Acta Geographica Sinica ›› 2021, Vol. 76 ›› Issue (6): 1380-1393.

• Population and Urban Studies •

### Spatial correlation analysis of residential and employment elements in Beijing based on collaborative location quotient

MENG Bin1(), GAO Liping2, LI Ruoqian2

1. 1. College of Applied Arts and Science, Beijing Union University, Beijing 100191, China
2. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
• Received:2019-03-19 Revised:2021-04-19 Online:2021-06-25 Published:2021-08-25
• Supported by:
National Natural Science Foundation of China(41671165);National Natural Science Foundation of China(51878052);The Academic Research Projects of Beijing Union University(ZK40202001)

Abstract:

Places of employment and residence are the main spaces in which urban residents work and live, as well as key elements of the urban spatial structure. Hence, thorough investigations of the spatial correlations of office and residential buildings are of great significance for the understanding of the spatial relationships of urban elements, especially that of job-housing relationships. In this study, the objects of the research were office and residential buildings in Beijing, China, and the global and local characteristics of the spatial relationships between job-housing elements were investigated using the collaborative location quotient method. The results demonstrate that: (1) The co-location quotient, a method used to measure the spatial correlations of point elements of a survey, can be effectively applied in studies of job-housing relationships, and contributes indicators and a method for the measurement of job-housing relationships. (2) The empirical analysis reveals that the global co-location quotient (GCLQ) of office and residential buildings in Beijing is below 1, indicating relatively weak spatial correlations of the job-housing elements in the city, which is consistent with the increasing job-housing separation. Overall, residential buildings are more attracted by office buildings, suggesting that the location selection of residential buildings is affected by the local distribution of office buildings, whereas the local distribution of office buildings is barely a consideration for the location selection of residential buildings. (3) The results of the local co-location quotient (LCLQ) demonstrate that the local relationships of office and residential buildings in Beijing vary significantly in space. As the distance from the urban center increases, the LCLQ of residential buildings to office buildings decreases, while the LCLQ of office buildings to residential buildings increases. Moreover, the spatial relationships of urban job-housing elements in the north and south areas of Beijing, the dividing line of which is Chang'an Avenue, are significantly different; the spatial correlation of office and residential buildings in the north area is relatively strong, while that in the south area is relatively weak (i.e., the distribution of residential buildings is independent of that of office buildings). Additionally, the result show that the spatial relationships of office and residential buildings are related to their prices. (4) Recently, researchers have turned from studies of the urban hierarchical structure based on theories of "the space of places" to studies of the trends of "the space of flows", namely population flow, logistics flow, and information flow. This study shares a similar logic, as it investigates the urban spatial structure from the perspective of elemental correlation. This research is of great significance for the understanding of the functional zones of living, working, recreation, and transportation in cities, and relevant studies will contribute to the reasonable spatial layout of job-housing elements in urban planning.