Urban Vitality from the Perspective of Information Space: A Measurement and Prediction Model Based on Multisource Data

With the rapid development of the internet and communication technologies, the concept of information space has emerged as a critical component of urban research, complementing traditional physical and social spaces. This study introduces the novel concept of network vitality as an indicator of urban vitality from the perspective of information space. Network vitality characterizes a city’s activity levels and information exchange capacity, offering a new theoretical framework for urban vitality research. Using multisource big data, including social media check-ins, WI-FI traffic, points of interest (POIs) density, population flow, gross domestic product (GDP), and takeaway sales, this study quantitatively analyzes the network vitality of Chongqing’s Guanyinqiao commercial district. The analysis reveals a significant spatial clustering of network vitality, with higher vitality in core commercial areas. To predict network vitality and explore its driving factors, a particle swarm optimization (PSO)-optimized gradient boosting decision tree (GBDT) model is employed. The results demonstrate that the PSO-GBDT model significantly enhances predictive accuracy, outperforming traditional models. Key drivers of network vitality include population density, POI density, and takeaway sales, with noticeable threshold effects on their influence. These findings provide valuable insights for urban planning and resource optimization, emphasizing the importance of integrating physical and information spaces to foster sustainable urban development. The proposed framework and methodology offer a replicable approach for future studies that can be used by other cities to identify areas of high and low urban vitality, so as to optimize resource allocation and improve the overall vitality of the city. The findings underscore the transformative potential of integrating information space into urban research, offering new directions for enhancing urban vitality effectively.

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Publication Details

Journal
Journal of Urban Planning and Development
Published
2026-02-24
DOI
https://doi.org/10.1061/jupddm.upeng-6007
Primary Topic
Smart Cities and Technologies
Type
article
Field-Weighted Citation Impact
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article

Urban Vitality from the Perspective of Information Space: A Measurement and Prediction Model Based on Multisource Data

Ying Chen, Jie Yang, Tingting Xu, Xinyi Cao
Journal of Urban Planning and Development
Smart Cities and Technologies
article

Urban Vitality from the Perspective of Information Space: A Measurement and Prediction Model Based on Multisource Data

Ying Chen, Jie Yang, Tingting Xu, Xinyi Cao
article en

Abstract

With the rapid development of the internet and communication technologies, the concept of information space has emerged as a critical component of urban research, complementing traditional physical and social spaces. This study introduces the novel concept of network vitality as an indicator of urban vitality from the perspective of information space. Network vitality characterizes a city’s activity levels and information exchange capacity, offering a new theoretical framework for urban vitality research. Using multisource big data, including social media check-ins, WI-FI traffic, points of interest (POIs) density, population flow, gross domestic product (GDP), and takeaway sales, this study quantitatively analyzes the network vitality of Chongqing’s Guanyinqiao commercial district. The analysis reveals a significant spatial clustering of network vitality, with higher vitality in core commercial areas. To predict network vitality and explore its driving factors, a particle swarm optimization (PSO)-optimized gradient boosting decision tree (GBDT) model is employed. The results demonstrate that the PSO-GBDT model significantly enhances predictive accuracy, outperforming traditional models. Key drivers of network vitality include population density, POI density, and takeaway sales, with noticeable threshold effects on their influence. These findings provide valuable insights for urban planning and resource optimization, emphasizing the importance of integrating physical and information spaces to foster sustainable urban development. The proposed framework and methodology offer a replicable approach for future studies that can be used by other cities to identify areas of high and low urban vitality, so as to optimize resource allocation and improve the overall vitality of the city. The findings underscore the transformative potential of integrating information space into urban research, offering new directions for enhancing urban vitality effectively.

Journal of Urban Planning and DevelopmentVol. 152(2)
Chongqing University of Posts and Telecommunications (CN)
Sustainable cities and communities
Openalex Percentile: Top 53%
Smart Cities and Technologies
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