From mega-regions to mega commutes: US commuting working paper

My previous post provided some images from a recent piece of work I did on mapping tract-to-tract commuting patterns in the contiguous United States. This post provides a bit more background and extracts from a working paper, plus some of the original map outputs from the project - which are different in style (kind of a night time view). The focus is also more on mega commutes and mega-regions (think Gottmann's 'megalopolis'). I also provide a bit more detail on the method and data.

A constellation of cities in the Midwest

Being a member of the Regional Studies Association for a good few years now, I've followed various debates about regions, city-regions and mega-regions - including the very interesting work on mega-regions by the America2050 project of the Regional Plan Association. I also have a longstanding interest in commuting flows (and mapping them) so I set myself the challenge of mapping micro-level commuting flows in the contiguous United States in the hope of identifying what I expected would be some interesting mega-region commutes. I also hoped, in the context of this data, that I would discover some of the mega commutes identified by Rapino and Fields of the US Census Bureau. On both counts I wasn't disappointed. The first map below shows the entirety of the lower 48 states and the commuting patterns come out quite clearly.

Journeys to work in the contiguous United States

Obviously, some areas are more interesting than others, so I zoomed in on various areas, including California and the Northeastern United States. The map below shows travel to work patterns in California, and you can clearly see the wider Los Angeles metro area as one large commuter region, the Bay Area as another (but more polycentric), and also the settlement and journey to work patterns in the Central Valley, from Redding in the north down to Bakersfield in the South. This shows the urban settlement patterns in the state of California, but also the spatial configuration of the commuting connections between places.

If you take a closer look at the working paper behind these maps you'll find out more about the data. What I found most interesting were the locations where 'mega commuting' was prevalent, so I looked at the top 20 Census tracts in the Northeastern US with the highest number of people commuting there - i.e. over 50 miles each way. As you can see from the table below, this is dominated by New York City, but Washington DC also features. The total volume may not seem much, but remember that these are quite small Census tracts, with only a few thousand people.

Mega commuting in the Northeastern United States

I then did something slightly different - I wanted to filter the data in a more scientific manner. Since the data provided by US Census Bureau includes a margin of error (MOE) value for each individual tract-to-tract flow, I calculated the coefficient of variation for each individual flow line (there were just over 4 million). These were based on a 90% confidence level, so the formula was simply:

((MOE/1.645)/Commuting Estimate) x 100

I used a rather generous cut-off and then displayed only those flows which had a coefficient of variation of less than 40. The results are shown in the map below. We can see the expected pattern of commuting but - hold on a minute - what are those really long distance lines? Surely people don't 'commute' vast distances like this. Well, it turns out that this might actually be true because many of these lines begin and end in military locations or other places associated with regular, long distance moves for work and since the American Community Survey asks respondents how they usually got to work ‘last week’, it's entirely plausible that a number of people will work away from home and that this will lead to the kinds of patterns we see below. Or, to put it another way, don't think of these long lines as journeys people travel every day! 

If you want to read more about it, you can click below to see the working paper, which also includes links to high resolution versions of the images shown here.

American Commute: working paper

The beating heart of the City of London

I've had a rush of blood to the head so here I am with a second blog in two days. I'm getting some slides ready for tomorrow's Modelling World 2015 talk in London, which is all about visualising mobility (see below) so I wanted to add in a couple of new visuals on commuting in and out of London. Visualisation can often be just a lot of fancy graphics. This can be useful in itself for a number of reasons (e.g. capturing attention on an important issue, drawing attention to unusual patterns in a dataset) but since I've been working with commuting data in England and Wales I wanted to focus on flows into and out of the City of London. 

This interests me for a number of reasons, including i) commuting can play a significant role in wealth creation and it also needs to be understood in relation to how we measure GVA; ii) commuting is often very stressful and damaging to the individual - particularly long commutes - so I'm interested in the kinds of distances involved and this can be seen easily on a map; iii) commuting can often be environmentally damaging - though this isn't what I'm mapping here; iv) commuting in and around London is often about green belt hopping so I was curious to see how much commuting comes from beyond the metropolitan green belt; and v) commuting is a two-way process and affects places at both ends and in between due to travel. 

So, here's what I did. I took the MSOA-level commuting data for England and Wales (table WUEW01 here), used a bit of QGIS, extracted frames from QGIS using the MMQGIS plugin, then patched it all together in GIMP to create an animated gif. One for inflows, one for outflows and one for in and outflows (thanks to Ebru Sener for the idea). It might run a little slowly in the blog post in a browser but see below for the images. Just to clarify, I've only shown flows of 25 or more into the City of London. Those not familiar with the data should be aware the the 'City of London' refers to the small area in the centre of London and not the entirity of Greater London! An obvious point but one worth repeating in case anyone is confused. A Greater London map would have many more data points, covering most of England.

Commuting flows (>=25) into the City of London

Same as above, but going back the way

The 'pulse' of the City of London

You should be able to get a better view of the images by clicking on them individually and if you want them to work more quickly try saving them to your own machine.

The Polycentric South East

Tweets yesterday from Michael Edwards and Joseph Kilroy reminded me of a map I produced last year in which I showed commuting patterns in South East England, minus London. I did this to get a sense of the polycentric nature of travel to work in the South East as this has been a topic of many previous studies - including the famous Hall and Pain book - but none (to my knowledge) using the 2011 Census data I mapped. The other reason for me blogging about this today is that I'm speaking on a similar topic at Modelling World 2015 this Thursday in London. Enough words, time for some maps, which I've refreshed for this week.

The first map below shows all commuting in the South East of England in 2011, without place names. As you can see, I've removed London from the equation, both in relation to travel to work flows and from the underlying map canvas. This gives a slightly different perspective than the one we're used to. The second map is the same as the first but I've added the names of local authorities in order to help identify places. Click any of the images to enlarge.

Commuting in South East England, 2011

Same as above, but with labels

Now, here's what it looks like when you add London back in... Kind of brings to mind astronomical metaphors, as hinted at in a previous study by the RTPI. I should add that the definition of a supernova is 'a star that suddenly increases greatly in brightness because of a catastrophic explosion that ejects most of its mass' so this might be stretching things slightly... Then again, if what people are saying about the displacement of the poor from London this might actually be spot on.

The 'London Supernova'

Finally, I've produced a zoomed-in version closer to London where you can see some of the flows which go through/over the capital. I don't fancy that commute!

A national map of cycling to work

I've recently being doing some visualisation work with the newly released Census commuting data from 2011. I've produced maps of all travel to work, and travel by car, train and bus. I've now done a map of cycling to work (below). This map is particularly interesting in relation to the patterns it reveals but also in relation to the strange long-distance flows we can see. I'm certainly not saying that anyone actually commutes by bike between Manchester and Bristol, as the map may suggest. Click on the big version and have a look around to see if you can spot anything interesting or particularly unexpected. A version with some place name labels can be found here.

Go to the full size version

This data comes from Question 41 of the 2011 Census form, which asked people to say how they 'usually' travelled to work in relation to the mode of transport which accounted for the largest part, by distance, of their journey. The results can look quite beautiful on a map, but they can also be confusing. Look closely at the map above and you'll ask yourself why there are so many long distance cyclists in England and Wales. More seriously, you might begin to question the validity of the data, the honesty of respondents or some other aspect of the results. 

The ability to interrogate datasets in this way is one of the strengths of visualising large datasets in that we can often immediately identify anomalous patterns or results that confound expectations or are just plain wrong. I'm not entirely sure what's going on with the long-distance flows. Perhaps some people take their bike on a train so ticked the 'bike' option, despite the train journey being longer. Perhaps some people live in one part of the country during the week and cycle to work there but then live at their usual address during the weekend and this is registered as their residence on the Census forms. I'm only speculating but this could be one possible explanation. 

In the image below, I've filtered the data so that only flows of 2 or more are shown. This significantly reduces the visual clutter, but also draws out stronger long distance connections between places such as Bristol and Manchester, and indeed Manchester and lots of other places. Take a closer look by clicking the link below this map. I've added some place names to this map to help with orientation.

Go to the full size version

I'd be keen to hear different interpretations on the data. You get similar results when you map the 'walk to work' data so there's definitely something interesting going on with how people have answered the Census question and the data we have to work with. I'm certainly not saying it's 'wrong', more that we need to understand what exactly it tells us. For now, I'll leave it at that.

N.B. Why didn't I include Scotland and Northern Ireland? The data are not out yet. It's not some ploy to exclude anyone and I know the blog title says 'national' so forgive me if that threw you. I intend to expand the analysis in due course.