Renew Pedestrian Modelling in the City by Media Metrica Ltd

Pedestrian Modelling in the City of London

January 2009 Media Metrica ltd | Renew Your Streets ltd Studio two 166 Tower Bridge Road London SE1 3LS 020 7407 2933 020 7089 9022

Tables of Contents Executive Summary Pedestrian flows in the City of London The Pedestrian Model

I. II. III. VI. V.

Appendices

Visibility analysis Pedestrian Flow Counts Gate Identification Unit sites and associated pedestrian traffic Network Audience Calculations

19 21 23 24 27

Executive Summary Renew is a communication network designed to target and engage with a pedestrian audience. The Renew team have worked with Intelligent Space Partnership Limited (ISP) to develop a pedestrian model of the City of London from which to establish to best unit locations and to determine the size of the pedestrian audience passing these units. This summary report explains the pedestrian model and the methodology upon which the projections are derived. The report begins by presenting the results of a major pedestrian movement survey in Westminster and the City of London. In this survey, real pedestrian flow data was captured from over 100 locations between the 9th and 11th May 2006. These observations were combined with past observations recorded by Intelligent Space and are held in their pedestrian flow database. This has given a total of 182 individual sample locations. In terms of street segments, this provides 268 samples on which to base the annual flow calculations (98 samples in the City of London and 170 in Westminster). A calibrated model of pedestrian flows has been created for the Westminster and City of London areas in which Renew units could be located, providing predicted flows for over 1,650 individual street links. The model is based on a very large origin-destination matrix comprised of 577,623 potential locations for pedestrian movement within London. For the annual pedestrian flow model presented in this report, over 125 individual measures have been tested for statistical significance against pedestrian flows. Many of the significant factors for this study area are strongly related to retail activity, such as the number of shops in view, the size and accessibility of department stores and the accessibility of food and drink uses. Other factors that are significant include public transport (accessibility of tube stations within the street network) and footway capacity. This document sets out the findings from Intelligent Space Partnership Ltd’s pedestrian model of the two deployment zones identified by Renew; the New West End and City of London areas. This model has benefited from the extensive experience of Intelligent Space Partnership Limited in modeling flows in London and provides the following A model estimating the pedestrian flows for the City of London The visualization of flows in the pedestrian model as an important decision support tool

About this report This report provides an overview of the specific study undertaken for Renew. For a more detailed technical review of Intelligent Space’s pedestrian modeling, including statistical techniques, origins of our approach, strengths and weaknesses etc, please see the white paper “Pedestrian Modeling in Large Cities” (2003) which can be accessed online.1

The white paper is also available online at http://www.intelligentspace.com/download/Pedestrian%20Demand%20Modelling%20of%20Large%20Cities.pdf

About Intelligent Space Partnership Ltd Intelligent Space Partnership Ltd (ISP). is a consultancy providing expertise on pedestrian movement and space use. We work to help improve public space, minimise social risks and maximize economic benefits. The practice uses science-based methods to turn pedestrian movement from an undervalued resource into a tangible and manageable asset. ISP is based in central London and carries out projects on an international level. Since its foundation in 2000, ISP has been working for renowned clients among government bodies, property owners, developers and consultants. The work of the practice is cited in the Department for Transportâ&#x20AC;&#x2122;s good practice casebook â&#x20AC;&#x153;Walking: The Way Aheadâ&#x20AC;?. ISP won the 2002 AGI Innovation Award for the analysis of crowding at Notting Hill Carnival and ISP were independent cross party technical advisors to the 2002 UK Parliamentary Debate on Walking in Towns and Cities.

Pedestrian flows in the City of London This section of the report provides the results of the pedestrian movement study undertaken in May 2006 and data from ISPâ&#x20AC;&#x2122;s pedestrian flow database. It presents some of the key features of the present movement pattern.

Survey methodology An observation study was carried out in the City of London and Westminster to gather evidence of current movement patterns. In this survey, approximately 110 individual locations were observed around the deployment areas, with approximately 78 locations in the City of London and 32 in Westminster. The surveys were conducted from Tuesday 9th May 2006 to Thursday 11th May 2006. For a detailed methodology report please see Appendix 2 on page 20. This data was then combined with pedestrian flow observations from 10 other previous projects undertaken by ISP. This resulted in a total of 182 individual locations observed in the City of London and 337 in Westminster. In terms of actual pedestrian flow on street segments this provides 98 samples in the City of London and 170 in Westminster.

Annual flow scaling method Having obtained pedestrian flow results for the hours of 08:00 to 18:00 (inclusive) the data was then annualised to give calculated yearly flows. The first stage in the scaling method is to calculate total daily flows from 00:00 to 23:00. Using 24hr recorded pedestrian flow data from ISPâ&#x20AC;&#x2122;s database of flows in London, the ratio of daytime flows (08:00 to 19:00) to night-time flows (19:00 to 08:00). Once attained, nighttime flows can be estimated and added on to our 08:00 to 18:00 day time flows. The next stage is to calculate the weekly pedestrian flows. To calculate Monday to Friday flows, our calculated total weekday daily flow was multiplied by 5. As all of the data used in this analysis was recorded on a weekday, a ratio was used to calculate weekend flows from weekday flows based on previous studies. It was found that the ratio of weekday to weekend flows differed in the City of London and Westminster (the city has very little activity at the weekend in comparison to the West End), therefore different scaling methods were employed to the flow data depending whether it was located in the City of London or Westminster. The final stage is to scale the calculated weekly flows to annual flows. In the City of London, it was found that there was little monthly variation in terms of pedestrian flow, therefore the weekly flow results could simply be multiplied by 52. In Westminster there is a peak of very high flow in the months of November and December because of Christmas shopping. Therefore as well as multiplying the weekly flow by 52, a typical November/December peak was also calculated and added to the equation.

Levels of movement The highest levels of pedestrian flow can be found in Westminster, on Oxford Street, with a highest calculated average annual flow of approximately 70 million. The highest annual flow in the City of London was recorded on Bishopsgate.

80000000 70000000 60000000 50000000 40000000 30000000 20000000 10000000 Oxford Street

Regent Street

Bishopsgate

Moorgate

Poultry Street

Cheapside

New Bond Street

King William Street

South Molton Street

Cannon Street

Eastcastle Street

0 Maddox Street

Highest a average annual pedestrian flow

FIGURE 1 Calculated annual pedestrian flow on selected streets in London

Change in flows over time In the City of London, the timing of pedestrian flows reflects the office land uses, with 3 peaks in pedestrian flows reflecting the morning commuter flows, the lunchtime activity and the evening commuter flows. This can be seen in Figure 2 below, which shows the average observed pedestrian flow sites in the City. FIGURE 2 Average hourly flows in the City of London 2000

Average PPH

1500

1000

500

0 08:00

09:00

10:00

11:00

12:00

13:00 14:00 Hour

15:00

16:00

17:00

18:00

Pedestrian Flows over a 24hr period To predict the missing time periods the streets were categorised into 10 different types of location based on land use and use levels. Each of the 10 individual location types were then modeled separately to predict the missing time periods. As the actual flow levels vary within each of the datasets, the approach taken has been for each to take the maximum flow then to calculate for each hour, itâ&#x20AC;&#x2122;s percentage of the maximum flow for that individual flow location. ISPâ&#x20AC;&#x2122;s database of pedestrian flow data has been used for the extrapolation of flows. This dataset contains over 1875 surveys on Weekdays in London and 753 surveys on Saturdays in London. Maps showing the locations of the Renew flow samples are shown on the A3 maps at the end of this document.

Location Type 1 Location: City of London Type: 3 Peaks: AM, Lunch, PM Time profile: A graph showing the time profile for this type of location is shown below. This highlights the average percentage of peak flows for each hour of the day, with the AM, Lunch time and PM peaks all close to 90% of the peak. Approach The locations for which there is no flow data are shown as greyed areas in the chart below. To model the times between 19:00 and 07:00, the percentage of the peak flows were multiplied by the peak flows for each separate location in order to glean the hourly flow counts. For the period of 07:00 to 08:00, the ratio of 07:00/08:00 was taken. Therefore to calculate the flows the ratio of 07:00/08:00 was multiplied by the 08:00 flows to get the predicted 07:00 flows. For the period 11:00 until 12:00, the ratio of 11:00/10:00 was taken. Therefore to calculate the flows, the ratio of 11:00/10:00 was multiplied by the 10:00 flows to get the predicted 11:00 flows. For the period of 15:00 to 16:00, the ratio of 15:00/14:00 was taken. Therefore to calculate the flows, the ratio of 5:00/14:00 was multiplied by the 14:00 flows to get the predicted 15:00 flows.

100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

:0 0

Location type 2 Location: City of London Type: 2 Peaks: AM and PM Time profile: A graph showing the time profile for this type of location is shown below. This highlights the average percentage of peak flows for each hour of the day, with the AM peak close to 100% and the PM peaks all close to 90% of the peak. Approach The locations for which there is no flow data are shown as greyed areas in the chart below. To model the times between 19:00 and 07:00, the percentage of the peak flows were multiplied by the peak flows for each separate location in order to glean the hourly flow counts. For the period of 07:00 to 08:00, the ratio of 07:00/08:00 was taken. Therefore to calculate the flows the ratio of 07:00/08:00 was multiplied by the 08:00 flows to get the predicted 07:00 flows. For the period 11:00 until 12:00, the ratio of 11:00/10:00 was taken. Therefore to calculate the flows, the ratio of 11:00/10:00 was multiplied by the 10:00 flows to get the predicted 11:00 flows. For the period of 15:00 to 16:00, the ratio of 15:00/14:00 was taken. Therefore to calculate the flows, the ratio of 5:00/14:00 was multiplied by the 14:00 flows to get the predicted 15:00 flows.

100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

:0 0

:0 0 23

:0 0 19

:0 0 18

:0 0 17

:0 0 16

:0 0 15

:0 0

:0 0 14

:0 0 10

:0 0 09

:0 0 08

:0 0 07

:0 0 06

:0 0

:0 0 05

:0 0 01

:0 0

Location Type 3 Location: City of London Type: 2 Peaks: AM and Lunch Time profile: A graph showing the time profile for this type of location is shown below. This highlights the average percentage of peak flows for each hour of the day, with the AM peak slightly higher than 90% of the peak and the lunch peak close to 90% of the peak. Approach The locations for which there is no flow data are shown as greyed areas in the chart below. To model the times between 19:00 and 07:00, the percentage of the peak flows were multiplied by the peak flows for each separate location in order to glean the hourly flow counts. For the period of 07:00 to 08:00, the ratio of 07:00/08:00 was taken. Therefore to calculate the flows the ratio of 07:00/08:00 was multiplied by the 08:00 flows to get the predicted 07:00 flows. For the period 11:00 until 12:00, the ratio of 11:00/10:00 was taken. Therefore to calculate the flows, the ratio of 11:00/10:00 was multiplied by the 10:00 flows to get the predicted 11:00 flows. For the period of 15:00 to 16:00, the ratio of 15:00/14:00 was taken. Therefore to calculate the flows, the ratio of 5:00/14:00 was multiplied by the 14:00 flows to get the predicted 15:00 flows.

100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

:0 0

Location Type 4 Location: City of London Type: 2 Peaks: Lunch and PM Time profile: A graph showing the time profile for this type of location is shown below. This highlights the average percentage of peak flows for each hour of the day, with the lunch peak close to 100% and the PM peak close to 90% of the peak. Approach The locations for which there is no flow data are shown as greyed areas in the chart below. To model the times between 19:00 and 07:00, the percentage of the peak flows were multiplied by the peak flows for each separate location in order to glean the hourly flow counts. For the period of 07:00 to 08:00, the ratio of 07:00/08:00 was taken. Therefore to calculate the flows the ratio of 07:00/08:00 was multiplied by the 08:00 flows to get the predicted 07:00 flows. For the period 11:00 until 12:00, the ratio of 11:00/10:00 was taken. Therefore to calculate the flows, the ratio of 11:00/10:00 was multiplied by the 10:00 flows to get the predicted 11:00 flows. For the period of 15:00 to 16:00, the ratio of 15:00/14:00 was taken. Therefore to calculate the flows, the ratio of 5:00/14:00 was multiplied by the 14:00 flows to get the predicted 15:00 flows.

100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

:0 0

Location Type 5 Location: City of London Type: 1 Peak: AM Time profile: A graph showing the time profile for this type of location is shown below. This highlights the average percentage of peak flows for each hour of the day, with the AM peak close to 100% of the peak. Approach The locations for which there is no flow data are shown as greyed areas in the chart below. To model the times between 19:00 and 07:00, the percentage of the peak flows were multiplied by the peak flows for each separate location in order to glean the hourly flow counts. For the period of 07:00 to 08:00, the ratio of 07:00/08:00 was taken. Therefore to calculate the flows the ratio of 07:00/08:00 was multiplied by the 08:00 flows to get the predicted 07:00 flows. For the period 11:00 until 12:00, the ratio of 11:00/10:00 was taken. Therefore to calculate the flows, the ratio of 11:00/10:00 was multiplied by the 10:00 flows to get the predicted 11:00 flows. For the period of 15:00 to 16:00, the ratio of 15:00/14:00 was taken. Therefore to calculate the flows, the ratio of 5:00/14:00 was multiplied by the 14:00 flows to get the predicted 15:00 flows.

100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

:0 0

Location Type 6 Location: City of London Type: 1 Peak: Lunch Time profile: A graph showing the time profile for this type of location is shown below. This highlights the average percentage of peak flows for each hour of the day, with the lunch peak close to 100% of the peak. Approach The locations for which there is no flow data are shown as greyed areas in the chart below. To model the times between 19:00 and 07:00, the percentage of the peak flows were multiplied by the peak flows for each separate location in order to glean the hourly flow counts. For the period of 07:00 to 08:00, the ratio of 07:00/08:00 was taken. Therefore to calculate the flows the ratio of 07:00/08:00 was multiplied by the 08:00 flows to get the predicted 07:00 flows. For the period 11:00 until 12:00, the ratio of 11:00/10:00 was taken. Therefore to calculate the flows, the ratio of 11:00/10:00 was multiplied by the 10:00 flows to get the predicted 11:00 flows. For the period of 15:00 to 16:00, the ratio of 15:00/14:00 was taken. Therefore to calculate the flows, the ratio of 5:00/14:00 was multiplied by the 14:00 flows to get the predicted 15:00 flows.

100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

:0 0

Location Type 7 Location: City of London Type: 1 Peak: PM Time profile: A graph showing the time profile for this type of location is shown below. This highlights the average percentage of peak flows for each hour of the day, with the PM peak close to 100% of the peak. Approach The locations for which there is no flow data are shown as greyed areas in the chart below. To model the times between 19:00 and 07:00, the percentage of the peak flows were multiplied by the peak flows for each separate location in order to glean the hourly flow counts. For the period of 07:00 to 08:00, the ratio of 07:00/08:00 was taken. Therefore to calculate the flows the ratio of 07:00/08:00 was multiplied by the 08:00 flows to get the predicted 07:00 flows. For the period 11:00 until 12:00, the ratio of 11:00/10:00 was taken. Therefore to calculate the flows, the ratio of 11:00/10:00 was multiplied by the 10:00 flows to get the predicted 11:00 flows. For the period of 15:00 to 16:00, the ratio of 15:00/14:00 was taken. Therefore to calculate the flows, the ratio of 5:00/14:00 was multiplied by the 14:00 flows to get the predicted 15:00 flows.

120% 100% 80% 60% 40% 20%

:0 0

Saturday Flows, City of London Location: City of London Type: 1 Peak: Lunch Time profile: A graph showing the time profile for this type of location is shown below. This highlights the average percentage of peak flows for each hour of the day, with the lunch peak close to 30% of the peak. Approach The locations for which there is no flow data are shown as greyed areas in the chart below. To model the times between 00:00 and 23:00, the percentage of the peak flows were multiplied by the peak flows for each separate location in order to glean the hourly flow counts.

100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

:0 0

The distribution of flows Pedestrian flows vary considerably across the City of London. The busiest streets appear to be located near busy stations such as Liverpool Street, Moorgate and Bank. High flows also occur on London Bridge. In these areas, annual flows are above 10 million pedestrians per year, whilst the highest calculated flows occur at Bishopsgate where a flow of just over 20 million pedestrians has been calculated. Figure 4 on page 11 shows the distributions of annual pedestrian flow in the City of London using a spectral range colour-scale from red (highest flows) through to blue (lowest flows).

The Pedestrian Model This section of the report presents the pedestrian model of Westminster and the City of London. It has been divided into a series of questions regarding the model in order to explain the approach.

What does the model measure? The model presented in this report is a model of annual pedestrian flow circulation within the New West End Company area of Westminster and the City of London. The output of the model is pedestrians per annum on over 1,650 street segments covering the deployment areas of Westminster and the City of London.

What are the origins and destinations used for the model? The modelling is based on a grid of origins and destination points covering the whole pedestrian movement network of the study areas. The grid is spaced at 3m intervals and the total number of potential origins and destinations is 577,623. This means that the total number of potential shortest journeys between origins and destinations used in the grid is huge (approximately 333 billion). Within this large number of potential journeys, a selection of key origins and destinations have been selected, for example the 11,450 entrances to retail units in the deployment areas account for approximately 6 billion potential journeys. More information about the method of visibility graph analysis used to calculate the grid of origins and destinations is provided in Appendix 1 on page 18. For the purposes of linking the model to sample data on flows, each street segment within the deployment areas is treated as a unit. This leads to potentially 13,774 street segments with individual flow values on them.

How is the model calibrated? The modelling is based on the standard statistical technique of Multiple Regression Analysis (MRA). This technique shows the relationship between a series of independent variables (for example, retail floorspace) on the dependent variable of annual pedestrian flow. The model has been calibrated against observed pedestrian flows from over 270 sample locations, using data from the survey presented in Section 3 on page 8.

The pattern of movement in the model

PSG A TE

MONUMENT

CORNHILL

UR C

LIVERPOOL STREET

C EC H

G DON ST

ST. PAUL'S

MANSION HOUSE

OS Licence Number: 1000232436

FA RRIN

BLACKFRIARS

R R TE

T ES US

LBO R

IA D UC T

é é

FARRINGDON

BARBICAN

CHEA PSID

LONDON WALL

MOORGATE

BANK

CITY RD

Modelled annual pedestrian flows in the City of London

C FEN

RC H

TOWER HILL

ALDGATE

TOWER GATEWAY DLR

ALDGATE EAST

Low

Millions of pedestrians

High

B ISHO

Annual Flow

The distribution of modelled flows within the City of London is shown in Figure 6 on page 14 and Westminster in Figure 7 on page 15, providing an overview of annual movement volumes. The colours on this map represent predicted pedestrians per hour on each street link, in a spectral range from red (highest pph) through to blue (lowest).

Which factors have been included in the model? Over 125 different measures that might have an influence on pedestrian flows are available for calibration of the model and have been tested using a combination of the observation study data recorded between the 9th and 11th May 2006 and the data already held in ISPâ&#x20AC;&#x2122;s pedestrian flow database. The measures are different ways of accounting for key influences on pedestrian flows, such as land use and pavement capacity. For each factor, statistical tests can be undertaken to identify which variables are significantly correlated with annual pedestrian flows. This is used to create a predictive model of the deployment areas. The statistically significant factors in this central London pedestrian model are strongly related to the town centre and retail activities of the study areas. Many of the factors relate to the visual accessibility of key land uses for short pedestrian trips. These are: The number of visible shops, The street network accessibility and size of department stores, The street network accessibility of food and drink outlets. As well as these land use oriented factors, there are some factors that relate to other transport modes and the capacity of the footway. These are: Public transport accessibility, measured as the street network accessibility of the nearest tube station, Footway capacity (the available width of footway for walking)

What kind of behaviours are not represented in the model? As this is a model of pedestrian flows on street segments, it does not address the detailed pedestrian behaviour of road crossing patterns. For example, on individual street segments it is possible to identify patterns of formal and informal crossing, where pedestrians cross at the designated area or away from it. However, the visibility graph analysis used in the pedestrian model can be applied to identify â&#x20AC;&#x2DC;desire linesâ&#x20AC;&#x2122; for pedestrian crossing. In this way, it is possible to use the model in this way to support advertising locations near significant formal pedestrian crossings, but this is not covered in the current scope of the modelling project.

appendix 1 - Visibility analysis About Visibility Modelling Visibility Analysis is a measure of how much space pedestrians can see as they move around at ground level. In dense urban areas, where there are many possible origins and destinations for pedestrians, there are a huge number of small pedestrian journeys between different locations. However, pedestrians are highly sensitive to the complexity of routes and they tend to choose the simplest path. This means that overall, movement flows tend to become concentrated on those streets that offer the simplest visual links through the street grid. Visibility (the area of useable space visible to a pedestrian at any point in the street grid) is one of the most important factors determining the pattern of pedestrian flows in models of movement. Research in many different cities over the last 20 years has shown that pedestrian movement flows tend to be greater on routes that provide clear and direct visual links through the built environment (so-called ‘desire lines’) than on complex routes where people cannot see directly where they want to go (A summary of this research can be found in Hillier (1996) “Space is the Machine” Cambridge University Press). Pedestrians rely heavily on visual information to orient themselves and move about, so their movement is highly influenced by this.

Methodology of Visibility Analysis Intelligent Space has developed state of the art software to quantify visibility for pedestrians in street networks. The software uses a technique known as ‘Visibility Graph Analysis’. The analysis calculates the visual field for a pedestrian at any point in the public space network. The photograh below provides an example of a visual field: it shows everything that a pedestrian can see at ground level from a particular point in Shoreditch, central London. Taking accurate scale maps of an area, a computer algorithm creates a grid of sample observation points throughout the pedestrian movement space. The computer then calculates the visual field at 360 degrees from each point in the grid by checking which of the other points each point can see. In the figure below, the points in red are all those directly visible from the location shown in the photograph on the previous page. The analysis tells us the area in square metres that is visible from a pedestrian standing at this point. By performing the same calculation for all points in a grid, measures of the average visibility of an area are calculated to enable comparisons between alternative designs. The resulting pattern of visibility can be represented by colouring each point according to the area of its visual field. An example of this is shown in the figure below, where the visibility of each part of public space is represented in an equal range, spectral colour scale from red (highest visibility) to blue (lowest visibility).

Using a Visibility Graph to Calculate Accessibility Measures Once a visibility graph has been created for a pedestrian movement network, it is possible to calculate various â&#x20AC;&#x2DC;graph measuresâ&#x20AC;&#x2122; about the network. For example, a computer programme can calculate the accessibility of each point within the network to every other point, travelling through the network on the simplest routes. This kind of measure can also be used to calculate the accessibility within a more limited local area, which tends to be a useful measure of how strategic a route will be for pedestrian trips.

Using a Visibility Graph to Calculate Natural Surveillance The visibility graph model is also the basis for measures of natural surveillance. By locating the entrances to buildings within the visibility graph, it is possible to calculate how well overlooked any point in the pedestrian movement network is from building entrances. These measures have been applied in this report to identify how well overlooked the public spaces in the designs will be.

appendix 2 - Pedestrian Flow Counts Summary of Surveys dates:

09/05/2006 10/05/2006 11/05/2006

days:

Tuesday Wednesday Thursday

time:

08:00 to 19:00

total gates:

110 sample locations

frequency:

every hour

duration:

5 minutes

total duration:

6050 minutes sampled in total over the three days

weather:

Tuesday: Fine Wednesday: Fine Thursday: Sunny/Fine

method:

stationary gate method

Method Following TfL sampling guidelines, flows were counted for five minutes every half an hour at each sample location. The sample method used is known as the â&#x20AC;&#x2DC;stationary gate methodâ&#x20AC;&#x2122; whereby all pedestrians who cross an imaginary line are counted during fixed periods. When recording their sample, observers distinguished between eastbound and westbound, or northbound and southbound pedestrian movement as appropriate. Unless specified, flows will be sampled on each individual pavement.

Sample Locations Overleaf is a map showing the locations of each street that were surveyed.

appendix 3 - Gate Identification

appendix 4 - Unit sites and associated pedestrian traffic

Rank StreetN ame

Flows between 08:00-19:00

Store

Building N o.

Building N ame

Postcode

ObservedFlows

BISHOPSGATE

29,000

PRET A MANGER

192

EC2M 4NR

MOORGATE

28,000

MARUBENI EUROPE PLC

120

EC2M 6SS

yes yes

MOORGATE

28,000

BP PLC

BRITANNIC HOUSE 1-6

EC2M 7BA

yes

MOORGATE

28,000

NEXT RETAIL LTD

88-92

EC2M 6SE

yes

BISHOPSGATE

27,000

THE OLD MONK

128

EC2M 4HX

yes

BISHOPSGATE

26,000

K FC

180

EC2M 4NQ

yes

KING WILLIAM STREET

25,000

yes

KING WILLIAM STREET

25,000

yes

POULTRY

22,000

POULTRY

22,000

ROYAL BANK INSURANCE SERVICES

SCOTTISH LIFE HOUSE

KING WILLIAM STREET

22,000

KING WILLIAM STREET

22,000

EASTCHEAP

20,000

NATWEST

BISHOPSGATE

18,000

Broad Street House

EC2

yes

PRINCE'S ROAD

18,000

1 Bank Buildings

EC2R 8EU

yes

BISHOPSGATE

18,000

HACKETT LTD

117

EC2M 3TH

yes

LOTHBURY

18,000

BANK OF ENGLAND

EC2R 7DB

yes

CHEAPSIDE

18,000

SPEAR LEEDS & KELLOG GLOBAL MA

138

EC2V 6LT

yes

CHEAPSIDE

18,000

DELI BOX

126

EC2V 6BT

yes

GRACECHURCH STREET

18,000

ROOM UNDERWRITING SYSTEMS LTD

EC3V 0EE

yes

LIVERPOOL STREET

17,000

GREAT EASTERN HOTEL

EC2M 7QN

yes

LIVERPOOL STREET

17,000

GREAT EASTERN HOTEL

EC2M 7QN

yes

LIVERPOOL STREET

17,000

MOWLEM PLC

EC2M 7PR

yes

GRACECHURCH STREET

17,000

CONTINENTAL INSURANCE CO LTD

C N A HOUSE

EC3V 0DL

yes

THREADNEEDLE STREET

16,000

BANK OF ENGLAND

BANK BUILDINGS

EC2R 8EU

yes

WALBROOK

16,000

SKY CAPITAL UK LTD

WALBROOK HOUSE 23-29

EC4N 8BT

yes

WALBROOK

16,000

SKY CAPITAL UK LTD

WALBROOK HOUSE 23-29

EC4N 8BT

yes

WALBROOK

16,000

EC4N 8BN

yes

NEWGATE STREET

15,000

EC1A 7AJ

yes

BISHOPSGATE

15,000

EC2N 4BQ

yes

CANNON STREET

14,000

EC4N 6JJ

LEADENHALL STREET

14,000

LEADENHALL STREET

14,000

LEADENHALL STREET

QUEEN VICTORIA STREET

EC2R 8NA

yes

EC2R 8EL

yes yes yes

23-29

EC3M 1AH

CHEAPSIDE HOUSE

38 BRITISH TELECOM

BT CENTRE

4 Burger King

40-42

yes

EC2N 4BQ

BENJY'S TAKE AW AY

EC3A 1AB

14,000

BENJY'S TAKE AW AY

EC3A 1AB

14,000

CITY OF LONDON MAGISTRATES COU

EC4N 4XY

BISHOPSGATE

14,000

PREBON TECHNOLOGY GROUP

164

EC2M 4LZ

yes

BISHOPSGATE

14,000

PREBON TECHNOLOGY GROUP

FARRINGDON ROAD

13,000

THE NEWGATE GALLERY

BISHOPSGATE

13,000

BISHOPSGATE

41 42

EC2M 4LZ

yes

59-60

164 BATH HOUSE 59-60

EC1A 2FD

NATWEST

THE GIBSON HALL

EC2N 3BA

13,000

SHAREHOLDER COMMUNICATIONS PLC

CROSBY COURT

EC2N 4AF

LIVERPOOL STREET

13,000

NEXT RETAIL LTD

34-37

EC2M 7PP

yes

LIVERPOOL STREET

13,000

CLAIRES ACCESSORIES

LIVERPOOL STREET STATION

EC2M 7PY

yes

POULTRY

13,000

ROYAL BANK INSURANCE SERVICES

SCOTTISH LIFE HOUSE

EC2R 8NA

yes

CHEAPSIDE

13,000

THE ROYAL BANK OF SCOTLAND PLC

32-34

EC2V 6DJ

yes

CHEAPSIDE

13,000

SPEAR LEEDS & KELLOG GLOBAL MA

138

CHEAPSIDE HOUSE

EC2V 6LT

yes yes

34-37

LUDGATE HILL

13,000

EC4M 7DR

LUDGATE HILL

13,000

W H SMITH LTD

EC4M 7JH

yes

CANNON STREET

13,000

BOOTS THE CHEMISTS LTD

EC4N 6HL

yes

CANNON STREET

13,000

THE CARPHONE W AREHOUSE

EC4N 6HT

yes

CANNON STREET

13,000

KIRKPATRICK & LOCKHART NICHOLS

110

EC4N 6AR

yes

FENCHURCH STREET

13,000

DRESDNER KLEINWORT BENSON

EC3M 3BE

yes

QUEEN VICTORIA STREET

12,000

CITY OF LONDON MAGISTRATES COU

EC4N 4XY

BISHOPSGATE

12,000

SNAPPY SNAPS

220

EC2M 4QD

yes

MOORGATE

12,000

HABIB BANK A G ZURICH

EC2R 6JJ

yes

FENCHURCH STREET

12,000

MANPOWER PLC

HABIB HOUSE

EC3M 4BT

yes

KING WILLIAM STREET

12,000

STARBUCKS COFFEE CO LTD

EC4N 7BJ

yes

NEW BRIDGE STREET

12,000

BAKER & MCKENZIE

100

EC4V 6JA

yes

FLEET STREET

12,000

OLD BELL TAVERN

EC4Y 1DH

yes

FLEET STREET

12,000

REFRESH JUICE BAR

EC4Y 1HY

yes

NEW BRIDGE STREET

12,000

15 N B S CHAMBERS

EC4V 6AU

yes

PETER'S HILL

12,000

PETER'S HILL

12,000

FENCHURCH STREET

12,000

HALIFAX PLC

MOORFIELDS

11,000

BOOTS THE CHEMISTS LTD

EC2Y 9AG

LONDON WALL

11,000

B C TOMS & CO

EC2M 5TP

BISHOPSGATE

11,000

KUONI TRAVEL LTD

BISHOPSGATE

11,000

AMBAC INTERNATIONAL

BISHOPSGATE

11,000

DANIEL STEWART & CO LTD

BISHOPSGATE

11,000

DANIEL STEWART & CO LTD

MOORGATE

11,000

THREADNEEDLE STREET

11,000

yes yes

RHINE SECURITIES LTD

159

EC3M 6AB

yes

EC2N 4AU

EC2N 4AW

EC2N 4AJ

EC2R 6AR

yes

EC2R 8HP

yes

60-64

HASILWOOD HOUSE 60-64

HOUBLON HOUSE 62-63

Rank StreetN ame

Flows between 08:00-19:00

Store

Building N o.

Building N ame

Postcode

HOUBLON HOUSE 62-63

EC2R 8HP

ObservedFlows yes

4 CREED COURT

EC4M 7AA

yes

EC4V 6BW

yes

LUDGATE CIRCUS POST OFFICE 16-18

EC4V 6HX

yes

THREADNEEDLE STREET

11,000

RHINE SECURITIES LTD

LUDGATE HILL

11,000

DEWAR HOGAN SOLICITORS

NEW BRIDGE STREET

11,000

S S L INTERNATIONAL PLC

NEW BRIDGE STREET

11,000

POST OFFICE

QUEEN VICTORIA STREET

11,000

M B C CONSULTING

CANNON STREET

11,000

LIVERPOOL STREET

10,000

RAILWAY TAVERN

CHEAPSIDE

10,000

THE CARPHONE W AREHOUSE

CHEAPSIDE

10,000

DAVID CLULOW OPTICIANS

CHEAPSIDE

10,000

NATIONWIDE BLDG SOC

CORNHILL

10,000

Molton Brown

CORNHILL

10,000

Lay & W heeler

BISHOPSGATE

10,000

THE NEW TECHNOLOGY GROUP LTD

199

BISHOPSGATE ARCADE

10,000

U F J INTERNATIONAL

EC2A 2JL

yes

BISHOPSGATE ARCADE

10,000

KAREN MILLEN

EC2M 3YD

yes

BISHOPSGATE

10,000

SOMPOJAPAN INSURANCE INC

NEW BRIDGE STREET

10,000

O'NEILL'S

FLEET STREET

10,000

BARCLAYS BANK PLC

ELDON STREET

9,000

PRET A MANGER

ELDON STREET

9,000

FARRINGDON STREET

93 94

5 35 16-18 77

EC4V 4AY

yes

EC4N 6LY

yes

EC2M 7NX

108-110

EC2V 6DT

EC2V 6DY

62-63

EC2V 6BP

EC3V 3LP

yes

EC3V 3ND

yes

EC2M 3TY

yes

BROADGATE COURT

155

EC2M 3TQ

yes

EC4V 6AA

yes

EC4Y 1ET

yes

EC2M 7LA

PRET A MANGER

EC2M 7LA

9,000

THE CARRIAGE HOUSE

EC4A 4BD

FARRINGDON STREET

9,000

REUTERS

LONDON WALL

9,000

CAFE JAIPUR LTD

2 to 3

34-35

MERIDIAN HOUSE 34-35

EC4A 4HL

EC2M 5TE

MOORGATE

9,000

Moorgate Hall

CANNON STREET

9,000

S2 Card Services Ltd.

155

MOORGATE HALL

EC2M 6XB

yes

47-53

WATLING HOUSE

EC4M 5SH

yes

MOORGATE

9,000

ERNEST JONES

105

ALDGATE HIGH STREET

9,000

RAW COMMUNICATIONS

ALDGATE HOUSE

EC2M 6SL

yes

EC3N 1AH

ALDGATE HIGH STREET

9,000

THALES I S

MATRIX

yes

EC3N 1AH

100 QUEEN VICTORIA STREET

9,000

T ROWE PRICE INTERNATIONAL INC

yes

101 CANNON STREET

9,000

MASTERCARD/EUROPAY UK LTD

102 CANNON STREET

9,000

NICHOLSON & GRIFFIN

EC4N 6AE

yes

103 CANNON STREET

9,000

FRESH OPTIONS

129

EC4N 5AX

yes

104 GRACECHURCH STREET

9,000

CANOPIUS

EC3V 0BT

yes

105 FINSBURY CIRCUS

8,000

BP PLC

EC2M 7BA

106 MOORFIELDS

8,000

107 NEWGATE STREET

8,000

TONI & GUY

108 CAMOMILE STREET

8,000

MICHAEL SHOE CARE

109 FENCHURCH STREET

8,000

EMAILYOURCV.COM

110 FENCHURCH STREET

8,000

TRANSPERFECT TRANSLATIONS LTD

120

EC3M 5BA

111 HIGH HOLBORN

8,000

KINKO'S LTD

WC1V 7PE

yes

112 NEWGATE STREET

8,000

BRITISH TELECOM

113 LEADENHALL STREET

8,000

COMPUTERS IN THE CITY LTD

114 LEADENHALL STREET

8,000

REYNOLDS PORTER CHAMBERLAIN

115 FENCHURCH STREET

8,000

ASSOCIATION OF LLOYD'S MEMBERS

116 CORNHILL

8,000

CORPNEX PLC

47-53

BRITANNIC HOUSE 1-6 18-20

EC4N 4TZ

yes

EC4M 5SH

yes

EC2Y 9AA

EC1A 7AA

EC3A 7BH

141

EC3M 6BL

123-124

326-328

36-38

123-124

326-328 BT CENTRE

36-38

EC1A 7AJ

yes

EC3A 2BJ

yes

EC3A 1AT

yes

100

EC3M 5LG

yes

EC3V 3ND

yes

117 EASTCHEAP

8,000

BANK SEPAH INTERNATIONAL PLC

118 KING WILLIAM STREET

8,000

SUMITOMO MITSUI ASSET MANAGEME

5 to 7

EC3M 1JT

yes

EC4N 7BP

yes

119 FENCHURCH STREET

8,000

H SB C

120 FENCHURCH STREET

8,000

BENJY'S TAKE AW AY

EC3M 4BA

yes

107

EC3M 5JF

121 LONDON STREET

8,000

A I G EUROPE (UK) LTD

yes

EC3M 4AB

yes

122 FISH STREET HILL

8,000

SNAX

123 LONG LANE

7,000

Extra time (across from)

EC3R 6BR

yes

124 NEWGATE STREET

7,000

GOLDMAN SACHS

125 NEWGATE STREET

7,000

GOLDMAN SACHS

126 OLD BROAD STREET

7,000

127 FLEET STREET

7,000

128 FLEET STREET

PHOENIX HOUSE

COMMERCIAL UNION HOUSE 1-5

EC1A 9HA

EC1A 7HD

EC2N 1HT

MORGAN COLE

167

EC4A 2JB

7,000

SNAPPY SNAPS

EC4Y 1JU

129 QUEEN STREET

7,000

GRESHAM FINANCIAL SYSTEMS LTD

EC4R 1BB

130 LIME STREET

7,000

BEAUFORTS WINE BAR

EC3M 7HS

131 FETTER LANE

7,000

JSAINSBURY PLC

EC1N 2HT

yes

132 HOLBORN

7,000

BURGER KING (UK) LTD

EC1N 2LE

yes

133 LONDON WALL

7,000

CAFFE NERO

EC2M 5NG

yes

134 LONDON WALL

7,000

AMOS TRUST

EC2M 5ND

yes

135 QUEEN VICTORIA STREET

7,000

T ROWE PRICE INTERNATIONAL INC

EC4N 4TZ

yes

136 CANNON STREET

7,000

CANNON CAPITAL

145

EC4N 5BQ

yes

137 GRACECHURCH STREET

7,000

CONTINENTAL INSURANCE CO LTD

EC3V 0DL

yes

138 DEVONSHIRE ROW

6,000

139 OLD BROAD STREET

6,000

140 ST MARTIN'S LE GRAND 141 ST MARTIN'S LE GRAND 142 GRESHAM STREET

6,000

143 GRESHAM STREET

6,000

C N A HOUSE

EC2M 4RH

LA SENZA PLC

EC2M 1RX

6,000

NOMURA CAPITAL MANAGEMENT (UK)

NOMURA HOUSE

EC1A 4NT

6,000

NOMURA CAPITAL MANAGEMENT (UK)

NOMURA HOUSE

EC1A 4NT

EC2V 7PD

Rank StreetN ame

Flows between 08:00-19:00

Store

Building N o.

Building N ame

Postcode

ObservedFlows

144 HOUNDSDITCH

6,000

THE OLD MONK

128

EC2M 4HX

145 OLD BROAD STREET

6,000

BOOTS THE CHEMISTS LTD

EC2M 1RX

146 DUKE'S PLACE

6,000

CAPITA INSURANCE SERVICES

147 BUCKLERSBURY

6,000

ALLISON MITCHELL LTD

148 FLEET STREET

6,000

YE OLDE COCK TAVERN

149 FLEET STREET

6,000

COUTTS TRADING

150 QUEEN STREET

6,000

151 LOW ER THAMES STREET

6,000

152 HOLBORN VIADUCT

6,000

CITY TEMPLE

153 HOLBORN VIADUCT

6,000

REMUS PARTNERS LLP

154 HOLBORN VIADUCT

6,000

1ST TRANSLATION CO LTD

155 HOLBORN VIADUCT

6,000

156 HOLBORN VIADUCT

6,000

157 ST PAUL'S CHURCH YARD

6,000

158 QUEEN VICTORIA STREET

6,000

159 ROPEMAKER STREET

5,000

STEMCOR LTD

160 ROPEMAKER STREET

5,000

STEMCOR LTD

161 ST BRIDE STREET

5,000

162 ST MARTIN'S LE GRAND

5,000

PARITY GROUP PLC

163 ST MARTIN'S LE GRAND

5,000

164 OLD BROAD STREET

5,000

165 OLD BROAD STREET

EASTGATE HOUSE

EC3A 7NH

BUCKLERSBURY HOUSE

EC4N 8EL

EC4Y 1AA

190

EC4A 2AG

EC4N 1SR

W ELL COURT HOUSE

EC3R 6DT

EC1A 2DE

yes

FITZ-EYLW IN HOUSE

EC1A 2BP

yes

GRESHAM HOUSE

EC1A 2BN

yes

ENDSLEIGH INSURANCE SERVICES L

2 to 5

EC1A 2AA

yes

STARBUCKS

2 to 3

EC4M 7RA

yes

BRIDGE CHAMBERS

EC4V 4DG

yes

CITYPOINT

EC2Y 9ST

CITYPOINT

EC2Y 9ST

ST. MARTINS HOUSE

EC1A 4EN

PARITY GROUP PLC

ST. MARTINS HOUSE

EC1A 4EN

K B C ALTERNATE INVESTMENT MAN

111

5,000

ARCHIPELAGO EUROPE

166 OLD BROAD STREET

5,000

H SB C

117

167 ST MARY AXE

5,000

BANCA NAZIONALE DEL LAVORO

168 THROGMORTON STREET

5,000

LIGHTHOUSE INDEPENDENT FINANCI

169 QUEEN STREET

5,000

170 BYW ARD STREET

5,000

CHEZ CHERARD

171 ALDERSGATE STREET

5,000

Vecchio Parioli

172 NEW BRIDGE STREET

5,000

POST OFFICE

16-18

173 BLOMFIELD STREET

4,000

WAREHOUSE

174 GRESHAM STREET

4,000

WORSHIPFUL COMPANY OF WAX CHAN

175 GRESHAM STREET

4,000

JONES LANG LA SALLE

176 GRESHAM STREET

4,000

SALANS HERTZFELD & HEILBRONN H

177 KING STREET

4,000

HUNGARIAN INTERNATIONAL FINANC

178 FENCHURCH PLACE

4,000

VALENTE WINE BAR

179 MOORGATE

4,000

Habib Bank

36-42

180 LONG LANE

4,000

BISTRO A VIN

62-63

181 OLD BAILEY

4,000

182 LONG LANE

2,000

183 FARRINGDON STREET

2,000

184 SHOE LANE 185 FARRINGDON STREET

yes 171

EC2N 1AP

INTERNATIONAL FINANCIAL CENTRE

EC2N 1HQ

EC2N 1AH

FITZWILLIAM HOUSE

EC3A 8NA

EC2N 2AN

EC4N 6LY

EC3R 5BA

133-134

EC1A 4JQ

yes

LUDGATE CIRCUS POST OFFICE 16-18

EC4V 6HX

yes

EC2M 7BD

WAX CHANDLERS HALL

EC2V 7AD

EC2V 7JD

14-18

EC2V 7NN

ENERGY HOUSE

EC2V 8EA

EC3M 4AJ

EC2R 6JJ

yes

62-63

EC1A 9EJ

yes

EC4M 7BG

yes

CHAMBERS & PARTNERS

EC1A 9HL

B N B TRAINING

EC4A 4EU

yes

2,000

DELOITTE & TOUCHE LLP

EC4A 3BQ

yes

2,000

AMDOCS (UK) LTD

EC4A 4EP

yes

FLEETWAY HOUSE

appendix 5 - Network Audience Calculations To establish the average footfall for a Renew units in the City of London, 100 footfall counts established by ISP were averaged by Media Metrica to determine the traffic over an average trading day (6:00am to 11:00pm). This footfall count will be re-calibrated for the network once the units are installed and operational using passive technologies and an on-going collaboration with Intelligent Space.

Top 100 unit flows between 08:00 - 19:00

14,090

Top 100 unit flows between 06:00 - 23:00

15,588

*Increased by 9.6% to cover 6:00 - 8:00 am and 19:00 - 23:00

Network Values Morning - lunchtime PEAK MORNING

PEAK LUNCHTIME

Network footfall audience

74,755

322,370

127,907

304,755

Yearly flows (250 trading days year) Percentage of full day footfall

18,688,665

80,592,527

31,976,669

76,188,632

4.8%

20.7%

8.2%

19.6%

Afternoon - evening PEAK EVENING

Network footfall audience

264,803

322,169

142,017

Yearly flows (250 trading days year) Percentage of full day footfall

6,200,808

80,542,280

35,504,334

20.7%

9.1%

17.0%

558,776 11,558,776 389,693,916

Daily footfall Yearly footfall