基于个体时空邻近指数的户籍维度社会空间分异研究——以上海市郊区10个典型镇为例

社会空间分异是城市研究的经典议题。在人类移动性不断增强的背景下,传统的基于居住空间汇总的社会空间分异测度方法表现出一定的局限性,对于居住空间外的日常活动空间隔离的探讨相对缺乏,对于不同活动和不同时段间分异格局差异的考虑有所不足。因此有必要从“基于人”的视角出发,探索社会空间分异测度的新方法,探讨不同时空间维度的社会分异格局。本研究基于上海市郊区10个典型镇的活动日志调查数据,构建“个体时空邻近指数”,聚焦户籍这一反映中国城市特征的重要维度,以不同户籍类型人群之间的分异程度为研究对象,分析其时空间特征,并对结果进行可视化。研究表明：上海市不同户籍人群在活动、时间和空间维度上存在明显的社会空间分异。本研究创新了基于活动空间的社会空间分异测度方法,从活动与时空间结合的视角探讨了户籍维度的社会空间分异,为更好的理解在中国大城市日益凸显的社会空间分异问题提供了新的视角。

Socio-spatial segregation of household registration based on a spatiotemporal index at the individual level:A case study of 10 towns in Shanghai suburbs

Socio-spatial segregation is a critical issue of urban studies. With the increase of human mobility, the traditional measurements of residential segregation based on aggregated data show limitations. Few studies have explored the segregation in residents' daily activity space outside their living spaces, or the spatiotemporal patterns of segregation level in different periods of a day. Thus, it is necessary to study the individual-based socio-spatial segregation in various geographic and temporal contexts. Using data from a household travel survey in 10 typical towns of the suburbs of Shanghai in 2017, this study researched the spatiotemporal characteristics of household registration segregation in people's daily life based on a creative individual-based proximity index, which measures the proximity of various groups in different geographic contexts with various activity types and time periods. We divided a day into eight periods and used the i-STP index to measure the spatiotemporal pattern of segregation of four kinds of household registered residents. By dividing Shanghai into hexagonal grids with an actual area of 5 km ², the average value of i-STP within each grid was calculated. Then Arcscene 10.2 was used to visualize the results. Results show that the average i-STP is higher in work activities during weekdays and is lower in recreation activities on weekends, indicating the distinctions of segregation levels in different activity contexts. Results also show that lower i-STP is detected during commuting time (6:00-9:00) and leisure time at night (18:00-21:00) on weekdays and the average i-STP reaches the minimum in the afternoon (15:00-18:00) on weekends. We also found that residents with different household registration types have different spatiotemporal segregation patterns and that the working place and activity place of residents in day time shows higher segregation level than the living place at night. The study provides a new measure of segregation from an individual-based and dynamic perspective, which can fill the gap in the existing research on segregation based on activity space. The results of the study indicate that attention should be paid to the segregation of different types of registered population in work and leisure activities in large cities of China to enhance the interaction between different groups.