The Population of China

In a few weeks I will be travelling to China for a conference, where I'm co-presenting a paper on regional inequalities in China and the EU. This has meant I've had to get hold of lots of Chinese datasets, some of which I have produced maps from - so I thought I'd post one or two here, along with some facts and figures. I should point out that most of the data I've been using has come from the National Bureau of Statistics of China website. 

Higher resolution version

In this 3D map I've just extruded the surface using population density data at a very local level. This required a reasonable amount of computing power but the effect is simply to emphasise the significant West/East split in population within China. This geographical division has been the topic of discussion for a long time and in relation to a number of areas but is generally referred to as the Hu Huanyong line (also sometimes the Hu line, Heihe-Tengchong Line or Aihui-Tengchong Line), after the Chinese population geographer of the same name. Strangely enough, there is a Facebook page dedicated to the Hu line. The line divides China roughly into two parts. In 1935 when Hu first identified the split, the West had 57% of the area and 4% of the population. Today, the East has 94% of the population of China, but only 43% of the area. You can see how this looks in the map below... 

I'm still working on my parts of the presentation but am really fascinated by the facts and figures emerging from the 2010 Chinese census and data for different regions of China. China accounts for almost exactly 20% of the world population and both Beijing and Shanghai (i.e. the provinces) have 20 million or more people. I still need to learn a lot more about China, Chinese data and regional development there generally but my work so far suggests that patterns of regional inequality - while different in absolute terms - are often strikingly similar to patterns of regional inequality in Europe. A good example of this is in Jiangsu province, to the north of Shanghai.

Citations: Center for International Earth Science Information Network - CIESIN - Columbia University, International Food Policy Research Institute - IFPRI, The World Bank, and Centro Internacional de Agricultura Tropical - CIAT. 2011. Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): Population Density Grid. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://dx.doi.org/10.7927/H4R20Z93. Accessed 10 June 2012.

Balk, D.L., U. Deichmann, G. Yetman, F. Pozzi, S. I. Hay, and A. Nelson. 2006. Determining Global Population Distribution: Methods, Applications and Data. Advances in Parasitology 62:119-156. http://dx.doi.org/10.1016/S0065-308X(05)62004-0.

P.S. Thanks are due to Chunhua Liu for her insights here!

Red Road Demolition

A couple of years ago I blogged on the Red Road Flats in Glasgow and their imminent destruction. It wasn't quite as imminent as I thought but it now appears that next Sunday, 10th June 2012 153-213 Petershill Drive will be demolished. As someone with an interest in planning, urbanism, architecture and Glasgow this is a significant event because it represents the end of an era, and in particular the end of the great public high-rise housing experiment that Glasgow embraced. 

153-213 Petershill Drive

The delay in getting to this point is related to the process of moving the asbestos from the buildings, which you can see in this fascinating time-lapse video...

The demolition story is documented on Safedem's Red Road Demolition website and the demolition itself can be viewed live there next Sunday. I'm sure they'll also have lots of video coverage of the event soon after, as they normally do. You can find more details about the original project and architect on these pages.

For me, the most interesting and important aspect of Red Road are the stories told by people who lived there, which are captured on the Red Road Flats website.

Unemployment in Europe (via Google)

Despite recent headlines about data capture, Google remains an excellent source of (or gateway to) information on socio-demographic data. For example, if you type in 'population' followed by a country name, such as 'mexico' then this is what you'll get...

If you do this with any country you'll get the latest results plus a little graph which you can then click on and explore further. Similarly, if you type in 'eu unemployment' you will see a little chart showing EU unemployment - currently 10.2% for March 2012 - and how it has changed over time. If you click on the small chart you'll then see data for Europe and be able to add in data for other EU nations by clicking the boxes to the left. You can even embed this in a web page, as you can see below...

Apart from being convenient and accurate, this is also a very useful analytical tool when you need quick comparisons, like in the example below where I've compared Spain, the EU, Germany and Austria. As you can see the time-series data does not always extend as far back as we'd like but it is a great way to get your head round what is happening in different places without much effort at all. You'll notice in the embedded graphs that if you hover over a line it should tell you the data value for that point.

I've now changed the criteria in the chart so that it only includes unemployment for those aged less than 25 - and I've added in the UK too. This makes pretty grim reading for the EU, and Spain in particular...

This method also works for lots of other kinds of data. For example, if you type in 'us gdp' you'll see the data for the US but also have the option to add in lots of other comparators. One of the most interesting comparisons is looking at GDP over time, as you can see below.

I'm going to a conference in China at the end of June, hence my interest in national comparisons. This kind of thing has of course been covered extensively by Hans Rosling, but not many people know that it is fully integrated into Google's basic functionality.

Bikes in Delft

Not a lot of data analysis or research been done on my part recently. That's because I've been on the road a bit, including attending the Regional Studies Association international conference in Delft. While I was in Delft I was not only amazed by the sheer volume of bikes but also by the way in which bikes are given their own space. I knew about this in advance but it was quite amazing to see it in action, as the short video shows. The video, by the way, was taken on my phone on a slightly windy day at the lovely TU Delft campus.

The number of bikes at Delft station was also staggering, though you can't really even begin to get the scale of it from the picture below...

While I was in Delft I gave a paper on housing market search, based on some Rightmove data. It seemed to go down quite well so hopefully during the summer I'll have time to finish the work and submit it for publication...

How did I manage to do a post without a map? I'm sure I'll rectify this next time.

The Population of the United Kingdom

Partly inspired by a global analysis of population by latitude and longitude and partly intrigued by the latest population estimates for small areas, I've been looking at the population of the United Kingdom in more detail recently. According to the latest small area estimates (for mid-2010) the total population of the country is 62.3 million. The 2011 Census results are not out yet (release schedule here) but this figure should be pretty close to the actual number from the Census. I've been looking at where people live according to different north/south cut-offs. The series of maps below looks at (roughly) how many people live south of a) the River Thames, b) Birmingham, c) Manchester, d) Newcastle and e) Edinburgh... [click an image to see it full screen]

About a quarter live south of Thames

About half live south of Birmingham

 

About two thirds live south of Manchester

Nine out of ten live south of Newcastle

Over 93% live south of Edinburgh

This is not all that mind-blowing really but I was quite surprised that for the UK about half the population live south of Birmingham. The cut-off lines are slightly fuzzy because the data are based on super output areas and data zones (and local authorities for cities) but the figures are pretty accurate. 

In terms of distribution within the United Kingdom (as it still is for the time being!), 83.9% live in England, 8.4% in Scotland, 4.8% in Wales and 2.9% in Northern Ireland. There are ten times as many people in England as there are in Scotland. Or, to look at it another way, you could easily fit the population of Scotland, Wales and Northern Ireland south of London (though I'm sure they might complain).

On a more serious data-related point, I'm still baffled as to why, for example, the US and China can get some early Census results out so quickly whereas we have to wait until July 2012 for the first releases. It will be interesting to see what the final figures are.

London's 100 Poorest Areas

The theme for this post follows on from some work I did recently which looked at the increasing level of deprivation in Outer London, as reported in the Guardian a couple of weeks ago - see also the maps on the Guardian datablog. It's true that housing market pressures (among other things) are helping to push poverty away from Inner London but the majority of London's poorest are still within the inner city, and Tower Hamlets, Hackney and Newham in particular. In order to provide a clearer picture of where exactly the very poorest (most deprived) areas are, I produced a map and animation of London's 100 most deprived areas. 

Animated version

The results are not at all surprising. Of the 100 most deprived LSOAs in London, according to the 2010 Indices of Deprivation, the Borough with the most areas is Tower Hamlets (18), followed by Hackney (17), Newham (13), Haringey (12) and Brent (10). Deprivation is increasing in Outer London relative to the past and I was particularly taken today by the news that Newham Council were looking to re-house poorer residents in Stoke (more than 150 miles away). That's taking the suburbanisation of poverty a bit far! 

Some work I did with Ed Ferrari last year looked at residential mobility patterns amongst the richest and poorest sectors of the population in England. What we found surprised us at the time. Our analysis showed that it was often the poorest areas which were associated with the longest residential moves. We didn't have enough fine-grained data to make more of this but it was an interesting insight into what might be happening more broadly.

Taking the 100 most deprived locations is of course arbitrary but the point here is that despite debates about whether 'the poor' should live in 'rich areas' the fact is that many of the poorest people living in London are in areas which in recent years have changed considerably so that they are now experiencing very high demand, inflated rents and severe socio-economic inequalities. This represents an intensification of existing processes rather than something entirely new but it does mean that policy makers need to think carefully about what to do about it...

Blog spring clean

I've decided to give my blog a little spring clean by changing some of the fonts and headings and adding a new header because I was getting tired of it. At the same time, I've been checking out my Google analytics stats for the blog - an extract is shown below for a recent period in early March 2012...

Not everything I post on here is directly related to my academic research (and some isn't really at all) but the value of blogging for academics is very clear to me, for three main reasons. 

1. As someone who produces a lot of visuals (usually maps) in my work, the printed page is not always a good medium for publishing because of the costs associated with colour printing and the limited pages you are assigned within a journal paper. Basically, it's much easier and more efficient to publish spatial visualisations here; 

2. Since I began blogging I've been contacted by countless researchers and students from all parts of the world either seeking to share their knowlegdge, borrow some of mine or just simply to say they are working on similar things too. Given that what I work on can be quite 'niche', this has been a really useful development; 

3. By putting some of my work on here I'm able to make connections with the outside world in a way that is not possible with journal publications - since they're usually locked behind a paywall and they are normally published 18 months or more from when they were written. The immediacy of blogging is hard to beat (even if it does allow a lot of unstructured, unmoderated content to appear!) and it's also quite therapeutic.

It does take a time and effort to keep it going but most of what I put on here is directly related to my ongoing research and represents a kind of 'snippet view' of what I'm working on at any given time or just an insight into what I find of interest.