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基于协同区位商的北京城市职住要素空间关联
引用本文:孟斌,高丽萍,李若倩.基于协同区位商的北京城市职住要素空间关联[J].地理学报,2021,76(6):1380-1393.
作者姓名:孟斌  高丽萍  李若倩
作者单位:北京联合大学应用文理学院,北京100191;首都师范大学资源环境与旅游学院,北京100048
基金项目:国家自然科学基金项目(41671165);国家自然科学基金项目(51878052);北京联合大学科研项目(ZK40202001)
摘    要:就业地和居住地是城市居民工作以及生活的主要场所,同样也是城市空间结构最重要的组成要素,写字楼与居民楼空间关联性研究对深刻理解职住关系有着至关重要的作用.利用协同区位商方法,对北京市写字楼与居民楼空间关联总体特征和局域空间关联格局进行分析.研究表明:①协同区位商作为一种测量点要素之间联系的方法,能够很好的应用到职住关系的...

关 键 词:职住关系  要素关联  协同区位商  同位模式  北京
收稿时间:2019-03-19
修稿时间:2021-04-19

Spatial correlation analysis of residential and employment elements in Beijing based on collaborative location quotient
MENG Bin,GAO Liping,LI Ruoqian.Spatial correlation analysis of residential and employment elements in Beijing based on collaborative location quotient[J].Acta Geographica Sinica,2021,76(6):1380-1393.
Authors:MENG Bin  GAO Liping  LI Ruoqian
Institution:1. College of Applied Arts and Science, Beijing Union University, Beijing 100191, China2. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
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.
Keywords:job-housing relationship  element association  co-location quotient  co-location patterns  Beijing  
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