Exploring the spatial correlation between accessibility to urban vibrancy centers and housing price from a time-dynamic perspective

ABSTRACT

Urban vibrancy is an important indicator of urban prosperity. Evaluating the correlation between urban vibrancy and housing prices is increasingly necessary. However, most studies have ignored the temporal characteristics of urban vibrancy and only considered its spatial nature. This study optimizes the identification model of urban vibrancy centers and proposes a novel model for evaluating the time-dynamic accessibility of urban vibrancy centers. The model takes into account real-time changes in travel costs and analyses its spatial correlation with housing prices. The case study of Chengdu shows significant variations in the spatiotemporal distribution of urban vibrancy centers. High-vibrancy areas are concentrated near commercial complexes. The time distribution of urban vibrancy accessibility is more concentrated at night (18:00–24:00), and the high-accessibility areas are located around the old city and the newly planned Central Business District in the south. Housing prices and urban vibrancy centers accessibility are mainly negatively correlated spatially. The study emphasizes the temporal nature of urban vibrancy and accessibility and enriches the evaluation model of urban vibrancy centers. It also contributes to the improvement of the framework of urban vibrancy research and deepens the understanding of the important variable of “time” in urban planning.

KEYWORDS:

• Spatial correlation
• accessibility
• urban vibrancy
• housing price

Acknowledgments

This research was supported by the National Social Science Foundation of China [18BJY086], National Natural Science Foundation of China [42201308] Natural Science Foundation of Shandong Province, China [ZR2021QD127, ZR2021ME203]. The authors would like to gratefully acknowledge the anonymous reviewers and the members of the editorial team who helped to improve this paper through their thorough review.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Social media data with geotags were obtained from Weibo (www.weibo.com), data related to residential communities were obtained from Lianjia (https://cd.lianjia.com/xiaoqu/), roads in the study area and TAZ data generated after processing in this study can be downloaded from this link: https://osf.io/uq6vg/files

Other data that support the findings of this study are available from the authors, upon reasonable request.