This study will compare the results of measuring Urban Complexity using the Shannon-Wiener index in two different methods. Using a joint dataset retrieved from Foursquare API, we will measure the degree of urban complexity of every street: 1) relating every amenity to the closest street segment in a computational way and then applying the calculation to the segments; and 2) applying the calculation to every cell of a grid that will be combined with the street network afterwards. The selected case study is the city of London, and the dataset employed will be retrieved from Foursquare. Over 79,000 venues were collected and classified in over 660 categories. In order to proceed to the analysis, these 660 categories will be reduced to 10 based on the classification of activities observed in the public space from the traditional urban discipline. Then the urban complexity index of each street segment of London will be measured as a simultaneous calculation of the density and diversity of collected and classified economic activities.

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The paper presents a method to operationalize Jan Gehl’s questions for public space into metrics to map Russian monotowns’ urban life in 2017. With the use of social media data, it becomes possible to scale Gehl’s approach from the survey of small urban areas to the analysis of entire cities while maintaining the human scale’s resolution. When underperforming public spaces are detected, we propose a matrix for urban design interventions using Jane Jacobs’ typologies for good city life. Furthermore, this method was deployed to improve the conditions of public spaces in Russian monotowns through a series of architectural briefs for design competitions and urban design guidelines for local administrations.

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