The spatial pattern and influence mechanism of urban vitality: A case study of Changsha, China

Abstract

In the new era, the vitality of urban space is an important engine of urban development, and the improvement of urban space vitality is the core component of urban spatial structure optimization and space renewal. However, the availability of data is an important issue in the evaluation of urban space vitality, and continuous vitality monitoring of the entire city is difficult to achieve through traditional methods of field research and questionnaire interviews. Due to this challenge, the traditional vitality assessment methods have serious limitations in the analysis of vitality causes and the guidance of urban space development. Using mobile phone signaling data, this study takes Changsha City as an example to measure the urban spatial vitality and uses the SEM model to analyze how market intervention, traffic accessibility, and spatial characteristics affect the density and stability of urban spatial populations. The results show that the overall urban space vitality density and vitality stability demonstrates an obvious “center–periphery” pattern, and the vitality of the urban center area is in a “high density–low stability” state. The overall urban vitality density on rest days is slightly lower than that on weekdays, and the stability of vitality on rest days is significantly higher than that on weekdays. Market intervention and transportation accessibility support vitality density, but not vitality stability, and spatial characteristics are the opposite. The findings can provide insights relevant to urban spatial planning and design.

Revealing the Spatio-Temporal Heterogeneity of the Association between the Built Environment and Urban Vitality in Shenzhen

“…To address this issue, some scholars have applied mobile phone signaling data to measure urban vitality. For example, Wu et al, Kang et al, and Xia et al applied mobile phone signaling data to measure the urban vitalities of Shanghai city, Seoul city, and Changsha city, respectively [22][23][24]. Their study confirmed that mobile phone communication data are a more accurate data source for measuring urban vitality than POIs.…”

“…A comparison of the main data sources in previous studies is shown in Table 1. [21] Mobile phone data Wu et al, 2019 [22] Broad coverage and user groups Low precision and difficult to obtain Kang et al, 2020 [23] Xia et al, 2022 [24] Social media data Wang et al, 2022 [25] High precision and easy access Biased user groups exist…”

“…Long et al [47] analyzed the effects of urban design on the economic vitality of 286 mega cities in China using the OLS model. Wu [22] and Xia [24] explored the factors influencing the urban vitality in different cities in China by applying the SLM model and SEM model, respectively. Indeed, global regression models can provide insights into the overall influencing factors on urban vitality, but ignore spatial heterogeneity.…”

Preserving the past, nurturing the future: a systematic literature review on the conservation and revitalization of Chinese historical town environments during modernization

“…The regeneration of historical conservation towns can bring economic benefits to the city and its inhabitants and contribute to the promotion of social and human development (Xia, et al, 2022). The renewal of historical conservation towns is not the creation of new space patterns or fabrication of a fake history or image for these places (Orbaşli, 2017).…”

“…Cultural heritage buildings can be former places of religious worship, aristocratic/ royal residences, community meeting places, industrial production sites, early modern office buildings, or military objects (Wang et al, 2022). It is important to seek sustainable solutions for these buildings in urban development (Xia, et al, 2022).…”