GIS Report - Leeds Internet Use

Page 1 :: Geodemographic Analysis of Internet non-use in Leeds Cobain Schofield

Geodemographic Analysis of Internet non-use in Leeds

Project Brief

A Leeds based IT training company is organising an internet training campaign for people who haven’t

used the internet before at a local school. The campaign involves the delivery of 5,000 advertisement

leaflets to local residents. The project specification states:

1. Identify the top five schools within Leeds that would make the most appropriate locations to run an

internet training course for people who have never used the internet before.

2. Identify a ranked list of the top 10 Output Areas (OA) to target a leafleting campaign for 400 leaflets.

3. Identify a range of Output Areas to target the remaining 4,600 leaflets

Selecting the top 5 schools

Locations of all schools in Leeds were obtained from the Department for Education [1]. The dataset

contained a list of all schools past and present, so schools which are either closed, duplicates (ie: primary

and secondary schools on the same site) or merged with other schools, were omitted from the dataset

leaving 296 schools on unique sites left for analysis.

Figure 1 :: Map of Leeds showing OAC Super Groups and ward boundaries, overlaid with locations of all

296 presently open schools and their catchment areas


According to the Project Brief, the top 5 schools within Leeds needed to be identified. In order to do this,

catchment boundaries were drawn according to the client’s criteria:

“People using a school predominantly reside within a Euclidean distance approximating a ten minute walk”

Based on this criterion, the average walking speed of 3mph can be used to estimate a radius around each

school: 3mph = 4828 meters/hour 4828 / 6 ≈ 804 meters

This gives a radius of 804m for the catchment areas, however, the provided radius is 1608m; double the

actual radius. This suggests that the catchment diameter has mistakenly been provided in place of the

radius. Despite this, the provided radius of 1608m has been used in calculating catchment areas for the

schools. This has resulted in catchments of diameter 3216m being analysed. The catchments for all 296

schools are shown in Figure 1.

Establishing the number of internet non-users in each Output Area

In order to properly establish the number of internet non-users, census estimate data was downloaded from

the Office for National statistics [4]. The number of non-users were then calculated on the basis of both

‘count’ and ‘rate’, where count is the actual number of non-users, whereas rate is the rate of non-use

across the OA, expressed as a percentage of total population. The Oxford Internet Survey [3] was used to

gauge rates of non-use.

Figure 2 :: Map of Leeds showing total number of internet non-users per school catchment


Figure 2 shows the total number of internet non-users falling within each school catchment. As is obvious

from Figure 1, the catchments often overlap, so a large proportion of internet non-users will be counted for

multiple schools. This may slightly exaggerate the distribution of non-users across Leeds, although the

general trend should remain the same. The trend is simply a large number of non-users in the centre of

Leeds, decreasing outwards into the suburbs and rural communities.

Figure 3 :: Map of Leeds showing the non-user count for all OAs across Leeds, with school locations and

ward boundaries overlaid

Figure 3 and Figure 4 show the differences in distribution between areas of high non-use, both in terms of

count and rate. The differences mean that there are potentially issues selecting which dataset to use in

order to establish the top 5 most suitable schools in which to locate the training sessions


Figure 4 :: Map of Leeds showing the non-user rate for all OAs across Leeds, with school locations and

ward boundaries overlaid

.

Figure 5 on Page 5 shows the same maps as Figures 3 and 4, but includes the top 5 schools on each map.

It is immediately clear that the top 5 schools for each dataset are in completely different areas of Leeds.

The top 5 schools from the count dataset are clustered together in the centre of Leeds (consistent with

Figure 2), while those from the rate dataset are spread across the city.

Figure 6 on Page 6 shows how the top 5 schools selected by internet non-user rate, infact have low counts

of non-users. This could be due to the relatively larger size of the output areas compared to those of the top

5 schools by count, or the total population being lower. This means that a high percentage of non-users

does not necessarily mean that there is a high number of non-users within the output area. Therefore, it is

logical to base the top 5 schools on the non-user count of their catchments, rather than the non-user rate.


Figure 5 :: Non-user count (top) and non-user rate (bottom) with Top 5 schools for each dataset overlaid


Figure 6 :: Top 5 school catchments from internet non-user rate dataset (Figure 5 bottom map), with OAs

coloured by internet non-user count. Schools are marked with a cross in the centre of the map.

Top 5 Schools from Internet non-user count dataset

The top 5 schools from the Internet non-user count dataset are those clustered in the centre of Leeds in the

top map of Figure 5. Table 1 lists these 5 schools, which satisfy Item 1 of the Project Brief.

Table 1 :: Top 5 schools from internet non-user count dataset alongside dominant OA classification

School Total Population within Catchment

Total Population of Internet Non-users

Dominant Output Area Group

1 Nightingale Primary Academy

55260 10248 Multicultural Metropolitans: Challenged Asian Terraces and Flats

2 Harehills Primary School

54123 10049 Multicultural Metropolitans: Pakistani Communities

3 Woodlands Primary Academy

51775 9850 Multicultural Metropolitans: Renting Young Families

4 Shakespeare Primary School

54377 9726 Multicultural Metropolitans: Commuters with Young Families

5 Bankside Primary School

52994 9656 Ethnicity Central: Established Renting Families

1 2 3

4 5

0m 1608m 3216m


Leaflet Distribution Areas

Top 10 Output Areas

Item 2 of the Project Brief states:

“Identify a ranked list of the top 10 Output Areas (OA) to target a leafleting campaign for 400 leaflets”

The top 10 OAs in Leeds were chosen by selecting those with the 10 highest counts of internet non-users.

These OAs are plotted in orange on Figure 7.

Remaining 4,600 Leaflets

Item 3 of the Project Brief states:

“Identify a range of Output Areas to target the remaining 4,600 leaflets”

To select the OAs to distribute the remaining 4,600 leaflets, the OAs were ordered by count of internet non-

users, and the OAs from 11 to 125 (115 OAs in total), were selected and coloured yellow on the map in

Figure 7.

Figure 7 :: Map of Leeds showing the top 5 schools from Table 1, and 125 output areas highlighted for the

distribution of 5,000 leaflets. All other schools are plotted as points.


Figure 7 shows a massive spatial distribution of proposed OAs to target leaflets. There are actually only 7

recommended OAs falling within or partially within the catchments of any of the schools, as shown in Figure

8 below. This shows that most people receiving leaflets will not benefit from a local venue for the training

sessions.

Figure 8 :: A map of the top 5 school catchment areas with leaflet distribution OAs overlaid

To overcome this issue, Figure 9 shows the OA non-user count for OAs which fall within the 5 school

catchments only. This means that leaflet distribution is much more targeted and a lot more effective to both

the client and the internet non-users who are interested in the course because they all fall within the

catchments of potential course venues.

Table 2 details the breakdown of the OAs. In the combined catchment of the 5 schools, there are 295 OAs.

Of these, 125 OAs will be targeted with leaflets.

Top 10 OAs for Leaflet Distribution

Based on the data in Table 2, it is logical to choose the 2x OAs with non-user counts exceeding 179, and

the next 8x highest OAs from the 91 to 179 count category. These top 10 OAs have been plotted into

Figure 10 in yellow.

Table 2 :: Total number of non-users per OA within the combined catchment of Figure 9

Internet non-user count OA count

38 to 56 216

56 to 71 48

91 to 179 29

179 + 2


Remaining 4,600 Leaflets

The remaining leaflets should be distributed in the same way as the top 10, taking the next 115 OAs with

the highest remaining counts. This means that the remaining 21x OAs from the 91 to 179 category are

included, along with all 48x from the 56 to 71 category, and the 46x highest OAs from the 38 to 56

category, to give a total to 115x OAs to distribute the remaining leaflets to. These OAs have been plotted

onto Figure 10 in blue.

Figure 9 :: Clipped map of the combined top 5 school catchment areas with OAs coloured by non-user

count per OA


Figure 10 :: Top 10 OAs and 115 OAs for remaining 4,600 leaflets plotted over map from Figure 9

Data Sources

All maps are based on Edina Census Geography [2] shape files and utilise data from the Office for National

Statistics 2013 census estimates [4].

1 School Location Data: HM Government Department for Education “Download all data” http://www.education.gov.uk/edubase/home.xhtml

2 Leeds Shape Files (mapping): Edina “Census Geography” http://census.edina.ac.uk/

3 Oxford Internet Survey: University of Oxford “Cultures of the Internet: The Internet in Britain” http://oxis.oii.ox.ac.uk/wp-content/uploads/2014/11/OxIS-2013.pdf

4 Output Area Census Data: HM Government Office for National Statistics “Census Output Area Estimates in the Yorkshire and Humber region of England, Mid-2013” http://www.ons.gov.uk

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