Population density in Europe

Population density is a subject I've been writing about for a while, so I decided to create a few more renders of European population density using the EU's GHS_POP data, which is freely available. The maps below use 1km x 1km data and the height of the bars represents the number of people living in any one square. The big squares are 50km x 50km (about 30 miles) and are there to provide sense of scale. The highest 1km densities are found in Spain and France, and Madrid, Barcelona and Paris in particular where you get values of more than 50,000. You can read more on that in a previous piece I did on the topic. Anyway, enough words for now - see below for the six different renders I created; I've tried to create a few interesting perspectives here. Scroll below the images for a bit more technical information about the process and the data.

Why do this?

I did these because I find it a useful way of understanding wider patterns and the bird's-eye view gives a nice sense of perspective over a large area. But of course with 3D mapping it's always a bit of a balancing act because turn the map one way and you inevitably obscure something or somewhere of interest to people. Although, in this case, it is more experimental and aesthetic than analytical, which I think is okay sometimes. 

The data for my area look wrong!

This may be the case because after all the quality of any kind of visualisation like this depends upon the data inputs. Anyway, the data come from the EU's Global Human Settlement project and are available for different years. I'm using the 2015 data here, and you can read more about it and get the data yourself at their excellent new download pages - and do read the documentation, which is also great.

Data processing and mapping

I downloaded the entire global 1km dataset and then in QGIS I clipped out an area focusing on Europe and then extracted it as a rendered tif. If that means nothing to you, don't worry! It should be helpful to anyone who wants to replicate this. I then imported the data into Aerialod and spent some time tweaking lots of different settings and I wanted to give Europe a nice hopeful glow effect. 

Should I give away my trade secrets on what settings and colours I used here? Of course I should - see below.

This is a difficult time right now, and I'm always looking for alternatives to doomscrolling, so I hope you find these interesting to look at - I found them interesting to make!

The Most Densely Populated Square Kilometre in 39 European Countries

A few days ago I published a short piece in The Conversation about population density across Europe, based on EU gridded population data. This was really my attempt to see if I could produce some numbers which better reflect the experience of population density across Europe, rather than just the raw arithmetic average. At the end of the piece I added a table with some stats, including the maximum 1km population density for each of the 39 countries I looked at. There wasn't space in the article to tell you where all these places were, so I'm doing it here instead. So, without further ado, here are the most densely populated 1km squares in each of the 39 countries, from Spain to Liechtenstein. Click to enlarge.

I did this quickly so it's a bit rough and ready as far as the maps go - a few labelling blips here and there but you can get the idea. Scrolling through from most dense to least dense does generally seem to make sense visually though you can't always tell what's what because some places have lots of high rises in them and you don't get a sense of that from the aerial photos.

Notes: the data are from 2011, so a little old now. We should also really consider these estimates, for a variety of reasons, but I think they are likely to be close to truth, based on my analysis of similar datasets (e.g. ONS in the UK and GHSL globally). Note that if you download the EU data you'll have to then join it to some kind of geodata (e.g. shapefile) because it's not already done. This can be tricky with about 2 million 1km cells and rows of data. Why are England, Northern Ireland, Scotland and Northern Ireland separate here? That's just the way they published the data. But I found it useful to get a better look at patterns in different parts of the UK.