AjayakumarJCurtisAJRouzierV, et al. (2021) Exploring convolutional neural networks and spatial video for on-the-ground mapping in informal settlements. International Journal of Health Geographics20: 5.
2.
BottaFMoatHSPreisT (2020) Measuring the size of a crowd using Instagram. Environment and Planning B: Urban Analytics and City Science47(9): 1690–1703.
3.
GebruTKrauseJWangY, et al. (2017) Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States. Proceedings of the National Academy of Sciences114(50): 13108–13113.
LiSMaSTongD, et al. (2021) Associations between the quality of street space and the attributes of the built environment using large volumes of street view pictures. Environment and Planning B: Urban Analytics and City Science23998083211056340.
O’KeeffeKPAnjomshoaaAStrogatzSH, et al. (2019) Quantifying the sensing power of vehicle fleets. Proceedings of the National Academy of Sciences116(26): 12752–12757.
SeresinheCIMoatHSPreisT (2018) Quantifying scenic areas using crowdsourced data. Environment and Planning B: Urban Analytics and City Science45(3): 567–582.
YeYZengWShenQ, et al. (2019) The visual quality of streets: A human-centred continuous measurement based on machine learning algorithms and street view images. Environment and Planning B: Urban Analytics and City Science46(8): 1439–1457.