This is the documentation for Urban Analyst platform (UA), providing open source analyses of urban structure and function across the world. The source for this documentation can be found in this GitHub repository.
Urban Analyst provides interactive maps of the properties of cities, including socio-demographic conditions and the structure and function of transport systems. Each property is measured in terms of a "variable". Relationships between individual variables are also analysed and presented, 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 summaries of all cities, enabling relationships between any pair of variables, such as transport and socio-demographic disadvantage, to be compared across all UA cities.
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.
Urban Analyst present a variety of statistics for each city analysed, as well as relationships between these statistics. Values for each statistic are derived at every street intersection in each city. These values are then aggregated into the polygons shown in the "Maps" page, and across entire cities for the values shown in the "Stats" page. Aggregations are always weighted by local population densities, to generate values representing equivalent values per person as experienced in each city.
The "Transform" page transforms the data of one city to become more like the data from a selected "target" city. This page, and the algorithms used to generate its data, are described in a separate chapter.
The values presented in Urban Analyst represent the first truly comprehensive routing analyses for each city, 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 current Urban Analyst cities.
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.
Not directly, but feel free to open a GitHub issue to start a discussion about requesting full data sources.
This documentation includes the following five chapters:
- This introduction
- "Example": A walk-through example comparison between Berlin, Germany and Paris, France, illustrating the kinds of comparisons enabled by the Urban Analyst platform.
- "UTA Variables": Providing descriptions of all variables included in the Urban Analyst platform.
- "Data Sources": Providing descriptions of all data sources used to derive these variables.
- "Software and Algorithms": Providing descriptions of, and links to, all software used to generate the UTA variables.
Contributions to, or questions regarding, this documentation, are welcome at this GitHub repository.