How Big is Beijing?

I was in Beijing recently for a conference and was astonished by the scale and intensity of the city. I found it a little difficult to get my head round the sheer size of Beijing so I thought I'd do a little comparison between Beijing and London. 'Beijing' here refers to the municipality of Beijing (i.e. the Province-level city) and 'London' refers to the 32 Boroughs + City of London which make up Greater London. I've illustrated this in the graphic below, which maps Beijing and Greater London at the same scale. As you can see, Beijing is much bigger - both in terms of area and population.

Click here to see the full size version.

Key facts: Beijing is, area-wise, more than ten times bigger than Greater London. It has a population of 19.6 million, compared to about 7.8 million for Greater London. This comparison is of course not really fair because Beijing includes several large rural areas. A better comparison is to look at the Inner Districts of Beijing since these cover an area quite similar to Greater London (1,377 vs 1,572 sq. km. respectively). In this comparison Beijing has 11.7 million people compared to London's 7.8 million. No matter how you look at it, though, Beijing is 'big'! If you're interested in another comparison, take a look at Oliver O'Brien's comparison of Tokyo and London...

Why I Like 3D Maps

I do quite a bit of spatial analysis and mapping in my academic research, and some of it ends up on this blog. Over the past few years I've done quite a few 3D* maps - most recently one of population density in China. A comment by map-guru James Cheshire made me think about the 3D issue, hence this post, which attempts to say a little more about why I like using the third dimension, as it were. Also, there's not much about this stuff online at present. The two images below show population density in Europe at NUTS3 level, with a colour scale running from red (high density) to blue (low density). Click the images to enlarge.

*N.B. Data for some parts of Italy, Germany, and the UK are missing, 

but that doesn't matter for now - this is just an example.

The reason I like the addition of the third dimension with this kind of dataset is that you can tell more about the differences between areas within the same statistical category. Essentially, it adds an additional dimension of information that you can not observe from the conventional 2D map above. This is particularly true of the most high density areas in the first map. There is of course an issue here about the relative size of areas and how this might change the population density of different places but that is a different matter since I'm not in control of NUTS3 definitions! For more on this kind of thing I'd recommend looking at Stan Openshaw's work and for more on the utility (or futility?) of choropleths generally Tobler (1973) is an excellent starting point. Gale and Halperin (1982) is also worth a look.

If we assume that the main purpose of a choropleth map is to present and discover spatial patterns then there is sometimes a strong case for using the vertical dimension and extruding polygons using a z-variable (I do this in ArcScene, in case anybody is interested). However, there are some complications and I don't think it is always appropriate to go 3D. For example, depending upon the spatial structure of your data extruded polygons in one area can obscure those in another. There is also the issue of the different size of areas and the way these might have an impact upon the level of extrusion - i.e. if we used 1km cells for the European population density map it would look rather different in 3D - though this is possibly another artifact of the modifiable areal unit problem, as described by Openshaw. I've patched together three different examples from my blog in the image below, just for comparison. Another option would be to follow the example of Ben Hennig and produce population-weighted cartograms.

When I produce these 3D maps (or visualisations) I'm not trying to create a geographically precise rendering of space but rather I'm attempting to draw attention to variations in a dataset in a way which 2D maps can only do to a limited degree. They are abstractions and simplifications but in terms of understanding the world I find it can be an improvement. There is a little bit about it in this Environment and Planning B paper I wrote but I plan to write more about this in the near future (the'near future' in geological terms of course). 

*Also known as 2.5D in the GIS world, but I'll put that to one side for now...

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.