Non-Uniform Population Density in some European Countries

By arthur charpentier

A few months ago, I did mention that France was a country with strong inequalities, especially when you look at higher education, and research teams. Paris has almost 50% of the CNRS researchers, while only 3% of the population lives there.

CNRS, “répartition des chercheurs en SHS” http://t.co/39dcJJBwrF, Paris 47.52% IdF 66.85% (pop 3.39% et 18.18% resp) pic.twitter.com/OsEXiFywPf

— Arthur Charpentier (@freakonometrics) 28 septembre 2015

It looks like Paris is the only city, in France. And I wanted to check that, indeed, France is a country with strong inequalities, when we look at population density.

Using data from sedac.ciesin.columbia.edu, it is possible to get population density on a small granularity level,

> rm(list=ls())
> base=read.table(
+      "/home/charpentier/glp00ag.asc",
+      skip=6)
> X=t(as.matrix(base,ncol=8640))
> X=X[,ncol(X):1]

The scales for latitudes and longitudes can be obtained from the text file,

> #ncols         8640
> #nrows         3432
> #xllcorner     -180
> #yllcorner     -58
> #cellsize      0.0416666666667

Hence, we have

> library(maps)
> world=map(database="world")
> vx=seq(-180,180,length=nrow(X)+1)
> vx=(vx[2:length(vx)]+vx[1:(length(vx)-1)])/2
> vy=seq(-58,85,length=ncol(X)+1)
> vy=(vy[2:length(vy)]+vy[1:(length(vy)-1)])/2

If we plot our density, as in a previous post, on Where People Live,

> I=seq(1,nrow(X),by=10)
> J=seq(1,ncol(X),by=10)
> image(vx[I],vy[J],log(1+X[I,J]),
+ col=rev(heat.colors(101)))
> lines(world[[1]],world[[2]])

we can see that we have a match, between the big population matrix, and polygons of countries.

Consider France, for instance. We can download the contour polygon with higher precision,

> library(rgdal)
> fra=download.file(
"http://biogeo.ucdavis.edu/data/gadm2.8/rds/FRA_adm0.rds",
+ "fr.rds")
> Fra=readRDS("fr.rds")
> n=length([email protected][[1]]@Polygons)
> L=rep(NA,n)
> for(i in 1:n) L[i]=nrow([email protected][[1]]@Polygons[[i]]@coords)
> idx=which.max(L)
> polygon_Fr=
+       [email protected][[1]]@Polygons[[idx]]@coords
> min_poly=apply(polygon_Fr,2,min)
> max_poly=apply(polygon_Fr,2,max)
> idx_i=which((vx>min_poly[1])&(vx> idx_j=which((vy>min_poly[2])&(vy> sub_X=X[idx_i,idx_j]
> image(vx[idx_i],vy[idx_j],
+       log(sub_X+1),col=rev(heat.colors(101)),
+       xlab="",ylab="")
> lines(polygon_Fr)

We are now able to extract information about population for France, only (actually, it is only mainland France, islands are not considered here… to …read more

Source:: r-bloggers.com