Due to the difficulty of tracking large numbers of new migrants, how their daily activity behaviors differ from those of settled residents has not been well investigated, leading to a lack of understanding of new migrants' integration. Meanwhile, existing research largely emphasized residential space and ignored other activity disparities. To obtain a more comprehensive picture of urban segregation, we identified new migrants and two settled urban groups from two kinds of human mobility data. A S-T-A-D-I interactive framework was proposed to measure segregation from multiple activity dimensions, including spatial colocation, temporal coexistence, accessibility, activity diversity, and social interaction. Two-scale analysis of spatial colocation patterns reveals residential segregation by both residential location and housing type, suggesting the effectiveness of the mobility data in profiling socioeconomic groups. The temporal disparity in undertaking activities was unveiled by identifying temporal coexistence patterns. Moreover, the groups presented significant inequality in accessibility owing to the use of different travel modes, leading to a notable disparity in activity diversity. Jointly determined by the disparities in space, time, and diversity, the three groups generated a high level of self-segregation, and new migrants and transit users presented very low interaction potentials with the car group.

中文翻译：

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分离还是整合？利用人口流动数据探索流动人口和定居城市居民之间的活动差异

由于难以追踪大量新移民，因此他们的日常活动行为与定居居民的日常活动行为有何不同尚未得到很好的研究，导致对新移民的融入缺乏了解。同时，现有研究在很大程度上强调了居住空间，而忽略了其他活动差异。为了更全面地了解城市隔离情况，我们从两种人口流动数据中确定了新移民和两个定居城市群体。提出了一个 STADI 交互框架来衡量来自多个活动维度的隔离，包括空间托管、时间共存、可访问性、活动多样性和社会互动。空间托管模式的双尺度分析揭示了住宅区位和住房类型的住宅隔离，表明流动数据在分析社会经济群体方面的有效性。通过确定时间共存模式，揭示了开展活动中的时间差异。此外，由于使用不同的出行方式，这些群体在可达性方面表现出显着的不平等，导致活动多样性存在显着差异。受空间、时间和多样性的差异共同决定，这三个群体产生了高度的自我隔离，新移民和公交用户与汽车群体的互动潜力非常低。由于使用不同的出行方式，这些群体在无障碍方面表现出明显的不平等，导致活动多样性存在显着差异。受空间、时间和多样性的差异共同决定，这三个群体产生了高度的自我隔离，新移民和公交用户与汽车群体的互动潜力非常低。由于使用不同的出行方式，这些群体在无障碍方面表现出明显的不平等，导致活动多样性存在显着差异。受空间、时间和多样性的差异共同决定，这三个群体产生了高度的自我隔离，新移民和公交用户与汽车群体的互动潜力非常低。