Measuring spatial nonstationary effects of POI-based mixed use on urban vibrancy using Bayesian spatially varying coefficients model

Abstract

Understanding the relationship between mixed land use and urban vibrancy is vital in advanced urban planning applications. This study presents a Bayesian spatially varying coefficient (SVC) model to explore the spatially nonstationary relationship between mixed land use and urban vibrancy after controlling for other factors. We first use the convolutional conditional autoregressive prior to accommodate the ecological bias resulting from unobserved confounders. Then we develop our approach in the case of a single predictor to allow the spatially varying coefficient process. We further introduce a type of the Bayesian SVC model that considers the stratified heterogeneity of the outcome, allowing the coefficients to simultaneously vary at the local and subregion level. We illustrate the proposed model by conducting a case study in Shenzhen using mobile phone data, an officially registered point-of-interest (POI) dataset, and several supplementary datasets. The model evaluation results show that including spatially unstructured and structured component combinations can improve the model's fitness and predictive ability; additionally, considering spatial stratified heterogeneity can further enhance the model's performance. Our findings provide an alternative for measuring the variable local-scale association between mixed-use and urban vibrancy and offer new insights that broaden the fields of environmental science and spatial statistics.

Keywords:

• Bayesian hierarchical model
• spatial stratified heterogeneity
• mixed land use
• urban vibrancy
• Spatially varying coefficients model

Disclosure statement

No potential conflicts of interest were reported by the author(s).

Data and codes availability statement

The covariates and codes supporting this study's findings are available with a digital object identifier (DOI) at https://doi.org/10.6084/m9.figshare.18462065. The original POI data (point layers) and mobile phone data cannot be shared publicly due to restrictions.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (41601407,41801322,42071360) and Peng Cheng Laboratory Research Project (PCL2021A07).

Notes on contributors

Zhensheng Wang

Zhensheng Wang is an Associate professor in Peng Cheng Laboratory, Shenzhen. His research focuses on geospatial artificial intelligence and spatial analysis. The main contributions to the paper are writing-original draft preparation, editing, and conducting the experiments. Email: [email protected].

Feidong Lu

Feidong Lu is a Ph.D. candidate in College of Architecture and Urban Planning, Tongji University. His research interests include urban planning and medical system. The main contributions to the paper are conducting experiments and reviewing. Email: [email protected].

Zhaohui Liu

Zhaohui Liu is the CTO of China ECO-City Academy. His research interests include new urbanization, urban design, and smart city. The main contribution to the paper is experimental design. Email: [email protected].

Wei Tu

Wei Tu is an Associate professor in the department of urban spatial information engineering, Shenzhen University. His research interests include trajectory modeling, analysis, and optimization. The main contributions to the paper are funding acquisition and editing. Email: [email protected].

Ke Nie

Ke Nie is a senior engineer in Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen, China. The main contribution to the paper is data processing. Email: [email protected].

Qingyun Du

Qingyun Du is the dean of School of Resource and Environmental Sciences, Wuhan University. His research interests include digital mapping, cartography, spatial statistics, and smart city. The main contributions to the paper are conceptualization and experimental design. Email: [email protected].

Qingquan Li

Qingquan Li is the president of Shenzhen University. He is also the director of Guangdong Key Laboratory of Urban Informatics, and the director of Shenzhen Key Laboratory of Spatial Smart Sensing and Services. His research interests include engineering survey and smart city. The main contribution to the paper is conceptualization. Email: [email protected].

Zhiqiang Wu

Zhiqiang Wu is the former vice president of Tongji University, Member of Chinese Academy of Engineering. His research interests include urban planning, sustainable development, and smart city. The main contributions to the paper are reviewing and supervision. Email: [email protected].