mroutley
commented
10 years ago Here's a draft approach:
library(rgdal)
library(sp)
library(rgeos)
# Census tracts -----------------------------------------------------------
if(file.exists("data-raw/gct_000b11a_e.shp")) {
# Nothing to do
} else {
download.file("http://www12.statcan.gc.ca/census-recensement/2011/geo/bound-limit/files-fichiers/gct_000b11a_e.zip", destfile = "data-raw/gct_000a11a_e.zip")
unzip("data-raw/gct_000b11a_e.zip", exdir="data-raw")
}
proj4string=sp::CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=GRS80 +towgs84=0,0,0"))
ct_geo <- rgdal::readOGR(dsn = "data-raw", layer = "gct_000b11a_e")
# Toronto wards -----------------------------------------------------------
if(file.exists("data-raw/VOTING_SUBDIVISION_2010_WGS84.shp")) {
# Nothing to do
} else {
download.file("http://opendata.toronto.ca/gcc/voting_subdivision_2010_wgs84.zip",
destfile = "data-raw/subdivisions_2010.zip")
unzip("data-raw/subdivisions_2010.zip", exdir="data-raw")
}
to_geo <- rgdal::readOGR(dsn = "data-raw", layer = "VOTING_SUBDIVISION_2010_WGS84")
# Harmonize the projections
ct_geo <- spTransform(ct_geo, CRSobj = CRS(proj4string(to_geo)))
# Subset the CTs to just those in Toronto
ct_geo_to <- ct_geo[to_geo,]
Currently using the Toronto_CTs.csv file to filter the census data to Toronto census tracts. Should switch to using sp::over instead.