Journal article

Streetscape augmentation using generative adversarial networks: Insights related to health and wellbeing

Jasper S Wijnands, Kerry A Nice, Jason Thompson, Haifeng Zhao, Mark Stevenson

Sustainable Cities and Society | Elsevier BV | Published : 2020

Abstract

Deep learning using neural networks has provided advances in image style transfer, merging the content of one image (e.g., a photo) with the style of another (e.g., a painting). Our research shows this concept can be extended to analyse the design of streetscapes in relation to health and wellbeing outcomes. An Australian population health survey (n = 34,000) was used to identify the spatial distribution of health and wellbeing outcomes, including general health and social capital. For each outcome, the most and least desirable locations formed two domains. Streetscape design was sampled using around 80,000 Google Street View images per domain. Generative adversarial networks translated thes..

View full abstract

Grants

Awarded by Australian Research Council Discovery Early Career Research Award


Awarded by National Health and Medical Research Council (Australia) Fellowship


Funding Acknowledgements

JT is supported by an Australian Research Council Discovery Early Career Research Award [grant number DE180101411]. MS is supported by a National Health and Medical Research Council (Australia) Fellowship [grant number APP1136250]. The authors would like to acknowledge the valuable feedback of three anonymous reviewers, which helped us to improve the quality of the original manuscript.