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Urban form, traffic volume, and air quality: A spatiotemporal stratified approach

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  • Ye Tian
  • Xiaobai Yao

Abstract

Understanding the interplay between urban form, traffic volume, and air quality is significant for urban planning and environmental sustainability. However, limited progress has been made in bringing effective urban planning strategies to help control traffic demand and resulting air pollutants. Therefore, this study aims to investigate the interrelation between urban form, traffic volume, and air quality with a spatiotemporal stratified method. The method extracts and preprocesses traffic volume data in spatial (polluted and unpolluted zones) and temporal (periods in holidays and workdays) dimensions. Three decision tree models (random forest, random tree, M5 model tree) and two comparison models (multiple linear regression, artificial neural network) are used to examine the relationships. The final results show that the spatiotemporal stratification approach effectively reveals the interrelations, and the random forest model outperforms the other models. Specifically, highly aggregated roads and industrial areas are more associated with traffic volume in polluted zones. The dominance of waterway and vegetation shows a strong association with traffic volume in unpolluted zones. The degree of association also varies significantly between workdays and holidays. Our spatiotemporal stratified approach reveals heterogeneous relationships between urban form, traffic volume, and air quality and provides insightful references on sustainable urban development.

Suggested Citation

  • Ye Tian & Xiaobai Yao, 2022. "Urban form, traffic volume, and air quality: A spatiotemporal stratified approach," Environment and Planning B, , vol. 49(1), pages 92-113, January.
    • Handle: RePEc:sae:envirb:v:49:y:2022:i:1:p:92-113
    DOI: 10.1177/2399808321995822
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    References listed on IDEAS

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    2. Gérard Biau & Erwan Scornet, 2016. "Rejoinder on: A random forest guided tour," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(2), pages 264-268, June.
    3. Ali Rahimikhoob & Maryam Asadi & Mahmood Mashal, 2013. "A Comparison Between Conventional and M5 Model Tree Methods for Converting Pan Evaporation to Reference Evapotranspiration for Semi-Arid Region," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(14), pages 4815-4826, November.
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    1. Ye Tian & Xiaobai Angela Yao & Marguerite Madden & Andrew Grundstein, 2024. "Synergic effects of meteorological factors on urban form-outdoor exercise relationship: A study with crowdsourced data," Journal of Geographical Systems, Springer, vol. 26(1), pages 47-72, January.

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