Revising urban areas and the rural-urban definition and classification for
England and Wales
Summary report of response to survey and next steps
Introduction
This document has been written to summarise the responses to the user
engagement survey and set out our next steps for revising the urban areas and ruralurban definitions.
Background
The survey, run on behalf of the joint project team1, was designed to capture user
views and therefore inform which options should be developed for revising the urban
areas and making enhancements to the rural-urban definitions/classifications. For
further information on the suggested options for revision and possible enhancements
please see:
http://www.neighbourhood.statistics.gov.uk/HTMLDocs/images/User%20engagemen
t%20document_tcm97-112039.doc
The user engagement survey ran from the 19th October 2011 through to 25th
November 2011. The survey received 60 responses during this period the majority
from public sector organisations, with private sector, not-for-profit/charity and
individuals also represented in the response.
Survey results and summary text
The survey results are set out according to the sequence of the survey questions. It
would not be appropriate to include all the comments received in a summary report.
However, selected comments have been added under each section to help illustrate
the main messages from the survey.
1
Department for Environment, Food and Rural Affairs, Office for National Statistics, Department for
Communities and Local Government and Welsh Government.
1. Please state which type of organisation you are responding on behalf of, or
whether you are responding as an individual.
The majority of responses came from Local Government (18 responses),
followed by Government Departments (15 responses), Private sector (7),
Individuals (7), Non Departmental Public Bodies (6) and Not-for-profit/charity
(5).
2. Ranking of Urban Area methodology options.
Option 3 was ranked as a first choice by 10 of the respondents, closely
followed by option 4 (9), option 1 (8) and option 2 (3). If the first and second
choice (rank) percentage score were combined the sequence of option
preference remains the same (i.e. 3,4,1 and 2). Option 1 was ranked 4th by 12
respondents, followed by option 4, 2 and 3 (although this option was not
ranked 4th by any respondents.
Comments made reflected the split (as shown in the ranking scores) between
users who wanted boundaries to reflect real world features and those who
valued the advantages of a grid-based approach.

Option 4 bears no simple relation to real world features on the ground – it’s an abstract
shape. However, by modifying option 4 you could make a more realistic outline which is
defined by features.

The example maps provided show option 4 as a reasonably accurate replication of
manual digitisation, whilst having advantages of being repeatable, eliminating subjectivity,
and able to include further land-use info. However, the credibility of the dataset could be
compromised if option 4 deviates away from this level of accuracy for other areas that
haven’t yet been mapped.

Option 4 is easy to produce but lacks aesthetic value and positional accuracy as it does
not align with real world features and would lead to inaccuracies when calculating the
area or population.

Option 4 might well work out to be ok, but I don’t think you should rule out the possibility
of manual correction in cases where it just does not work out and fit with real life
perception.
3. In section 4.6 of the accompanying document three possible product
enhancements were set out in relation to option 4 (the gridded approach to
creating urban areas). Please provide comments and views on: 1. Whether
additional information, such as detailed land use and settlement names,
should be assigned to the grid squares and why? 2. Whether urban 'holes'
which may relate to open space, parks should be included and why? 3.
Whether the size of the proposed grid squares (50 meters) should be
amended to a higher (25m) or lower (100m) resolution and why?
16 responses were received in relation to this question.
Users welcomed the inclusion of additional information, with names and landuse the most commonly cited examples.

More info would definitely be better, key for our use is settlement size and names (i.e. for
those areas smaller than 10k threshold)

Land use info. would be useful for the purposes of landscape impact evaluation for major
new infrastructure schemes.

Enrichment of the dataset would be invaluable, as it would extend the usability beyond
the rural and urban classification

It is useful if any additional info. or attributes are attached to each grid for running queries
There was broad support for the ability to identify urban ‘holes’ but most felt
this should be created as a separate, supplementary dataset.

I suggest including this as a separate dataset to avoid over complication

Identification of parks and open areas as a separate set of digitised boundaries would be
welcomed, however where these are totally surrounded by an area classified as ‘urban’
these should not be shown as holes in the urban boundaries dataset.

Id’ing urban holes usefulness will depend on their match to real world features
In general, users seemed content with 50m grid squares. Some said a higher
resolution (25m) would be preferable for increased accuracy but
acknowledged that there may be processing/budgetary implications.

Some of our users suggested the smaller the resolution the better, however each halving
of grid dimension quadruples the number of squares with potential impacts on resources
to do the calculations.

The [urban area] shapes themselves and all their properties… will vary according to the
size of the [grid] square used to generate them… Since this is the first time that the urban
areas have been created in this way in some sense the size of the square doesn’t matter
as long as it stays the same from now on,

A higher resolution would give a better match to actual boundaries but may prove beyond
budget.

25m preferred but 50m would probably be fine.
4. Options for sub-categorising the urban domain: Option 1. - Urban domain
classified as larger towns, cities and metropolitan areas. Option 2. - Urban
domain classified based on settlement population bandings. Option 3. Urban domain classified based on both of the above options, so users can
make their own choice.
The chart shows that the majority of those responding to this question
preferred option 3, which includes both urban domain category options 1 and
2. The numbers on the chart represent responses received.
Additional comments were:

Option 1 is preferred because urban areas are classified based on their status and
population, Option 3 would also be acceptable as users could make up their own minds,
option 2 is not useful because these population thresholds will become out of date over
time.

More details and options is always better

Classification should be based on real characteristics that can be measured not status
which is subject to political whims.
5. Settlements changing to greater or less than 10,000 population options:
Option 1. - The definition is created based on 2011 populations and no look
up provided (the default option). Option 2. - Settlement based look ups are
provided so users can differentiate between which settlements have changed
in category. Option 3. - Those settlements which move above or below the
10,000 population threshold retain their previous definition as at 2001.
This question received 28 responses overall (the numbers on the chart
represent those responses received), option 1 appears to be the most
favoured (definition created based on 2011 populations (the default), followed
by option 2, then option 3.
Additional comments were:

We favour the option that gives us the best idea of changes between the two dates

It will be essential for us that the new method of creating urban area polygons is backapplied to the 2001 Census data, the new method will introduce differences of its own.
We will need a set of Census 2001 shapes generated using the new method to allow for
direct comparison

Option 1 is preferred, Option 2 could be useful but not essential, Option 3 is ridiculous
and makes no sense.

Option 3 is least preferred. Feel it’s important that classification recognises change and
does not stand still.
6. Are there additional issues relating to urban areas and the rural-urban
definition/classification which should be considered as part of this project?
12 responses were received relating to this question, the main points were:

In general, the most important thing for us is to be able to relate the new shapes to the
old. This means that it’s essential for us that shapes be created for the 2001 Census data
using the new method so we can distinguish real change in urban areas.

We would welcome a standardised urban-rural classification for the whole of GB, ideally
the UK, with categories and methods used the same. If not possible please take whatever
steps to standardise the method as far as possible.

Any classification system should ideally be scale-independent in the sense that it can be
applied to small scales (m or cm) as well as km, it is clear that the results will differ
according to the scale used.

In relation to the rural-urban definition consideration should be given to sensitivity
analyses of density thresholds defining different settlements and more information
published on this compared with last time. The category ‘urban fringe’ should be given
more detailed analysis and transparent geographic definition.

Our primary use of urban areas and rural-urban definitions is to calculate areas and
populations within them using in house population forecasts. Another major use is for
providing aesthetic background to maps as an alternative to OS raster maps. Option 4 will
infringe on both of these uses as a gridded boundary. The use of grid squares will
negatively impact on the accuracy and reliability of the social data we produce.

Please provide digitised boundaries for the settlements with names and 2011 Census
data for each. Also provide urban/rural classification applied to OAs, LSOAs and wards
with LA summary.

An output area lookup file containing both urban areas, rural-urban and further settlement
characteristics (pop size and name) would be a really useful product for ONS to make
available as an output from the Census.

For us, the devisive issue has been the ward classification. We feel a richer classification
system could be useful here – namely adding ‘mixed’ urban or ‘mixed’ rural.

The two challenges to using the RUD are the lack of different urban settlement types; and
the asymmetry in population sizes in the different types. The second issue could be
improved by having an ‘intermediate sparsity’ group separated from the ‘less sparse’
context.

A prevailing overall OA classification or urban areas and rural-urban areas would be
useful.

The core logic is due for review: in particular, by the application of current principles two
large urban areas, such as Leeds and Bradford can be deemed linked purely because of
well spaced houses along one side of a single road

Clear labels of the classification, these make it very difficult to communicate e.g. sparse
and less sparse. These labels don’t mean anything to the audience.
7. Would you be interested in attending a workshop to learn more about these
options and to discuss the proposed developments with members of the
project team?
Overall most respondents were not interested in attending a workshop.
Next steps
The project team would like to thank all those that contributed to providing a
response to this survey it has enabled key decisions to be taken on next steps
regarding this programme of work. The next steps can be categorised into the
following four aspects:
 Developing the urban areas based on the preferred options
 Attribution of urban areas and scale
 Updating the rural-urban definition/classification
 Workshop and further engagement
Developing the urban areas based on the preferred options – the project team will
establish detailed cost information for undertaking option 3 (automatically generated
polygons with manual correction) and option 4 (automatically derived grid based
data). Once this information has been established these two options will be
assessed by the project team and recommendations will be made by this group on
which option to commission. The criteria for this assessment will not only be based
on value for money but achieving a product that broadly fulfils the needs of the
users.
Further consideration will also be given to possible enhancements to the grid-based
approach, as suggested by a number of respondents, which would enable better
alignment to real world features. Attribution of urban areas and scale – in
establishing a cost for the two options, a process for allocating settlement names,
population and land use categories will be assessed for fitness for purpose for the
product. It is likely that the urban holes option will be made available as a subsidiary
product to the main urban areas dataset. Subject to final recommendation of which
option to develop (i.e. 3 or 4), if option 4 it is likely that the current suggested scale of
50 metre grids would be utilised as the balance of comments received seem to
suggest this would be OK.
Updating the rural-urban definition/classification – based on the responses received
to this survey the urban domain (>10K population) will now include further sub
categorisations, the feasibility of including both options will be investigated i.e.
mets/cities/large towns and population bandings. For settlements changing to
greater or less than 10k population between 2001 and 2011, the current threshold
will remain to define between rural and urban settlements, however the feasibility of
providing a lookup for those which have changed will be assessed (as this option
was nearly as favoured as option 1 (the default).
Workshop and further engagement – There was insufficient interest to warrant
running a workshop event. However, the contact details of those who expressed an
interest will be retained as there may be further opportunities for involvement at a
later date in the project.