Measuring urban nighttime vitality and its relationship with urban spatial structure: A data-driven approach

Abstract

Nighttime vitality has garnered attention in recent years as an important indicator reflecting urban economy and quality of life. However, it is difficult to characterize this intangible issue. As a response, this study employed a data-driven approach to measure nighttime vitality and explored its relationships with urban spatial structure. Specifically, the data from Meituan.com—the largest Chinese shopping platform for local consumer products and retail services—were used to measure nighttime vitality based on a hierarchical weighting method. Multidimensional characteristics of the urban spatial structure were evaluated. Spatial regression models were conducted on the effect analysis of urban spatial structure on nighttime vitality. Relationship estimations were statistically significant with indicators, such as block functions, building density, interaction density, enclosure of locals, and the age structure of the main population. Our findings provide a more complete understanding of nighttime vitality, which is often overlooked in urban vitality studies. Insights derived from this study could help formulate spatial strategies to enhance nighttime vitality and quality of life.

Evaluating building color harmoniousness in a historic district intelligently: An algorithm-driven approach using street-view images

“…The road network collected from the Baidu Map API was used to generate the sampling sites. Spatial analyses were then achieved using ArcGIS to sample points with an interval of 20 m, which works well in Chinese streets to achieve a full coverage of the streetscape (Wu et al, 2022). After that, a Python script was coded to read the XY coordinates of sampling points to download SVIs from the Baidu Map API Service.…”

TOD and vibrancy: The spatio-temporal impacts of the built environment on vibrancy

“…Even containing detailed information about the population and types of activities, these quantitative measures still suffer from disadvantages such as small survey sample sizes, discontinuity in time, and the subjectivity of the interviewees. In recent years, with the rapid spread of smart phones as well as the advances in location aware device (LAD) and location based service (LBS), burgeoning technologies have brought new data sources and research tools for urban vibrancy studies (Wu et al, 2022). Multiplesource spatio-temporal big data, with its characteristics of massive scale, rapid flow, and diversity (Zhou et al, 2020), enriches the human social activities and urban spatial information.…”

How the built environment affects the spatiotemporal pattern of urban vitality: A comparison among different urban functional areas

“…One type entails the measurement of the intensity of urban vitality within different spaces considering the cumulative urban vitality value over time (Yue et al, 2017), which remains a spatial comparison. The other type involves the analysis of the spatiotemporal patterns of urban vitality through the construction of various indicators, such as the spatiotemporal vitality (C. Wu et al, 2018aWu et al, , 2018b, variability (Guo et al, 2021;Sulis et al, 2018), and daytime-nighttime vitality (Kim, 2020;Wu et al, 2022;Xia et al, 2022). These indicators can suitably capture urban activities that rise and decline in different time frames.…”

“…In urban morphology theory, it has also been suggested that suitable accessibility, appropriate building density and design, and sufficient functional mix are critical indicators for urban vitality enhancement (Montgomery, 1998). In empirical studies, accessibility, density, typology, and diversity have been highlighted as important spatial factors of urban vitality (Chen et al, 2021;Long & Huang, 2019;Wu et al, 2022;Ye et al, 2018;Yue et al, 2017;Zhang et al, 2021). However, most studies have focused on the influencing factors of general urban vitality or time-specific vitality (Guo et al, 2021;Xia et al, 2022), but few studies have investigated the effects of the built environment on temporal variations in urban vitality.…”