Wang et al. map a rapidly expanding urban research field in which street-view imagery, social-media traces, positioning data, physiological signals and video become instruments for examining perception, cognition, affect and behaviour. Their iconic move is to treat data type not as a neutral technical choice but as an epistemic filter: each source makes some dimensions of human–environment interaction visible while introducing characteristic blind spots, sampling biases, privacy problems and interpretive uncertainty. The review of 242 studies shows that increased scale, granularity and automation do not automatically produce stronger urban knowledge; some data-driven studies merely restate established findings through newer instruments. Methodologically, the paper therefore shifts emphasis from technological novelty toward validation, triangulation and integrated designs that combine heterogeneous data with conventional qualitative methods. Its wider importance lies in exposing a central problem of contemporary urban science: expanding evidential capacity without confusing abundance, resolution or computational sophistication with explanatory adequacy.
URBANISM MEETS ART