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Activity-space segregation is a new topic in urban segregation studies. The existing literature did not fully explain its mechanisms. In this study, we tested the hypothesis whether activity-space segregation is influenced by individual daily activity patterns. The dynamic ambient population that individuals interact with was identified with mobile phone big data and the individuals’ experienced segregation at the activity space was measured with travel survey small data. This study compared the differences in individuals’ daily activity patterns by different social-economic groups and examined the influence of the spatiotemporal pattern on the activity-space segregation. It has found that: (1) The degree of segregation in non-mandatory activity spaces during the day is less than that in mandatory activity spaces, and the degree of segregation in residence is the highest. (2) Disadvantaged populations have less leisure time and smaller activities space, and they are subject to greater time and space constraints. Spatiotemporal patterns affect the degree of an individual’s segregation. Those who have less leisure time and shorter travel distances experience higher activity-space segregation. This study has both theoretical and practical significance. The social interaction in non-mandatory activities is very important for decreasing activity-space segregation. It facilitates scientific decision-making for the government.
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