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The United Kingdom National Area Classification of Output Areas

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Title: The United Kingdom National Area Classification of Output Areas


1
The United Kingdom National Area Classification
of Output Areas
  • Daniel Vickers
  • School of Geography, University of Leeds

2
What Is An Area Classification?
  • A segmentation system which groups similar
    neighbourhoods into categories, based on the
    characteristics of their residents.

3
What Is An Output Area?
  • The smallest area for census output
  • 223, 060 in the UK
  • EW 174,434 min size 40 hholds 100 people
  • Scotland 42,604 min size 20 hholds 50 people
  • NI 5,022 min size 40 hholds 100 people

4
What Goes In?
  • 41 Census Variables covering
  • Age
  • Ethnicity
  • Health
  • Housing Tenure
  • Household Composition
  • Employment and Education

5
Standardising The Data
  • Log Transformation

Why?
  • Reduces the effect of extreme values (outliers)

6
Standardising The Data
  • Range standardisation between 0 -1
  • Why?
  • Problems will occur if there are differing
    scales or magnitudes among the variables. In
    general, variables with larger values and greater
    variation will have more impact on the final
    similarity measure. It is necessary to therefore
    make each variable equally represented in the
    distance measure by standardising the data.

7
What Technique Was Used?
  • Modified K-means clustering
  • First level run as standard k-means
  • Second level, first level is split into separate
    files and each file is clustered separately
  • Third level, second level is split into separate
    files and each file is clustered separately

8
Issues of Cluster Number Selection
  • When choosing the number of clusters to have in
    the classification there were three main issues
    which need to be considered.
  • Analysis of average distance from cluster
    distance for each cluster number option. The
    ideal solution would be the number of clusters
    which gives smallest average distance from the
    cluster centre across all clusters.
  • Analysis of cluster size homogeneity for each
    cluster number option. It would be useful where
    possible to have clusters of as similar size as
    possible in terms of the number of members within
    each.

9
Issues of Cluster Number Selection
  • The number of clusters produced should be as
    close to the perceived ideal as possible. This
    means that the number of clusters needs to be of
    a size that is useful for further analysis.
  • At the highest level of aggregation, the cluster
    groups should be about 6 in number to enable good
    visualisation and these clusters should also be
    given descriptive names.
  • At the next level of aggregation, the number of
    groups should be about 20. This would be good for
    conceptual customer profiling.
  • At the next level of aggregation, the number of
    groups should be about 50. This can be used for
    market propensity measures from the larger
    commercial surveys.
  • (Martin Callingham Birkbeck College, 2003,
    Personal Correspondence)

10
Cluster Selection
  • A three tier hierarchy 7, 21 52 clusters

11
Cluster Selection
  • First Level target 6, 7 selected based on
    analysis of, average distance from cluster centre
    and size of each cluster.
  • Second Level target 20, 21 selected based on
    analysis of, average distance from cluster centre
    and size of each cluster.
  • Third Level target 50, 52 selected based on size
    of each cluster. Split into either 2 or 3 groups

12
What Does The Classification Look Like?
2
2
2
3
3
2
3
3
3
3
2
2
2
2
2
3
3
3
2
3
2
52
7
21
13
What To Call The Clusters?
The naming of the clusters is a near impossible
task and on that always provokes much debate
however it is a very important one, as if it is
done wrong it can a false impression of the
people within a cluster. The naming must follow
two general principals 1. Mustn't offend
residents 2. Mustn't contradict other
classifications or use already established names.
14
How Does It Discriminate?
15
How Does It Discriminate?
16
How Does It Discriminate?
17
How Does It Discriminate?
18
How Does It Discriminate?
19
Focus On Leeds
20
A Look Around The Country
  • London
  • Edinburgh
  • Cardiff
  • Birmingham
  • Manchester
  • Liverpool
  • Newcastle
  • Bristol
  • Bradford
  • Norwich
  • Nottingham
  • Southampton
  • Glasgow
  • Dundee

21
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