Analysis of Urban Vitality in Nanjing Based on a Plot Boundary-Based Neural Network Weighted Regression Model

Yi Yang · Hong Wang · Shuhong Qin · Xiuneng Li · Yunfeng Zhu · Yicong Wang

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Human Mobility and Location-Based Analysis Regional Economics and Spatial Analysis Urban Design and Spatial Analysis

Abstract

As a representative indicator for the level and sustainability of urban development, urban vitality has been widely used to assess the quality of urban development. However, urban vitality is too blurry to be accurately quantified and is often limited to a particular type of expression of vitality. Current regression models often fail to accurately express the spatial heterogeneity of vibrancy and drivers. Therefore, this paper took Nanjing as the study area and quantified the social, cultural, and economic vitality indicators based on mobile phone data, POI data, and night-light remote sensing data. We also mapped the spatial distribution of comprehensive urban vitality using an improved entropy method and analyzed the spatial heterogeneity of urban vitality and its influencing factors using a plot boundary-based neural network weighted regression (PBNNWR). The results show: (1) The comprehensive vitality in Nanjing is distributed in a “three-center” pattern with one large and two small centers; (2) PBNNWR can be used to investigate the local regression relationships among the driving factors and urban vitality, and the fitting accuracy (95.6%) of comprehensive vitality in weekdays is higher than that of ordinary least squares regression (OLS) (65.9%), geographically weighted regression (GWR) (89.9%), and geographic neural network weighted regression (GNNWR) (89.5%) models; (3) House price, functional diversity, building density, metro station accessibility, and residential facility density are factors that significantly affect urban vitality. The study’s findings can provide theoretical guidance for optimizing the urban spatial layout, resource allocation, and targeted planning strategies for areas with different vitality values.

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References

2007The trajectories of European cities, 1960–2005 2000Statistical Tests for Spatial Nonstationarity Based on the Geographically Weighted Regression Model 2017Evaluating cities' vitality and identifying ghost cities in China with emerging geographical data 2018Urbanization for rural sustainability – Rethinking China's urbanization strategy 2018Check-in behaviour and spatio-temporal vibrancy: An exploratory analysis in Shenzhen, China 2015Residential built environment and walking activity: Empirical evidence of Jane Jacobs’ urban vitality 2019Portraying the spatial dynamics of urban vibrancy using multisource urban big data 2020Elaborating non-linear associations and synergies of subway access and land uses with urban vitality in Shenzhen

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