Street catalogue

The catalogue provides a visual and numeric reference to streets around the world. It allows users to compare the accessibility and connectivity measurements of different streets with time-lapse videos and corresponding pedestrian counts of the same streets. Videos captured during different times of the day allow you to examine temporal changes in the character of a street between times of a day, days of a week or times of the year. Read more

Submit street
Case ID
Country
City
Street name
Date & Time
Weekday
Footfall per hour
Betweenness
Access to Businesses
Access to Transit
Access to Floor Area
From
To
From
To
min
max
min
max
min
max
min
max
min
max
min
max
10th Avenue
#1 · New York, USA
23:30
15/03/2014
Sun
Weekday
1108
Footfall per hour
621
Betweenness
597
Businesses
 
Transit
2447604
Floor Area
Tenth Avenue, known as Amsterdam Avenue between 59th Street and 193rd Street, is a north-south thoroughfare on the West Side of Manhattan in New York City. It carries uptown (northbound) traffic as far as West 110th Street – also known as Cathedral Parkway for the Cathedral Church of St. John the Divine – after which it continues as a two-way street.
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Video by: Raul Kalvo
Swanston Street
#2 · Melbourne, Australia
11:00
30/03/2015
Mon
Weekday
2223
Footfall per hour
239
Betweenness
1071
Businesses
24
Transit
124000
Floor Area
Swanston Street is a major thoroughfare in the centre of Melbourne, Australia. It is historically one of the main streets of central Melbourne, laid out in 1837 as part of the Hoddle Grid, the layout of major streets that makes up the central business district. The street runs through the middle of Melbourne's city centre, just to the east of the centre of the rectangular Hoddle Grid. To the south, it crosses the Princes Bridge over the Yarra River before becoming St Kilda Road. As it runs north and leaves the CBD, it passes the University of Melbourne, and ends at the Melbourne General Cemetery.
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Video by: Raul Kalvo
Hudson Street
#3 · New York, USA
18:57
15/03/2015
Sun
Weekday
680
Footfall per hour
1288
Betweenness
801
Businesses
 
Transit
1768651
Floor Area
Hudson Street is a north-south oriented street in the New York City borough of Manhattan running from Tribeca to the south, through Hudson Square and Greenwich Village, to the Meatpacking District.
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Video by: Raul Kalvo
Lujiazui Pedestrian Bridge
#5 · Shanghai, China
12:30
02/04/2015
Thu
Weekday
1500
Footfall per hour
18
Betweenness
343
Businesses
13
Transit
 
Floor Area
The Lujiazui Bridge connects office and retail buildings in the Pudong financial district of Shanghai to leisure areas, shops, cafes and the waterfront situated across the seemingly interminable expanse of giant roadways. The bridge sits almost 20 feet above the street, with numerous escalator stairway entrances and exits.
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Video by: Andres Sevtsuk
Main St
#6 · Cambridge, USA
14:50
14/09/2015
Mon
Weekday
411
Footfall per hour
20
Betweenness
128
Businesses
6.8
Transit
154969
Floor Area
The section of Main St. in the video lies around 300 meters from the Kendall/MIT subway station at the heart of the MIT campus. The site is surrounded by large, multistory academic and lab structures as well as private office buildings and commercial establishments on the ground floor. The video is shot on a Monday afternoon.
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Video by: Andres Sevtsuk
Brattle St
#7 · Cambridge, USA
15:50
14/09/2015
Mon
Weekday
904
Footfall per hour
783
Betweenness
647
Businesses
19.2
Transit
251571
Floor Area
Brattle St at Harvard Square has a number of a popular shopping destinations, street cafes and restaurant. The timelapse is captured at about 50 meters from the nearest Harvard Square subway entrance. The space in front of the camera contains a large sidewalk with ample seating areas, which also functions as a public plaza for street musicians and people-watchers.
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Video by: Andres Sevtsuk
Cambridge Street
#8 · Cambridge, MA, USA
12:15
02/09/2015
Fri
Weekday
100
Footfall per hour
553
Betweenness
241
Businesses
8
Transit
284552
Floor Area
Dunkin Donuts on Cambridge St resides inside a Shell gas station. The observation focuses on retail business locations and explores how and why shop patronage to more or less identical stores varies from one location to another. The experiment tries to understand how much and what types of demand are necessary to economically sustain retailers.
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Video by: Vipavee Sirivatanaaksorn
Massachusetts Route 2
#9 · Cambridge MA, USA
09:15
10/05/2015
Mon
Weekday
24
Footfall per hour
100
Betweenness
48
Businesses
600
Transit
71572
Floor Area
Commercial stretch of MA Route 2 adjacent from Fresh Pond.
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Video by: Russel Koff
Cambridge Side Place
#10 · Cambridge MA, USA
18:00
05/10/2015
Mon
Weekday
960
Footfall per hour
 
Betweenness
248
Businesses
 
Transit
128334
Floor Area
Video by: Apoorva Shenvi
Third Street
#11 · Cambridge MA, USA
16:30
05/10/2015
Mon
Weekday
12
Footfall per hour
76
Betweenness
253
Businesses
13
Transit
266241
Floor Area
Video by: Isabel Cantada
Massachusetts Ave
#12 · Cambridge MA, USA
08:30
02/10/2015
Fri
Weekday
128
Footfall per hour
 
Betweenness
118
Businesses
800
Transit
214055
Floor Area
Video by: CristobalF
Massachusetts Ave
#13 · Cambridge, USA
10:30
02/10/2015
Fri
Weekday
344
Footfall per hour
4
Betweenness
213
Businesses
2800
Transit
254781
Floor Area
Video by: CristobalF
Memorial Drive
#14 · Cambridge, USA
14:45
05/10/2015
Mon
Weekday
100
Footfall per hour
79
Betweenness
39
Businesses
400
Transit
238655
Floor Area
Video by: Arianna Salazar
Main St
#15 · Cambridge MA, USA
09:00
05/10/2015
Mon
Weekday
764
Footfall per hour
311
Betweenness
390
Businesses
4000
Transit
256360
Floor Area
Video by: Apoorva Shenvi
Massachusetts Ave
#16 · Cambridge MA, USA
12:45
04/10/2015
Sun
Weekday
400
Footfall per hour
459
Betweenness
332
Businesses
600
Transit
367872
Floor Area
Video by: Rida Qadri
Massachusetts Ave
#17 · Cambridge MA, USA
13:30
05/10/2015
Mon
Weekday
552
Footfall per hour
 
Betweenness
476
Businesses
3700
Transit
314468
Floor Area
Video by: Marco Gorini
Harvard Square T-Station
#18 · Cambridge MA, USA
13:15
04/10/2015
Sun
Weekday
736
Footfall per hour
60
Betweenness
493
Businesses
18500
Transit
228602
Floor Area
Video by: John McCartin
Church Street
#19 · Cambridge MA, USA
13:45
04/10/2015
Sun
Weekday
316
Footfall per hour
13
Betweenness
605
Businesses
18500
Transit
230009
Floor Area
Video by: John McCartin
Eliot Street
#20 · Cambridge MA, USA
14:15
04/10/2015
Sun
Weekday
324
Footfall per hour
49
Betweenness
431
Businesses
15100
Transit
186879
Floor Area
Video by: John McCartin
Broadway
#21 · Cambridge mA, USA
15:45
05/10/2015
Mon
Weekday
172
Footfall per hour
 
Betweenness
181
Businesses
1200
Transit
182409
Floor Area
Video by: Marco Gorini
Massachusetts Route 2
#22 · Cambridge MA, USA
09:45
05/10/2015
 
Weekday
160
Footfall per hour
100
Betweenness
50
Businesses
400
Transit
83230
Floor Area
Video by: Elliot Kilham
Twin City Plaza 14 McGrath Hwy
#23 · Cambridge MA, USA
 
Weekday
88
Footfall per hour
575
Betweenness
260
Businesses
12
Transit
231293
Floor Area
Video by: Yue Shi


About


The Street Catalog aims to provide a visual and quantitative reference to pedestrian activity on selected streets around the world. A time lapse video, with an original duration of 15 minutes, is shown for each street, played back at 12 times the original speed. The videos describe the typical use patterns of the streets during shown weekdays and times. The video material is also used to count the number of pedestrians using the street, indicated as people per hour (see details below). In order to relate the visual video material to comparable quantitative indicators about the urban context around each street, four standardized metrics are shown for each case. These metrics describe the relative position of the street with regards to the surrounding land uses (Betweenness), the accessibility from the street to surrounding businesses, transit stops and overall gross floor area within a 400-meter walking radius around the camera location. The metrics are captured with the Urban Network Analysis Rhino toolbox, using data data survey from the sites or obtained from Open Street Map, Google Maps or other available source. The selection of indicators is narrowed down to only four complimentary metrics in order to allow streets from different parts of the world to be added with relative ease to the catalog. A PDF submission form allows you to submit new streets and help us expand the catalog. Please follow standard specifications of the four metrics as described below.

Footfall per hour

Describes the interpolated number of pedestrians per hour moving in either direction along the sidewalk in the visible video field. The count refers to a single sidewalk on only one side of the street, even if there are two sidewalks on both sides of a road. The original video clips typically capture a 15-minute observation period on a sidewalk, which are played back in time lapse videos at 12 times the original speed. The counted number of pedestrians observed in the said 15-minute period is generalized to an hour by multiplying by four (e.g.  40 pedestrians per 15 minutes equals 40*4=160 pedestrians per hour). A handy tool for performing the counts from time lapse videos is Google Chrome browser's Video Speed Controller, which allows you to slow the time lapse down for easier counting.

Betweenness

The betweenness from network analysis describes how in-between given origins and destinations on a network a particular location is, under the assumptions that travelers take either shortest, or near shortest paths from the origins to the destinations. The metric thus depends on what origins and destinations are used, at what walking radius and whether only shortest routes or also slightly longer routes are considered. The Street Catalog betweenness metric uses all business establishments, obtained from Google Maps in a 400 meter (1,300 ft) radius around the camera as origin points and all public transit stops found in the same radius as destinations. The metric effectively models predicted pedestrian flow from nearby businesses to nearby transit stations. The maximum allowable travel distance is set at 400 meters and walks can run on not only shortest paths, but paths that are up to 15% longer than shortest paths. Each of the paths from an origin to a destination that is up to 15% longer than the shortest path is given an equal probability. Betweenness was measured at the location of the camera (i.e. camera location is set as an Observer point in the Rhino UNA betweenness tool).

Businesses

Measures how many individual business establishments are found within a 400 meter network walk from the camera location. The data describing the business locations as points or coordinates is obtained from Google Maps or Open Street Map. The metric provides a basic indicator of how many potential trip destinations are found in the vicinity of the camera location, which are likely to affect the observed pedestrian traffic on the street.

Transit

Measures how many public transit stops are found within a 400 meter network walk from the camera location. Since stops are not equal and MRT stops tend to serve more riders than bus stops, the following convention was adopted for weighing the stops: An MRT (or subway) stop has a weight of "1000"; a light rail or tram stop a weight of "200"; and a bus stop a wight of "100". These weights roughly correspond to the differences in carrying capacity of the respective vehicles. An MRT train can carry up to 5 times more people than a tram and 10 times more people than a bus. If there is one MRT, one LRT and one bus stop within a 400 meter buffer around the camera, then the comined transit access result would show 1000+200+100=1300. Ideally, stop weights should also distinguish how many lines pass trhough each stop. Since such data is difficult to obtain in most cities, we have omitted this factor.

Floor Area

Measures how much gross floor area (GFA) in square meters is found in the buildings around the camera location within a 400 meter (1,300 ft) network radius. All buildings, regardless of type or function, are included as destinations for simplicity. The GFA numbers at the individual building level can be approximated from a site survey, obtained from axonometric views in Google Maps, precisely calculated from available data by multiplying the building footprint area with the number of floors, or obtained from city assessors records. Buildings of different size thus contribute differently to the result, with larger and nearer buildings creating a bigger impact on floor area accessibility.

Rerferences

Handy, S., & Niemeier, A. D. (1997). Measuring Accessibility: an exploration of issues and alternatives. Environment and Planning A, 29, 1175–1194.

Sevtsuk, A., Mekonnen, M., 2012, “Urban Network Analysis Toolbox,” International Journal of Geomatics and Spatial Analysis, vol. 22, no. 2, pp. pp. 287–305. PDF