README.md

2015-08-05 UPDATE I got an official response from the Maritime Safety Office that included the official shapefile! I added that GeoJSON to this gist

---

So, I managed to determine that NIMA is directly associated with the NGIA and I found a GitHub org for NGIA: https://github.com/ngageoint?page=1

There's an iOS app repo there - https://github.com/ngageoint/anti-piracy-iOS-app which had a CSV file: https://raw.githubusercontent.com/ngageoint/anti-piracy-iOS-app/master/Asam/subregions.csv

That CSV file is a set of "spatial lines" for framing the sub-regions. I had to modify the subregions (I put the modified file in this gist) to remove duplicate IDs.

The R script in this gist will convert the CSV tile to a SpatialPolygonsDataFrame and also uses the geojsonio package to make a geojson file of the SPDF (which is also in the repo).

Thank you to everyone who went on the hunt! It's really weird this shapefile wasn't in any catalog.

The reason for this treasure hunt will become evident on September 19th! #rrrr

makepolys.R

library(sp)
library(stringr)

dat <- readLines("subregions.csv")

SpatialPolygons(lapply(dat, function(x) {

  region <- str_split_fixed(x, ",", 2)[,1]
  poly_pts <- as.numeric(str_split(str_split_fixed(x, ",", 2)[,2], ",")[[1]])
  poly_mat <- matrix(c(poly_pts, poly_pts[1], poly_pts[2]), ncol=2, byrow=TRUE)
  tmp <- poly_mat[,2]
  poly_mat[,2] <- poly_mat[,1]
  poly_mat[,1] <- tmp
  Polygons(list(Polygon(poly_mat)), ID=region)
  
}), proj4string=CRS("+proj=longlat")) -> subr

subr_dat <- data.frame(id=sapply(subr@polygons, function(x) { slot(x, "ID") }),
             stringsAsFactors=FALSE)
rownames(subr_dat) <- subr_dat$id

subr <- SpatialPolygonsDataFrame(subr, subr_dat)

plot(subr)

library(geojsonio)
geojson_write(subr, geometry="polygon", file="subregions.geojson")

official_subregions.geojson

subregions.csv

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96a,42.083305359,129.567108154,41.515213013,124.297668457,41.537452698,113.226295471,41.546016693,99.000000000,50.000000000,99.000000000,50.000000000,102.750000000,56.336849213,129.539199829,67.800003052,178.000000000,74.000000000,178.000000000,74.000000000,180.000000000,59.141044617,180.000000000,53.000000000,170.000000000,50.000000000,170.000000000,42.500000000,155.000000000,40.830001831,140.750000000,42.150001526,130.210006714,42.148853302,130.175079346,42.083305359,129.567108154
96b,59.136230469,-180.000000000,74.036087036,-180.000000000,74.017883301,-168.000000000,66.500000000,-168.000000000,59.136230469,-180.000000000
97,40.830001831,140.750000000,42.500000000,155.000000000,50.000000000,170.000000000,45.000000000,170.000000000,25.000000000,170.000000000,25.000000000,150.000000000,23.500000000,150.000000000,23.500000000,130.000000000,21.500000000,130.000000000,21.500000000,123.500000000,33.000000000,124.310005188,33.000000000,128.000000000,34.166000366,131.000000000,35.099998474,135.500000000,36.000000000,138.000000000,39.000000000,140.500000000,40.830001831,140.750000000

subregions.geojson

I was mentioned on this from twitter, what's the hoopla all about? These subregions don't make a ton of sense without context, but sortof remind me of FAA regions: