1. Introduction
Urban Analyst (UA) analyses the structure and function of cities across the world. Each city can be viewed as an interactive map displaying several different properties or variables. These include socio-demographic conditions and the structure and function of transport systems. The platform also analyses relationships between individual variables, such as between socio-demographic conditions and frequency of transport services, or between distances to nearest schools and access to natural spaces.
UA also provides statistical comparisons between all cities, enabling comparisons across all UA cities of single variables, as well as relationships between any pair of variables, such as transport and socio-demographic disadvantage.
Finally, UA enables cities to “learn” from one another, by visualising how the properties of any chosen city can best be transformed to become more like the properties of any other chosen city. Paris, for example, has better bicycle infrastructure than Berlin, and the UA transformation algorithm can calculate how Berlin can most easily transform its bicycle infrastructure to become more like Paris. Values for every area in Berlin are then displayed as the proportional increase in bicycle infrastructure which would be necessary for the whole city to have infrastructure equivalent to Paris.
1.1. How does it work?
Urban Analyst presents a variety of variables for each city analysed, as well as relationships between these variables. Values for each variable are derived at every street intersection in each city. These values are then aggregated into the polygons shown in the Map and Transform pages, and across entire cities for the values shown in the Compare page. Aggregations are always weighted by local population densities, so that all UA values represent values per person as experienced in each city. Details are provided in the Data Sources and Software and Algorithms chapters.
1.2. How many calculations are involved?
The values presented in Urban Analyst are derived from estimates of travel times from every point in each city to every other point using any combination of possible modes of transport. The following table summarises numbers of street intersections, public transport (“PT”) stops, and calculations for a selection of Urban Analyst cities.
city
|
intersections
(thousands)
|
PT stops
|
PT calcs
(millions)
|
routing calcs
(millions)
|
|---|---|---|---|---|
Berlin |
360 |
9,302 |
173 |
150 |
Hamburg |
192 |
4,585 |
42 |
56 |
London |
506 |
20,072 |
806 |
160 |
Paris |
313 |
29,393 |
1,728 |
124 |
One way to appreciate the scale of these calculations is through comparison with commercial alternatives. One service, traveltime.com, charges a flat subscription fee of €540 per month for a maximum of 60 requests per minute. That rate would permit 31.5 million queries per year. The city of Hamburg, for example, would then take almost 2,000 years to calculate, and would cost €12 million. Google also offers a commercial routing service, limited to a maximum of 500,000 queries per month, for a total price of US$2,000. At that rate, the analyses for Hamburg would cost US$224 million.
The results presented in Urban Analyst are simply not possible using commercial tools, or indeed any other open source tools. These analyses truly are uniquely powerful, and provide a depth of insight into how people move through cities not available in any other way.
1.3. Can I access the full data?
Not directly, but feel free to open a GitHub issue to start a discussion about requesting full data sources.