This paper is the direct result of the 2019 Urban Studies Network Day of CUS,  ACHI and ACUH in the Lloyd Hotel. Mingshu Wang (University of Twente) and Floris Vermeulen met there and decided to write this paper together. It will be part of USJ special issue ‘Big data in the city’ (Tony O’Sullivan ed.) with articles from among others Robert Sampson, Edward Glaeser, Michael Batty, Harvey Miller and Mario Small.

In the article Wang and Vermeulen use big data from images captured by Google Street View (GSV) to analyse the extent to which the built environment impacts the survival rate of neighbourhood-based social organisations in Amsterdam, the Netherlands. To extract data on built environment features from GSV images, they applied a deep learning model, DeepLabv3+. They then used elastic net regression to test the relationship between the built environment empirically – distinguishing between car-related, walking-related and mixed-use land infrastructure – and the survival of neighbourhood organisations. The study points to the value of easily applicable observational big data to study urban life.