Wednesday, 13 June 2018

How many people live in the English green belt?

There was a blog post here about the total population living on land in England that is designated as green belt.

I decided to take it down because I wasn't as confident as I wanted to be about my original estimate of 3.5 million and I don't want to spread misinformation. This figure could be correct, but it may not be.

The problem is that it's impossible to know for sure with the data we have available, which is a shame. Perhaps in future we'll move to a position where we can easily answer these questions with better open data.

For now, I am just leaving this here as a note to anyone who might have seen the original post or tweet (also deleted).

Normal service shall resume soon.

15 June 2018


Note
You can find some English green belt shapefiles on this page, though they seem to mostly be historic ones (e.g. 2007-08) unless you click 'Show more' in which case you'll get everything from 2007-08 to 2016-17.

Sunday, 20 May 2018

The Shape of American Democracy, v1.0

The fifth Vice President of the United States, and 9th Governor of Massachusetts - Elbridge Gerry - has not been forgotten. His name lives on in debates about the shapes of political districts and specifically in relation to those very irregularly shaped Congressional Districts we often see in the United States. Thus, gerrymandering remains a hot topic, but it is often difficult to understand without maps. So, in an effort to simplify things, I've created a single graphic that shows the shape of every US Congressional District - or, as I've called it, 'The Shape of American Democracy'. I have put the massive full size version, plus smaller versions, on a dedicated web page, which I may update in due course. Read on for more details about this project.

This is a big version, but you can find a giant version here

What is this?
The graphic above is a single poster that shows all 435 US Congressional Districts of the 115th US Congress, arranged in 15 rows and 29 columns. This is quite convenient, because 15 x 29 is 435, so it allows for a nice, regular layout. The colours (sorry, colors), represent the party representing each district - blue for Democratic, red for Republican. The order of the shapes is also very important. From top left to bottom right, I have arranged the districts in order of their Polsby-Popper score, which is one measure of the compactness of a geographic area, among several. There are others, but I've used this one as I think it provides results that make sense and look right. 

A closer look at the layout
Congressional District table - so you can find them easily

On the right hand side, there is a list, in five columns of 87 rows (5 x 87 = 435, thankfully), which tells you where you can find any Congressional District in the main layout, where I have labelled the rows A to O and the columns 1 to 29. So, if you wanted to find Florida's 18th Congressional District, for example, you would look it up alphabetically on the right, see that it's in N-23 and then look up row N, column 23 to see what it looks like, as shown below. If you look closely, you'll notice that some Congressional Districts are actually whole states. This is because seven states have only one representative: Alaska, Delaware, Montana, North Dakota, South Dakota, Vermont, and Wyoming.


Why do this?
The reason I did this is because I'm interested in the subject and have written about it before. I lived in the US for a short time (OH-3) but I'm not an American and I have no vote. I do have an unhealthy interest in maps and stats, though, as you can see if you look at more of this blog. In previous attempts, I'd done things like make small multiple graphics or animated gifs, but I wasn't satisfied with them. This time I wanted to pack as much useful information into a single graphic as possible, yet I also wanted it to be easy to digest, and The Shape of American Democracy is the result. I'm reasonably happy with it as a first draft, yet almost as soon as I finished, Pennsylvania redrew its districts after the existing ones were struck down by their Supreme Court. I am definitely not doing this to say any single political party is bad or good, or that an irregular shape is necessarily a problem. But by putting them all in one place, where we can also compare and contrast individual districts, I think it gives us a good overview and is a useful conversation starter at the very least.


What does it tell us?
Let's begin with the basics. It tells us that there are 435 Congressional Districts and that some are red and some are blue. By using the Polsby-Popper measure (which I learned about from my colleague Ruth Hamilton), and ordering them like as I have, it also tells us that some areas are much more irregularly-shaped than others. But of course we already knew this information. Where I think a graphic like this adds value is in its ability to pull all this information together into one information set that is, from a cognitive point of view, easier to digest. It provides a kind of at-a-glance summary of US Congressional District irregularity. This is not to say unusual shapes are inherently a bad thing because there may be good reasons for it. Likewise, more regular shapes may not necessarily be a good thing even if, on balance, most people would agree that this is the case. For more on this general topic, I recommend you read Garrett Dash Nelson's piece in Citylab, which asks the question of what a good electoral map would look like.

PA has since changed, but you get the idea

How did I do this?
In brief, I downloaded the latest US Congressional District shapefile from the US Census Bureau website, loaded it up in QGIS and then created an Atlas and then patched it all together in another open source application, called (ahem) GIMP. Creating the Congressional District finder table was a bit more tricky, so for that I used spreadsheets and pivot tables because it was the quickest way I could think of doing it, even if it was a wee bit clunky. I then exported different sizes of the graphic and put it all online in a dedicated single web page.

Click here to download the full size version


Am I saying US Democracy is in bad shape?
I realise the title of the graphic makes it sound that way, but it's not my intention. This is about shapes, and I toyed with the idea of calling it 'The Shapes of American Democracy' but in the end I went with Shape because I thought it sounded better and of course people can make their own minds up about what this might tell them about the state of democracy, if anything. Being from the UK (as a Scot living in England) it would be quite rich for me to criticise anyone else's democracy at present anyway! So, all I'm really saying is that the graphic gives you an impression of the shapes of US Congressional Districts, which form part of the democratic process in the United States, and from that you can make up your own mind about what it all means.


Other things
I originally put this together as a submission for the brilliant Atlas of Design, but it didn't make the cut, so I'm sharing it here instead, and on its own dedicated web page. I made it in January 2018, but then almost straight away the Pennsylvania Congressional Districts were re-drawn, but it still represents the correct information at a moment in time. I could update it if a) I ever find the time or b) someone commissions me to do it. So, that's already two kinds of fails with this project, but I think it is still useful to share it.

That's basically it for now. I haven't been able to obtain the very latest boundaries in the wake of the Pennsylvania re-draw but I might return to this in future if I can to create a version 1.1.


Technical information
When calculating the shapes of Congressional Districts, and their irregularity, there are a number of technical challenges, not least of which is the coastline. What we really want to measure are only those boundaries that can or have been manipulated by people rather than nature. A heavily indented coastline will give a district a very irregular shape, but this is not gerrymandering. So, when I was doing this I used an unclipped shapefile with, essentially, a smoothed coastline. Yet even when you do this you get some anomalies - e.g. Alaska and Hawaii's 2nd District end up on the top row, when really they are just quirks of geography - nobody would claim they were heavily gerrymandered! So this is a limitation but a relatively minor one.

Another thing that you might notice if you look closely is that some Districts might appear to be in the wrong place, based on what they look like. A good example of this is in Florida's 13th Congressional district, which is placed just before Wyoming as the second least irregularly shaped, even though it doesn't look right. But if we look at the portion of the boundary which could actually be modified through gerrymandering, given the coastline and the fact that this is St Petersburg (on a peninsula) it makes more sense. Wyoming does, thankfully, end up in the right place as the least irregular of all the shapes.

FL-13, surely some mistake?

Now it makes more sense - source


Wednesday, 25 April 2018

WALRUS: the Wirral and Liverpool Regional Urban System

On a recent trip to Liverpool I needed an all-day ticket that would let me use public transport across the city. So I bought a couple of day passes for me and a friend, which meant getting a plastic card that can be topped up, kind of like the Oyster Card in London. But in Liverpool it's called the Walrus card. It's not exactly the same as the Oyster, but it is named after a sea creature, though it took us a few moments to figure out why they chose Walrus as the name. But of course we decided it must really stand for Wirral and Liverpool Regional Urban System (surely, yes?) and I therefore had to make an animated gif of commute flows in the WALRUS, so here I am. Watch it multiple times to see the main travel to work patterns, and scroll to the bottom for a slower version. I've tried to get the colours right so you can see the mix of destinations clearly. Liverpool city centre is near the L of Liverpool and I've also labelled some other locations including the airport (Liverpool John Lennon Airport, as it is officially called).

Behold: commuter flows in the WALRUS

Surely the people who came up with Walrus really meant it as a play on the Beatles song plus a play on this urban and regional acronym. After all, there is a history of this kind of thing in the wider area, with SELNEC as 'South East Lancashire, North East Cheshire' probably the most famous example, from the late 1960s to the early 1970s. But no, if I Google it, I get absolutely nothing, as you can see below or try for yourself. Surely somebody already uses this, it seems too obvious. If not, then I will claim partial credit alongside my good friend for creating this backronym.

"WALRUS, you say?"

From the JR James Archive

There are other examples of urban and regional acronyms in the UK and across the world (feel free to suggest more) but I can't think of one that incorporates a nice local reference like this. Although, if they chose Oyster in London because it means the world is your Oyster then the Walrus thing doesn't work so well here ("The World is Your Walrus"!?). Anyway, it did make travel on public transport much more efficient and it also meant I got to revive my series of animated gifs, for an area I know pretty well.


My Walrus card

The other side of my Walrus card

That's really all there is to it for now. Hope to catch you next time I'm in the WALRUS, which really is a regional urban system. If you get the chance, I'd like to hear about other urban and regional acronyms you may have heard of. I'll end this post with another version of the gif at the top of the pages, this time slowed down a bit more.

The WALRUS in slow motion

Tuesday, 27 March 2018

Daytime Population Density

My last blog post on population density was basically just a little extract of some work I've been doing on population density. However, density is not absolute or fixed and it can change significantly throughout the day. A variety of sources suggest that the maximum density per square kilometre in the UK is around 25,000. Yet this only relates to where people live. Spend any time in a busy city centre and you'll see far higher densities than this, so I thought I'd take a look at it. To begin with, here's a map of daytime population density in the southern and eastern part of England.

The maximum density during the day is over 125,000 per sq km

As you can see on the map above, when we look at population density during the day, there are some big differences - the most obvious of which are in central London. Compare this to the picture when we look at residential population density, which is how it is usually reported.

This is also useful, but it's only part of the story

This is not particularly surprising, of course, but it is quite striking how large the differences are. Thanks to the folks at the Centre for Ecology & Hydrology, and an open licence, we can look more closely at daytime population density across the UK, as well as residential density, using 2011 data. This can provide us with a much more nuanced view of population density and help us understand how the population distribution changes during the working day. Outside London, the single square kilometre with the highest workday population is in central Glasgow, with over 60,000 people. A little extract of this, and the equivalent residential population is shown below.

Glasgow has the highest daytime population density in Scotland

Edinburgh has the highest residential density in Scotland

With this data we can then drill down to look at other parts of the UK, and this is what I've done in the rest of this post. I've extracted images for all areas where there are more than 20,000 people present in any single 1km cell during the working day, according to the CEH figures. As you'd expect, it includes the major cities but some of the places that do feature may surprise you and some of the places that don't may also. Only places with a single cell containing 20,000 people or more during the working day are shown.

You'll also notice the connection between density and rail infrastructure if you look closely. It often looks like a cable plugged into individual red squares. The upper figure in each image is the daytime population, with the residential figure in brackets underneath. Each cell is, of course, 1km by 1km. Click on the individual images to enlarge.


Belfast

Birmingham

Brighton

Bristol

Cardiff

Edinburgh

Glasgow

Leeds

Leicester

Liverpool

London - overview 
London - zoomed in


London - Tower Hamlets

London - maximum values

Manchester

Newcastle

Nottingham

Oxford

Reading

Sheffield

That's it for now. I'll return to look at population density in the future, hopefully once I've finished my current overly-ambitious attempt to derive some new-fangled population density measures for the whole of Europe.


Data source: this data is made available under the Open Government Licence. ©NERC (Centre for Ecology & Hydrology). Contains National Statistics data © Crown copyright and database right 2011. Contains data supplied by Natural Environment Research Council.

Reference: Reis, S.; Liska, T.; Steinle, S.; Carnell, E.; Leaver, D.; Roberts, E.; Vieno, M.; Beck, R.; Dragosits, U. (2017). UK Gridded Population 2011 based on Census 2011 and Land Cover Map 2015. NERC Environmental Information Data Centre. https://doi.org/10.5285/0995e94d-6d42-40c1-8ed4-5090d82471e1

Sunday, 28 January 2018

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.