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Install

Install the package

devtools::install_github("AustralianAntarcticDivision/aceecostats")

Regions

Get the regions.

library(aceecostats)
library(sp)
labs <- data.frame(x= c(112406,4488211,-1734264,-4785284), y=c(4271428,-224812,-3958297,-104377), labels=c("Atlantic","Indian", "West Pacific", "East Pacific"))
labs <- SpatialPointsDataFrame(labs[,1:2],labs, proj4string = CRS(proj4string(aes_region)))
plot(aes_region, col = aes_region$colour, border="grey")
text(labs$x, labs$y, labs$labels, cex=0.6)

# latitude zone labels
lat.labs<- function(the.proj="polar"){
  if(the.proj=="latlon"){
    ext <- extent(aes_region_ll)
    text("Polar", x=ext@xmin, y=ext@ymin, xpd=NA, pos=2, cex=0.6)
    text("High latitude", x=ext@xmin, y=ext@ymin*0.8, xpd=NA, pos=2, cex=0.6)
    text("Mid latitude", x=ext@xmin, y=ext@ymin*0.6, xpd=NA, pos=2, cex=0.6)
  }
  if(the.proj=="polar"){
    text(c("Polar", "High latitude", "Mid latitude"), x=c(113064.6,-1017581.1,-3642294), y=c(-1518296,-2285519,-3012363), cex=0.5, col=rgb(0,0,0,0.7))
  }
}
lat.labs()

In unprojected form.

library(aceecostats)
library(raster)
library(sp)
plot(aes_region_ll, col = aes_region_ll$colour, border="grey")
ll_labs <- spTransform(labs, CRS(proj4string(aes_region_ll)))
text(ll_labs$x, ll_labs$y, labels=labs$labels, cex=0.6)
lat.labs("latlon")

Simplified regions

plot(aes_region_simple, col = aes_region_simple$colour, border="grey")
text(labs$x, labs$y, labels=labs$labels, cex=0.6)
lat.labs()

Write to shapefile.

shapefile(aes_region, "my_aes_region.shp")

(Leave your money on the fridge).

Metadata

The data is stored on the map object itself.

knitr::kable(as.data.frame(aes_region))

	ID	BathyClass	SectorName	Zone	Name	Shelf	area_km2	colour
47	1	BanksPlateaus	Atlantic	Polar	Atlantic_Polar_BanksPlateaus	Ocean	501423.64	#7CAE0099
48	2	Continent	Atlantic	Polar	Atlantic_Polar_Continent	Shelf	1084547.95	#7CAE00FF
49	3	Deep	Atlantic	Polar	Atlantic_Polar_Deep	Ocean	19353773.36	#7CAE0099
50	4	BanksPlateaus	Atlantic	Temperate	Atlantic_Temperate_BanksPlateaus	Ocean	2108929.34	#7CAE004D
51	5	Deep	Atlantic	Temperate	Atlantic_Temperate_Deep	Ocean	13562422.11	#7CAE004D
52	6	Continent	EastPacific	Polar	EastPacific_Polar_Continent	Shelf	724857.54	#C77CFFFF
53	7	Deep	EastPacific	Polar	EastPacific_Polar_Deep	Ocean	3241353.36	#C77CFF99
54	8	BanksPlateaus	EastPacific	Temperate	EastPacific_Temperate_BanksPlateaus	Ocean	405139.12	#C77CFF4D
55	9	Deep	EastPacific	Temperate	EastPacific_Temperate_Deep	Ocean	10168793.90	#C77CFF4D
56	10	BanksPlateaus	Indian	Polar	Indian_Polar_BanksPlateaus	Ocean	676845.57	#00BFC499
57	11	Continent	Indian	Polar	Indian_Polar_Continent	Shelf	706453.81	#00BFC4FF
58	12	Deep	Indian	Polar	Indian_Polar_Deep	Ocean	11022311.32	#00BFC499
59	13	BanksPlateaus	Indian	Temperate	Indian_Temperate_BanksPlateaus	Ocean	694668.93	#00BFC44D
60	14	Deep	Indian	Temperate	Indian_Temperate_Deep	Ocean	12373702.76	#00BFC44D
61	15	BanksPlateaus	WestPacific	Polar	WestPacific_Polar_BanksPlateaus	Ocean	32840.05	#F8766D99
62	16	Continent	WestPacific	Polar	WestPacific_Polar_Continent	Shelf	885409.00	#F8766DFF
63	17	Deep	WestPacific	Polar	WestPacific_Polar_Deep	Ocean	8103336.24	#F8766D99
64	18	BanksPlateaus	WestPacific	Temperate	WestPacific_Temperate_BanksPlateaus	Ocean	2552842.08	#F8766D4D
65	19	Deep	WestPacific	Temperate	WestPacific_Temperate_Deep	Ocean	20472658.20	#F8766D4D

Prefer ggplot2?

## TODO fix this code
library(ggplot2)
library(ggpolypath)
tab <- fortify(aes_region)

## Regions defined for each Polygons

zcols <- as.data.frame(aes_region)[, c("colour", "Name", "ID")]
tab$Name <- zcols$Name[factor(tab$id)]
ggplot(tab) + aes(x = long, y = lat, group = group, fill = Name) + scale_fill_manual(values = setNames(zcols$colour, zcols$Name)) + 
geom_polypath() + theme(legend.text=element_text(size=6)) + guides(position = "bottom")