Impacts of Built Environment on Urban Vitality: Regression Analyses of Beijing and Chengdu, China

Shiwei Lu, Chaoyang Shi and Xiping Yang
Additional contact information
Shiwei Lu: Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources of China, Shenzhen 518034, China
Chaoyang Shi: School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan 430074, China
Xiping Yang: School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China

IJERPH, 2019, vol. 16, issue 23, 1-16

Abstract: The loss of urban vitality is an important problem in the development of urban central areas. Analyzing the correlation between urban built environment and urban vitality supports urban planning and design. However, current research excludes the study of how consistent built environment factors affect urban vitality of cities with different development situations. Therefore, using social media check-in data, this paper measures neighborhood vibrancy in urban central areas in Beijing and Chengdu, China. Four levels of spatial information were used to measure the built environment: regulatory planning management unit (RPMU), land use, road network, and building. Regression model is used to quantify the correlation between urban vitality and the built environment of these two cities. The study found a strong correlation between built environment factors and urban vitality. Among the built environment factors, points of interest (POI) diversity and public transport accessibility indicators were strongly positively correlated with neighborhood vibrancy. However, the density indicators had totally different effects on urban vitality of cities with different development situations, which is excluded in existing studies. This research strengthens the practical understanding of the compact city concept, and can support the design and planning of urban built environment.

Keywords: social media check-in data; built environment; urban vitality; heterogeneous patterns; regression analyses (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
https://www.mdpi.com/1660-4601/16/23/4592/pdf (application/pdf)
https://www.mdpi.com/1660-4601/16/23/4592/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:16:y:2019:i:23:p:4592-:d:288857

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().