = x, y = y, fill = value), data = dat_grid) + geom_tile() + geom_path(data = ant_ggplot) + scale_fill_gradient(low = "white", high = muted("red")) + coord_polar(start = -pi/2, expand = FALSE) + scale_y_continuous("") + scale_x_continuous("") + xlim(x_cell_lim) + ylim(y_cell_lim) + opts(axis.ticks = theme_blank(), axis.text.y = theme_blank(), axis.title.x = theme_blank(), axis.title.y = theme_blank(), panel.border = theme_blank())

Note that I use theme_blank() many times to get rid of certain elements of the plot (rectangle around the plot, y-axis etc). In addition, the calls to x_lim and y_lim are necessary. Charlotte Wickham explains (direct quote from ggplot2 mailing list): *The little additions to the limits make sure the entire cell in plotted without any gaps. It might make more sense to have: x_cell_lim <- c(180, -180) + c(1, +1) * res/2, assuming cells centered at 180 and -180 longitude are the same*. The above call to ggplot resuls in the following plot:

Note that the grid cells are nicely scaled towards the north pole. In my opinion this is a much more effective plot for showing polar oriented data.

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