Gordon Stokes Transport

Self containment of settlements

Transport Home

Photography Home

Transport Photos

Last updated - Dec 2018



Pages in this series

This page

Link back to census mapping, which includes self containment mapping



This work is ongoing research based on 2011 census travel to work data. It goes alongside attempts to map 2011 census data for journeys to work.

Currently this contains maps showing degree of self containment as measured by the percentage of people living and working in a built up area. I have written a small amount of descriptive interpretation here, and have started on work to analyse what factors relate to self containment, which will be written about later.

How self contained are different settlements?

The aim of this work is to assess to what extent urban areas are self contained units. That's a difficult problem to work out precisely - "no town is an island", but some places are more so than others. The motivation started from the question of whether the post war generation of New Towns have remained more self-contained than other settlements of similar sizes but of different natures. But the issue is also of current relevance given the number of planning applications for large settlements outside existing ones. It's important to get some gauge on to what extent these will add traffic to roads in the area, or the extent to which they can hope to be self contained.

Methodology

The data used was from the 2011 UK census journey to work data, and linking this to data defining built up areas. The data on built up areas was from the Office of National Statistics (ONS) ‘lookup’ file for Census Output Areas (OAs) which includes Built Up areas (BUAs). The journey to work data used the Middle level Super Output Area (MSOA) level data accessed from the ‘NOMIS’ web site Origin-Destination (OD) data. Data is available at Output Area level for all modes of travel but as the NOMIS download limit is 1 million records (a 1,000 by 1,000 array) and as there are over 180,000 OAs it was only practicable at MSOA level. Even at this level data had to be downloaded for each region separately. At the foot of this note is a list of the datasets used.

Two programs were written. These were written in Fortran which some might find almost amusing. But it works, and is ideal for the computations needed in this case.

In addition to this Built Up Area approach, published data on numbers travelling different distances was also used to provide a different measure of locality. Data from Nomis allows has numbers travelling less than 2 or 5 kilometres (as well as longer distances). The Nomis data also includes the total distance that MSOA or settlement residents travel (in commuting) as well as the average distance.

Calculation of percentage living and working within the local area

Those who travel to work and record a usual mode of transport to work do not account for all those in employment at the time of the census. To get figures that add up is difficult, due to the definitions used for census travel to work purposes, which change between censuses. For this study, the number of people recording journeys within a BUA is divide by the number of residents of the BUA who have an origin and destination MSOA recorded. Thus, if, for example, an unusually high proportion of residents work from home, this will not be seen to affect the percentage travelling within the BUA. But, hey, life’s too short, and there’s plenty of other approximations and potential errors to muddy the figures.

Effect of using Regions for calculations

The extraction of OD data at regional level means there are some cases where BUAs straddle Region boundaries. This only occurs in a few cases, as Regional boundaries seldom pass through large settlements. Greater London does straddle various boundaries, and some areas relating to London boroughs cross into East or South East regions. An example is Redbridge which straddles Essex (East of England) and London. This can lead to, for example, a town with 2 MSOAs in one region, and 1 in another, only counting journeys between the 4 (2x2) in one region and the 1 (1x1) in the other (5 in all) rather than 9 (3x3).

Where such cases have been identified they are noted. Again, on the principle that life's too short to worry, this is overlooked. You're welcome to do an analysis to judge the scale of the problem, but I don't believe it's massive!

Built Up Areas and Sub-Divisions in ONS data

As mentioned above, the ONS uses the notion of the closeness of addresses for defining what is a BUA, using Hectare grids, roughly describing a set of hectare squares that each have addresses in and are contiguous as being a single BUA. This will not always accord with peoples’ view of a BUA in which they live. For example the Greater London BUA includes places such as Hemel Hempstead, Bracknell and several other sizeable towns that are regarded as separate entities.

Sub Divisions use a different formulation to split many of the BUAs into “BUASDs”, which makes places such as Hemel Hempstead separate areas. But this sub-division can also produce sub-areas that some will not recognise as built up areas. For example each London Borough is a sub area of Greater London (though these, such as Redbridge mentioned above) can extend outside Greater London.

For the purposes of this study BUAs and BUASDs have been analysed separately.

Post calculation analysis

The cacluation produces one figure for each BUASD/ BUA - the percentage of journeys to work from a BUA that end in that BUA. The prime interest in the study was to take a qualitative (maybe better described as anecdotal) approach to assessing whether some particular New towns which are ostensibly similar to other settlements have different degrees of employment self-containment.

But this inevitably leads to research into the degree to which size of settlement, distance to major external commuting attractors, remoteness and other factors affect self-containment. For this both GIS mapping and very simple regression were also used.

Basic results

Built Up Areas with high levels of self containment

Table 1 shows the 30 built up areas with the highest percentage of their journeys to work staying within the settlement. (Note that subdivisions of built up areas are in the next table).

There's plenty of interpretations that could be put on this list, and of course it only shows the one with the highest degree of self containment, but it looks as though the following are worthy of further analysis to see if they are factors:-

Built Up Sub divisions with high levels of self containment

Table 2 shows the same results for BUAs or BUASDs. In this case, if a BUA is split into BUASDs only the sub divisions are shown. Hence, the West Midlands has been broken down into Birmingham, Coventry etc. Many others, such as Oxford, are split, but because the sub areas, other than the main named place are small, this make a small difference to the degree of self containment.

The main differences between Table 1 and Table 2 are that:-

Results of mapping self containment

The interactive census mapping page contains maps shoiwng the percentage of residents who work in their settlments (pie chart maps). The options on the right hand side can be used to select '% of those who travel to a job who also work in that BUA' or '% of workers of that BUA who also live there'. The two are different since there are mostly different a different number of workers and jobs - they're very unlikely to be the same.

Figure 1 below shows a map for residents in the area between Oxford, Cambridge and London. Hovering a mouse of it or tapping on a tablet should replace it was an image that alternates between 'home' and 'jobs' versions.

Give it a bit of time to get used to what's going on and you should be able to see (amongst very many other things) that:

Figure 1. Percentage of residents of a built up area who work in that BUA
Hold the mouse over the image to alternate with % of jobs with workers from that BUA - or tap on a tablet

TO BE CONTINUED - December 2018

-

Footnote: Data sources

Data on journeys was all taken from the 'Nomis' web site and from the public area of the UK data archive "FlowData downloads page" ("WICID"). The data on modes of travel and distance travelled (non flow data) are from tables QS701EW (mode) and QS702EW (distance) which are found in 2011 Quick Statistics. All data used is public access.

The data from journeys between Medium level Super Output Areas (MSOAs) is from table WU03EW. (The data for self containment of settlements is also from WU03EW, but used more complex processing which I'll explain later).

Back to Transport Index

Gordon Stokes, 2016