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
19
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
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 Transport’s good practice casebook “Walking: The Way Ahead�. 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 ISP’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 ISP’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
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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, it’s percentage of the maximum flow for that individual flow location. ISP’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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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).
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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.
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The pattern of movement in the model
PSG A TE
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MONUMENT
é
HS
CORNHILL
UR C
LIVERPOOL STREET
A
C EC H
G DON ST
ST. PAUL'S
é
MANSION HOUSE
OS Licence Number: 1000232436
FA RRIN
BLACKFRIARS
CH
A
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HO
T ES US
HO
LBO R
NV
IA D UC T
é é
FARRINGDON
BARBICAN
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CHEA PSID
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LONDON WALL
MOORGATE
é
BANK
é
CITY RD
Modelled annual pedestrian flows in the City of London
GR
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C FEN
HU
RC H
ST
TOWER HILL
ALDGATE
é
TOWER GATEWAY DLR
é
ALDGATE EAST
Low
Millions of pedestrians
High
B ISHO
Annual Flow
é
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).
17
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 ISP’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 ‘desire lines’ 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.
18
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).
19
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 ‘graph measures’ 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.
20
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 ‘stationary gate method’ 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.
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22
appendix 3 - Gate Identification
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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
1
BISHOPSGATE
29,000
PRET A MANGER
192
EC2M 4NR
2
MOORGATE
28,000
MARUBENI EUROPE PLC
120
EC2M 6SS
yes yes
3
MOORGATE
28,000
BP PLC
BRITANNIC HOUSE 1-6
EC2M 7BA
yes
4
MOORGATE
28,000
NEXT RETAIL LTD
88-92
88-92
EC2M 6SE
yes
5
BISHOPSGATE
27,000
THE OLD MONK
128
EC2M 4HX
yes
6
BISHOPSGATE
26,000
K FC
180
EC2M 4NQ
yes
7
KING WILLIAM STREET
25,000
yes
8
KING WILLIAM STREET
25,000
yes
9
POULTRY
22,000
10
POULTRY
22,000
ROYAL BANK INSURANCE SERVICES
36
SCOTTISH LIFE HOUSE
11
KING WILLIAM STREET
22,000
12
KING WILLIAM STREET
22,000
13
EASTCHEAP
20,000
NATWEST
4
14
BISHOPSGATE
18,000
Broad Street House
55
EC2
yes
15
PRINCE'S ROAD
18,000
1 Bank Buildings
1
EC2R 8EU
yes
16
BISHOPSGATE
18,000
HACKETT LTD
117
EC2M 3TH
yes
17
LOTHBURY
18,000
BANK OF ENGLAND
1
EC2R 7DB
yes
18
CHEAPSIDE
18,000
SPEAR LEEDS & KELLOG GLOBAL MA
138
EC2V 6LT
yes
19
CHEAPSIDE
18,000
DELI BOX
126
EC2V 6BT
yes
20
GRACECHURCH STREET
18,000
ROOM UNDERWRITING SYSTEMS LTD
55
EC3V 0EE
yes
21
LIVERPOOL STREET
17,000
GREAT EASTERN HOTEL
40
EC2M 7QN
yes
22
LIVERPOOL STREET
17,000
GREAT EASTERN HOTEL
40
EC2M 7QN
yes
23
LIVERPOOL STREET
17,000
MOWLEM PLC
50
EC2M 7PR
yes
24
GRACECHURCH STREET
17,000
CONTINENTAL INSURANCE CO LTD
77
C N A HOUSE
EC3V 0DL
yes
25
THREADNEEDLE STREET
16,000
BANK OF ENGLAND
BANK BUILDINGS
EC2R 8EU
yes
26
WALBROOK
16,000
SKY CAPITAL UK LTD
WALBROOK HOUSE 23-29
EC4N 8BT
yes
27
WALBROOK
16,000
SKY CAPITAL UK LTD
WALBROOK HOUSE 23-29
EC4N 8BT
yes
28
WALBROOK
16,000
EC4N 8BN
yes
29
NEWGATE STREET
15,000
EC1A 7AJ
yes
30
BISHOPSGATE
15,000
EC2N 4BQ
yes
31
CANNON STREET
14,000
EC4N 6JJ
no
32
LEADENHALL STREET
14,000
33
LEADENHALL STREET
14,000
34
LEADENHALL STREET
35
QUEEN VICTORIA STREET
36
3
EC2R 8NA
yes
EC2R 8EL
yes yes yes
23-29
EC3M 1AH
CHEAPSIDE HOUSE
38 BRITISH TELECOM
81
BT CENTRE
4 Burger King
40-42
40-42
yes
4
EC2N 4BQ
no
BENJY'S TAKE AW AY
26
EC3A 1AB
no
14,000
BENJY'S TAKE AW AY
26
EC3A 1AB
no
14,000
CITY OF LONDON MAGISTRATES COU
1
EC4N 4XY
no
BISHOPSGATE
14,000
PREBON TECHNOLOGY GROUP
164
EC2M 4LZ
yes
37
BISHOPSGATE
14,000
PREBON TECHNOLOGY GROUP
38
FARRINGDON ROAD
13,000
THE NEWGATE GALLERY
39
BISHOPSGATE
13,000
40
BISHOPSGATE
41 42
EC2M 4LZ
yes
59-60
164 BATH HOUSE 59-60
EC1A 2FD
no
NATWEST
13
THE GIBSON HALL
EC2N 3BA
no
13,000
SHAREHOLDER COMMUNICATIONS PLC
38
CROSBY COURT
EC2N 4AF
no
LIVERPOOL STREET
13,000
NEXT RETAIL LTD
34-37
EC2M 7PP
yes
LIVERPOOL STREET
13,000
CLAIRES ACCESSORIES
16
LIVERPOOL STREET STATION
EC2M 7PY
yes
43
POULTRY
13,000
ROYAL BANK INSURANCE SERVICES
36
SCOTTISH LIFE HOUSE
EC2R 8NA
yes
44
CHEAPSIDE
13,000
THE ROYAL BANK OF SCOTLAND PLC
32-34
EC2V 6DJ
yes
45
CHEAPSIDE
13,000
SPEAR LEEDS & KELLOG GLOBAL MA
138
CHEAPSIDE HOUSE
EC2V 6LT
yes yes
34-37
46
LUDGATE HILL
13,000
26
EC4M 7DR
47
LUDGATE HILL
13,000
W H SMITH LTD
65
EC4M 7JH
yes
48
CANNON STREET
13,000
BOOTS THE CHEMISTS LTD
80
EC4N 6HL
yes
49
CANNON STREET
13,000
THE CARPHONE W AREHOUSE
88
EC4N 6HT
yes
50
CANNON STREET
13,000
KIRKPATRICK & LOCKHART NICHOLS
110
EC4N 6AR
yes
51
FENCHURCH STREET
13,000
DRESDNER KLEINWORT BENSON
10
EC3M 3BE
yes
52
QUEEN VICTORIA STREET
12,000
CITY OF LONDON MAGISTRATES COU
1
EC4N 4XY
no
53
BISHOPSGATE
12,000
SNAPPY SNAPS
220
EC2M 4QD
yes
54
MOORGATE
12,000
HABIB BANK A G ZURICH
42
EC2R 6JJ
yes
55
FENCHURCH STREET
12,000
MANPOWER PLC
78
HABIB HOUSE
EC3M 4BT
yes
56
KING WILLIAM STREET
12,000
STARBUCKS COFFEE CO LTD
87
EC4N 7BJ
yes
57
NEW BRIDGE STREET
12,000
BAKER & MCKENZIE
100
EC4V 6JA
yes
58
FLEET STREET
12,000
OLD BELL TAVERN
95
EC4Y 1DH
yes
59
FLEET STREET
12,000
REFRESH JUICE BAR
82
EC4Y 1HY
yes
60
NEW BRIDGE STREET
12,000
15 N B S CHAMBERS
15
EC4V 6AU
yes
61
PETER'S HILL
12,000
62
PETER'S HILL
12,000
63
FENCHURCH STREET
12,000
HALIFAX PLC
64
MOORFIELDS
11,000
BOOTS THE CHEMISTS LTD
17
EC2Y 9AG
no
65
LONDON WALL
11,000
B C TOMS & CO
64
EC2M 5TP
no
66
BISHOPSGATE
11,000
KUONI TRAVEL LTD
67
BISHOPSGATE
11,000
AMBAC INTERNATIONAL
68
BISHOPSGATE
11,000
DANIEL STEWART & CO LTD
69
BISHOPSGATE
11,000
DANIEL STEWART & CO LTD
70
MOORGATE
11,000
71
THREADNEEDLE STREET
11,000
yes yes
RHINE SECURITIES LTD
159
EC3M 6AB
84
yes
EC2N 4AU
no
EC2N 4AW
no
48
EC2N 4AJ
no
48
EC2N 4AJ
no
19
EC2R 6AR
yes
EC2R 8HP
yes
60-64
HASILWOOD HOUSE 60-64
HOUBLON HOUSE 62-63
24
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
72
THREADNEEDLE STREET
11,000
RHINE SECURITIES LTD
73
LUDGATE HILL
11,000
DEWAR HOGAN SOLICITORS
74
NEW BRIDGE STREET
11,000
S S L INTERNATIONAL PLC
75
NEW BRIDGE STREET
11,000
POST OFFICE
76
QUEEN VICTORIA STREET
11,000
M B C CONSULTING
77
CANNON STREET
11,000
78
LIVERPOOL STREET
10,000
RAILWAY TAVERN
79
CHEAPSIDE
10,000
THE CARPHONE W AREHOUSE
80
CHEAPSIDE
10,000
DAVID CLULOW OPTICIANS
81
CHEAPSIDE
10,000
NATIONWIDE BLDG SOC
82
CORNHILL
10,000
Molton Brown
83
CORNHILL
10,000
Lay & W heeler
84
BISHOPSGATE
10,000
THE NEW TECHNOLOGY GROUP LTD
199
85
BISHOPSGATE ARCADE
10,000
U F J INTERNATIONAL
1
EC2A 2JL
yes
86
BISHOPSGATE ARCADE
10,000
KAREN MILLEN
5
EC2M 3YD
yes
87
BISHOPSGATE
10,000
SOMPOJAPAN INSURANCE INC
88
NEW BRIDGE STREET
10,000
O'NEILL'S
89
FLEET STREET
10,000
BARCLAYS BANK PLC
90
ELDON STREET
9,000
PRET A MANGER
91
ELDON STREET
9,000
92
FARRINGDON STREET
93 94
5 35 16-18 77
EC4V 4AY
yes
52
EC4N 6LY
yes
15
EC2M 7NX
no
108-110
EC2V 6DT
no
EC2V 6DY
no
62-63
EC2V 6BP
no
27
EC3V 3LP
yes
33
EC3V 3ND
yes
EC2M 3TY
yes
99
BROADGATE COURT
155
EC2M 3TQ
yes
EC4V 6AA
yes
80
EC4Y 1ET
yes
17
EC2M 7LA
no
PRET A MANGER
17
EC2M 7LA
no
9,000
THE CARRIAGE HOUSE
54
EC4A 4BD
no
FARRINGDON STREET
9,000
REUTERS
LONDON WALL
9,000
CAFE JAIPUR LTD
2 to 3
34-35
MERIDIAN HOUSE 34-35
45
EC4A 4HL
no
EC2M 5TE
no
95
MOORGATE
9,000
Moorgate Hall
96
CANNON STREET
9,000
S2 Card Services Ltd.
155
MOORGATE HALL
EC2M 6XB
yes
47-53
WATLING HOUSE
EC4M 5SH
yes
97
MOORGATE
9,000
ERNEST JONES
105
98
ALDGATE HIGH STREET
9,000
RAW COMMUNICATIONS
33
ALDGATE HOUSE
EC2M 6SL
yes
EC3N 1AH
99
ALDGATE HIGH STREET
9,000
THALES I S
9
MATRIX
yes
EC3N 1AH
100 QUEEN VICTORIA STREET
9,000
T ROWE PRICE INTERNATIONAL INC
60
yes
101 CANNON STREET
9,000
MASTERCARD/EUROPAY UK LTD
102 CANNON STREET
9,000
NICHOLSON & GRIFFIN
74
EC4N 6AE
yes
103 CANNON STREET
9,000
FRESH OPTIONS
129
EC4N 5AX
yes
104 GRACECHURCH STREET
9,000
CANOPIUS
36
EC3V 0BT
yes
105 FINSBURY CIRCUS
8,000
BP PLC
EC2M 7BA
no
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
no
111 HIGH HOLBORN
8,000
KINKO'S LTD
WC1V 7PE
yes
112 NEWGATE STREET
8,000
BRITISH TELECOM
81
113 LEADENHALL STREET
8,000
COMPUTERS IN THE CITY LTD
50
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
47-53
BRITANNIC HOUSE 1-6 18-20
EC4N 4TZ
yes
EC4M 5SH
yes
EC2Y 9AA
no
EC1A 7AA
no
9
EC3A 7BH
no
141
EC3M 6BL
no
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
1
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
60
EC3M 4BA
yes
107
EC3M 5JF
121 LONDON STREET
8,000
A I G EUROPE (UK) LTD
58
yes
EC3M 4AB
yes
122 FISH STREET HILL
8,000
SNAX
41
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
18
PHOENIX HOUSE
COMMERCIAL UNION HOUSE 1-5
EC1A 9HA
no
10
EC1A 7HD
no
10
EC1A 7HD
no
27
EC2N 1HT
no
MORGAN COLE
167
EC4A 2JB
no
7,000
SNAPPY SNAPS
59
EC4Y 1JU
no
129 QUEEN STREET
7,000
GRESHAM FINANCIAL SYSTEMS LTD
28
EC4R 1BB
no
130 LIME STREET
7,000
BEAUFORTS WINE BAR
24
EC3M 7HS
no
131 FETTER LANE
7,000
JSAINSBURY PLC
33
EC1N 2HT
yes
132 HOLBORN
7,000
BURGER KING (UK) LTD
14
EC1N 2LE
yes
133 LONDON WALL
7,000
CAFFE NERO
72
EC2M 5NG
yes
134 LONDON WALL
7,000
AMOS TRUST
83
EC2M 5ND
yes
135 QUEEN VICTORIA STREET
7,000
T ROWE PRICE INTERNATIONAL INC
60
EC4N 4TZ
yes
136 CANNON STREET
7,000
CANNON CAPITAL
145
EC4N 5BQ
yes
137 GRACECHURCH STREET
7,000
CONTINENTAL INSURANCE CO LTD
77
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
2
EC2M 4RH
no
LA SENZA PLC
57
EC2M 1RX
no
6,000
NOMURA CAPITAL MANAGEMENT (UK)
1
NOMURA HOUSE
EC1A 4NT
no
6,000
NOMURA CAPITAL MANAGEMENT (UK)
1
NOMURA HOUSE
EC1A 4NT
no
24
EC2V 7PD
no
24
EC2V 7PD
no
25
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
no
145 OLD BROAD STREET
6,000
BOOTS THE CHEMISTS LTD
54
EC2M 1RX
no
146 DUKE'S PLACE
6,000
CAPITA INSURANCE SERVICES
40
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
25
154 HOLBORN VIADUCT
6,000
1ST TRANSLATION CO LTD
24
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
no
BUCKLERSBURY HOUSE
EC4N 8EL
no
22
EC4Y 1AA
no
190
EC4A 2AG
no
EC4N 1SR
no
10
W ELL COURT HOUSE
50
EC3R 6DT
no
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
1
CITYPOINT
EC2Y 9ST
no
1
CITYPOINT
EC2Y 9ST
no
16
ST. MARTINS HOUSE
EC1A 4EN
no
PARITY GROUP PLC
16
ST. MARTINS HOUSE
EC1A 4EN
no
K B C ALTERNATE INVESTMENT MAN
111
5,000
ARCHIPELAGO EUROPE
25
166 OLD BROAD STREET
5,000
H SB C
117
167 ST MARY AXE
5,000
BANCA NAZIONALE DEL LAVORO
10
168 THROGMORTON STREET
5,000
LIGHTHOUSE INDEPENDENT FINANCI
26
169 QUEEN STREET
5,000
170 BYW ARD STREET
5,000
CHEZ CHERARD
171 ALDERSGATE STREET
5,000
Vecchio Parioli
99
172 NEW BRIDGE STREET
5,000
POST OFFICE
16-18
173 BLOMFIELD STREET
4,000
WAREHOUSE
34
174 GRESHAM STREET
4,000
WORSHIPFUL COMPANY OF WAX CHAN
6
175 GRESHAM STREET
4,000
JONES LANG LA SALLE
10
176 GRESHAM STREET
4,000
SALANS HERTZFELD & HEILBRONN H
177 KING STREET
4,000
HUNGARIAN INTERNATIONAL FINANC
9
178 FENCHURCH PLACE
4,000
VALENTE WINE BAR
5
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
no
EC2N 1AP
no
INTERNATIONAL FINANCIAL CENTRE
EC2N 1HQ
no
EC2N 1AH
no
FITZWILLIAM HOUSE
EC3A 8NA
no
EC2N 2AN
no
52
EC4N 6LY
no
14
EC3R 5BA
no
133-134
EC1A 4JQ
yes
LUDGATE CIRCUS POST OFFICE 16-18
EC4V 6HX
yes
EC2M 7BD
no
WAX CHANDLERS HALL
EC2V 7AD
no
EC2V 7JD
no
14-18
EC2V 7NN
no
ENERGY HOUSE
EC2V 8EA
no
EC3M 4AJ
no
EC2R 6JJ
yes
62-63
EC1A 9EJ
yes
4
EC4M 7BG
yes
CHAMBERS & PARTNERS
23
EC1A 9HL
no
B N B TRAINING
28
EC4A 4EU
yes
2,000
DELOITTE & TOUCHE LLP
66
EC4A 3BQ
yes
2,000
AMDOCS (UK) LTD
25
EC4A 4EP
yes
FLEETWAY HOUSE
26
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
6
7
8
9
10
11
12
13
AM
AM
AM
AM
AM
AM
PM
PM
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
14
15
16
17
18
19
20
21
PM
PM
PM
PM
PM
PM
PM
PM
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
27