A Seasonal Study of the Spatial Quality of Cold Streets Based on Activity Portrait Indexes (APIs): The Example of Harbin City Streets

China’s cities are shifting from expansion to renewal. In cold-climate cities, street use often drops in winter, so human-centred street quality matters. However, few studies measure behavioural activity using the same indicators for winter and non-winter periods. We propose an “activity portraits” framework and an Activity Portrait Index (API) that combines activity density, activity-type propensity, and age-group diversity. We used street-view images and field surveys from 37 street segments in Harbin, covering commercial, living, and landscape streets. Streetscape elements were extracted, and separate regression models were built for winter and non-winter conditions. In winter, seven streetscape factors were significant and were entered into the regression as four PCA components. In non-winter conditions, the model retained four predictors: street width-to-height (W/H) ratio, road clutter, greenery visibility, and signage density (R2 = 0.802). The models show season-specific links between activity and street space and support a seasonal API measurement system for cold-region streets. The results inform targeted design and renewal principles to improve street usability and vitality year-round.