PROGRESS IN GEOGRAPHY ›› 2019, Vol. 38 ›› Issue (12): 1831-1842.doi: 10.18306/dlkxjz.2019.12.001

• Articles •     Next Articles

Impacts of street and public transport network centralities on housing rent:A case study of Beijing

DU Chao1, WANG Jiaoe2,3,*(), LIU Binquan1, HUANG Dingxi1   

  1. 1. Guangdong Urban & Rural Planning and Design Institute, Guangzhou 510290, China
    2. Institute of Geographic Sciences and Natural Resources Research, Key Laboratory of Regional Sustainable Development Modeling, CAS, Beijing 100101, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2018-12-21 Revised:2019-05-28 Online:2019-12-28 Published:2019-12-28
  • Contact: WANG Jiaoe
  • Supported by:
    National Natural Science Foundation of China(41722103);Technology Project of the Ministry of Housing and Urban-Rural Development of China(2018-R4-004)


Higher housing demand leads to housing price increasing rapidly, with lower housing affordability. Under these circumstances, renting a place has progressively become an alternative way for residents of cities. Urban transportation is one of the most significant influencing factors for housing rent, which needs to be examined at greater depth. This study used complex network analysis to explore how transportation centrality impacts housing rent. The conclusions are: transportation network shows significant impacts on housing rent, with higher impacts of public transport network than street network. Closeness in public transport has the highest impact on housing rent. Each centrality aspect influences housing rent differently, and relative accessibility in public transport network and transfer capacity in street network have the greatest impacts on housing rent. This article discussed two modes of urban transportation and their spatial characteristics. By refining the impacts of different transportation modes by network analysis, it provides a new perspective of urban transportation research and its spatial effects.

Key words: transportation network, housing rent, spatial pattern, influence mode, Beijing