Sunday, 25 September 2016

Population Density Comparisons

I grew up in the Highlands of Scotland - well kind of. Perhaps the New York of the Highlands is more accurate (Inverness, obviously). But I am also partly of crofting stock so spent a lot of time in very sparsely populated areas. I lived in Liverpool for 5 years and now live in Sheffield and visit London a lot, and I also like looking at maps and making maps. That's why I was particuarly interested in Steven Kay's population comparison map which compared circular areas centred on London to the populations of Scotland, and also Scotland plus Wales and Northern Ireland.

You can see the original map here

Steven has lots of really interesting, clever maps on his website, many of which do this kind of thing. I also really like his Edinburgh comparison with less populated European nations, as you can see below.

Edinburgh - population about 495,000

Obviously, at one level, such graphics don't really tell us that much beyond the fact that some places are really densely populated, and some aren't - and we all know that. But their power lies in the cognitive trick of the simple spatial overlay. By putting them in the same place and simplifying the shapes to roughly circular ones it makes the comparison more powerful and immediate. And this is why it's both easy to understand and quick to digest. It's also what makes me like it as a simple comparison. There are lots of other examples of this kind of thing online, including one I did in the past looking at the Highland local authority area vs Greater London (which is 32+1 authorities, but also a single political space).

Most definitely not a town planning policy suggestion for Nicola Sturgeon

Talking of the Highlands, the other Steven Kay piece I really liked was his analysis of which parts of Britain and Ireland are closer to Westminster, Dublin, Stavanger, and Oslo respectively. My part of the Highlands is, of course, closer to Stavanger than Westminster. But again, this is just a geographical curiosity and not a reason to suggest we be governed from there! Mind you, their sovereign wealth fund would be nice (current value and nice video - click here).

So, where were we - ah yes... These maps are interesting geographical artifacts but they often have a kind of power that connects with people at different levels - including the emotional. But that's a whole other topic.

For the time being, it's interesting to note the different responses to my tweet of Steven's map. I only noticed it because I went back into the Flickr QGIS feed the other day to change my password after the Yahoo! hack. I liked his map because it made an interesting comparison and even though I know London has 'lots of people' and a good few million more than Scotland, seeing it in this way was quite shocking. For some, that might feel threatening (see notes below) but for others - including me - it's just a comparison which captured my attention as a data/map buff.

Notes: for map nerds, Alan MacEachren's 1995 'How Maps Work' has some good stuff on how maps are imbued with meaning - Part II from p. 213. The section on map connotation (p. 336 onwards) is quite relevant here. For some, the London/Scotland comparison is immediately annoying because of the nation/city comparison (I have a little sympathy here) and for others there is something of an 'incitive connotation' because of the current state of UK politics and particularly the push for Scottish indepdenence vs continued Westminster governance. While I'm on a roll, I'll add that Norway has about £56bn invested in the UK, including ownership of 50% of Meadowhall in Sheffield and 25% of Regent Street in London. So, if you are ever at a loss for words, impress your friends with this knowledge. Tenous links here are that I live in Sheffield and Scotland and Norway have similar populations.

Wednesday, 21 September 2016

DataFest 2016 - what was all that about?

When I'm not writing obscure blog posts about geo things, I work at the University of Sheffield. Half the time I'm in the Department of Urban Studies and Planning and the other half is spent in the Sheffield Methods Institute. The SMI is an interdisciplinary research centre and we have a strong quantitative methods group here - spanning the breadth of social science. A big part of what we do is running the Sheffield Q-Step programme. Say what? Let me demystify... Q-Step is a UK-wide programme - funded by the Nuffield Foundation, HEFCE and the ESRC, with the aim of significantly improving the quantitative skills of social science undergraduates. There are 15 centres across the UK and I happen to be the director of the Sheffield one. That's why we recently hosted DataFest 2016, a quantitative methods summer school for undergraduate students from the north of England (plus two keen interlopers from Bristol!). Too much text already, time for a pic...

DataFest boffins in the lab, mapping Brexit with QGIS

This blog serves as a little bit of a retrospective round up for everyone involved - and others who might be interested or who plan to put something on in future. DataFest ran over 4 days - a couple of weeks before the start of term - and each day was themed, as follows: Skills, Employability, Analysis, Presentation. We had a mix of practical, interactive and lecture-style content, with some great guest speakers, including:

  • Emily Grossman - from the telly, obviously, but also a top scientist and data boffin.
  • Joe Twyman - Head of Political and Social Research for Europe, Middle East and Africa at YouGov, and generally all-round good guy (he bought a round of drinks for EVERYONE at DataFest!).
  • John Burn-Murdoch - from the Financial Times and one of the world's leading data journalists

In addition, we had input from Jackie Carter from the University of Manchester Q-Step team, Julie Scott-Jones from MMU, Chris Forde from Leeds and our good selves at the University of Sheffield. Even so, getting students to come to something called DataFest, of their own accord, during the summer, is a bit of a hard sell. But somehow, some way, they came and for four days we had 30 students unduly excited about data and methods. Hours-wise, it was like a full module for each student so they learned a lot, including dabbling with coding in R, as you can see below.

Not bad at all for someone completely new to R

We even had nice festival-style wristbands to help create a sense that this was a much-more-fun-than-it-sounds rock festival...

The main stage was absolutely jam-packed

The students who came were mainly second and third year undergraduates and all from social science backgrounds. I'd say we pitched it about right and every single person there really got stuck in and learned a lot - so thanks to all for making it a success. I also did a session on dataviz, as you can see below. At the end of the week, each group presented their findings on the question of 'what caused Brexit?' which was a theme for the week - well done to Group 2, who took away the winnings.

A few technical problems, but we won in the end

Really great presentation by Group 2 - top stuff

Finally, we actually managed to use our rooftop terrace because the weather was amazing all week. This provided a nice venue for eating the piles of pizza delivered during the week and for the final DataFest 'graduation' shot - you can see some of the people who attended below with their certificates.

Thanks guys, good luck for the future

As a bonus, when we were coming out of the computer lab one day, we bumped into some friendly University of Sheffield robots, so I'll leave you with this. They made DataFest 2016 that little bit more interesting.


Acknowledgements: the images here were mostly captured by our marketing and PR guru Sophie Hawley, and the original set-up was done by viral content whiz Hazel Moss. SMI Manager Ruth Bartles decided that 'DataFest' was catchier than 'Quantitative Methods Summer School' and also got all the logistics sorted. Dominos did the pizza... Simon Gallacher and Hannah Broad from our funders (The Nuffield Foundation) also visited on the last day, which was very nice of them.

Saturday, 3 September 2016

SIMD 2016: Concentration and Contrasts

The 2016 version of the Scottish Index of Multiple Deprivation was released this week. It's very similar to indices used elsewhere in the UK and other parts of the world. The interactive mapping is great, so I'm not going to do anything on that. Instead, I looked at areas where there are contrasts or concentrations relating to the most and least deprived deciles. With a relative deprivation measure, some places always have to be at the bottom or top, but it's the location, level of spatial clustering, proximity and total number that I was interested in exploring. Here are some maps, starting with Glasgow and then going on a tour round the country. Red areas are in the most deprived 10% of Scotland and blue areas are in the 10% least deprived.

This is probably the bleakest map, in terms of concentrated deprivation

The famous Drumchapel/Bearsden cross-boundary contrast visible here

A bit more mixed towards the south east of Glagsgow's urban area

Alness and Invergordon - some of the more 'hidden' areas on most SIMD maps

Ayr is very notable for its north/south deprivation split

Edinburgh is often contrasted with Glasgow - and you can see why

Again, a somewhat mixed pattern in Falkirk and nearby

Hamilton and Motherwell are also quite mixed in a 'most-least' sense

Inverness - persistent pockets at both ends of the spectrum

A little bit of Fife - which is a bit split in this view

I did another 20 or so maps, in addition to the ones above. They can be seen on a separate Google Drive page if you are interested.

These are all in high-resolution - feel free to use them

I'm not planning to do any more SIMD mapping as there are enough other people looking at it. I just wanted to explore a little bit in relation to how the most and least deprived locations were spread across Scotland. Clearly, very little has changed (and I wouldn't have expected it to) but there have been some recent reports relating to the suburbanisation of poverty in Scotland, including this Conversation piece by Nick Bailey and Jonathan Minton.

Finally, a little SIMD 2016 map insight for you. According to my analysis, there are 31 data zones in the most deprived decile which have a neighbouring data zone in the least deprived decile. Conversely, there are 26 data zones in the least deprived decile with a neighbour in the most deprived decile. In a lot of these, the buildings in neighbouring areas are some way from each other, but in some examples (see below) neighbouring streets are in opposite deciles.

Some neighbouring 'most-least' areas in SIMD 2016

Notes: when you rank places some will always be at the top and some at the bottom, obviously. All other things being equal, however, we might not expect to see such large concentrations of deprivation in single locations. But we know that things are not equal and history and geography have an important role to play in the formation and persistence of these patterns. We can easily blame the politicians of today or those of the past, but I don't think it's that simple. These patterns have persisted for decades and in some cases even longer. For a really good guide to the SIMD2016, read this introduction from the Scottish Government. 

Mapping: I've coloured entire data zones but added in building outlines. Why? Well, the SIMD relates not only to household attributes (such as income) but also to area characteristics (e.g. crime) so the wider environment is important. I wanted to strike a kind of compromise here in relation to what's displayed. Also, the place names are Ordnance Survey open data so the hierarchy in terms of capitalisation and font size is taken directly from the original data. I used QGIS for the mapping. The building outlines are quite generalised so you can't pick out individual houses - this was a deliberate choice as I want to avoid giving the impression that this data says anything about individual people - it's about areas. For reference, there are a total of 6,976 data zones in Scotland.