Unpacking the Relationship between Urban Form Complexity and Urban Vibrancy in Seoul, Korea: Application of Machine Learning Techniques

초록

Urban vitality is accepted as one of the essential aspects of a sustainable city. Ithas various determinant factors, including urban complexity, which boosts socialcohesion, information exchange, and interface. The definition and scope of complexityin urban planning are extensive, including functional, social, and morphologicalcomplexity. This study measures the complexity of urban morphology using variety,disparity, and separation metrics in physical structure of building, street, and block.Next, it investigates the relationship between urban physical complexity and urbanvitality in Seoul, South Korea. Using multi-source datasets, we measure urban vitalityby creating variables such as POI, mobility, credit card data, blog review data, andAirbnb data, and then use factor analysis to create three composite variables. Each ofthese three composite variables emphasize one characteristics of vitality; intensity,variability, and consistency. We then use machine learning and linear regression modelsto analyze the correlation between urban complexity variables and urban vitalitymodels, with the performance evaluation using RMSE, R-squared, MAE, and SHAPfeature importance. Finally, we analyze the non-linearity of the relationship betweenurban complexity and urban vitality using MINE statistics. Our results show that thethree complexity variables have different impacts on urban vitality, withdisparity-related variables having a less pronounced impact compared to variety andseparation-related variables. Also, the impact of complexity variables on vitality don’thave simple linear form. This study provides insights into the relationship betweenurban complexity and urban vitality, which can help urban planners and policymakersin designing sustainable and vibrant cities using optimum level of complexity measures.

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