Identifying Transport Profiles
It is evident that there is considerable variation and heterogeneity in transport characteristics of MSOAs across England and Wales. The next step was to determine whether different groups of MSOAs with a similar
transport profile could be identified. To do so, we used the transport characteristics discussed above, such as commuting mode shares, car ownership and travel time accessibility by different modes to represent the transport profile of an
MSOA. We used a clustering algorithm to group the MSOAs into distinct transport profiles (Shelton et al., 2006). Clustering algorithms group data points to maximize similarity within groups and minimize it between them. Our clustering revealed five
distinct groups in our data:
Good train accessibility but car dependant This cluster is composed of rural areas that surround land-locked urban areas. The MSOAs in this
are mainly in the center of England and Wales, compared to the rural areas in profile 2, which are on the outskirts.
This cluster has the second best accessibility scores for all measured transport modes due to the central locations. The cluster benefits from being on train routes and has the second highest train usage, but that is the only mode of
public transport that the MSOAs in this cluster are serviced by. As a result, the cluster is associated with high car ownership and usage, followed by train and walking.
Solely car dependant This cluster is made up of rural areas far from the cities. The MSOAs have few public transport options and people depend on
cars to move around. They have poor accessibility even by car, and this could be due to a lack of direct road and other connections between them and other parts of the country. The cluster is found on the periphery of profile 3, which is
itself made up of coastal urban areas with poor accessibility.
Lack of accessibility across all transport modes This cluster shows the third highest usage of bus, bicycle and walking to work, but has the
train usage, working from home (WFH) and all around accessibility. The most popular modes to travel to work are by car, by walking and bus, but the lack of accessibility across all modes and little train usage is the defining feature.
be found in coastal towns and cities such as Newcastle, Cardiff and Blackpool, which might suggest the MSOAs are at the end of train lines and other transport networks and therefore lack external connectivity.
High public transport and good accessibility The cluster is associated with high usage of public transport including the underground/metro/tram,
train and bus. It is noted to have very good accessibility to all MSOAs through all transport modes. This cluster dominates London, but can also be found in the centre of some MSOAs in big cities like Manchester and Birmingham. The
cluster suggests that the transport profile of London is different to the rest of the UK and can only otherwise be found in high accessibility centres of large cities.
Car reliant but high public transport This cluster has high car usage but is notable for the comparitvely large number of people who use the bus
and walk to work. These MSOAs also have a high degree of accessibility but the overall transport profile is more shifted towards cars than the previous cluster. This is found in large Urban areas across the UK such as Manchester and
Birmingham, suggesting that the main difference between these and London is the degree of usage of public transport with the main difference occurring due to the lack of usage of an underground/metro/tram.