Acta Geographica Sinica ›› 2020, Vol. 75 ›› Issue (8): 1585-1602.doi: 10.11821/dlxb202008003

• Population and Urban Studies • Previous Articles     Next Articles

Employment space of residential quarters in Shanghai: An exploration based on mobile signaling data

WANG De1(), LI Dan2, FU Yingzi3   

  1. 1. Collage of Architecture and Urban Planning, Tongji University, Shanghai 200093, China
    2. Shanghai Branch, China Academy of Urban Planning & Design, Shanghai 200335, China
    3. Jiangsu Institute of Urban Planning and Design, Nanjing 210036, China
  • Received:2018-12-21 Revised:2020-05-13 Online:2020-08-25 Published:2020-10-25
  • Supported by:
    National Natural Science Foundation of China(41771170)

Abstract:

The employment space of a residential quarter is widely affected by factors including housing properties and the neighboring supply of transportation and employments, which forms numerous spatial diagrams. Investigating and understanding the exemplar patterns of the employment space are thus crucial before we make targeted planning policies. Taking Shanghai as a case study and using mobile signaling data, this paper endeavors to extract typical patterns and distinguish the key factors. After the users' home and work locations are inferred, the employment space of 253 residential quarters is characterized in combination of the kernel densities estimation and the probability density analysis of commuting distance. We extracted five spatial patterns, namely, single-nucleated, ribbon-shaped, dual-nucleated, multi-nucleated, and decentralized, and highlighted several transitional patterns between them. Moreover, several factors are considered significant: the accessibility of employment centers and subway stations is a dominant factor that determines the global distribution of the patterns, while housing type is the secondary factor which leads to local variations and transitions. Finally, an integrated portrait covering the whole city area is summarized in terms of how different factors can be combined to explain the employment space of any quarters. We believe that our findings can help make planning policies regarding spatial structure optimization, industrial spatial adjustment, and housing development.

Key words: employment space, spatial pattern, residential quarter, mobile signaling data, Shanghai