Artificial Intelligence Implementation in Rural Planning and Design

Abstract

Urban vitality is a crucial factor in shaping the development of cities, with the built environment playing a pivotal role in influencing this vitality. This research focuses on the city of Yinchuan, utilizing the Baidu heat map as a tool to assess urban vitality. Independent variables are drawn from the built environment, and the study employs various models, including Ordinary Least Squares (OLS), Moran's I, Geographically Weighted Regression (GWR), and Gradient Boosting Decision Tree (GBDT), to explore the intricate relationship between urban vitality and the built environment.The analysis distinguishes between weekdays and weekends, providing a nuanced understanding of temporal dynamics. The findings reveal several key insights:(1) The study underscores that the built environment in Yinchuan significantly impacts urban vitality on both weekdays and weekends. Variables such as Landscape, Hotel, Shopping, Openness, Greenness, Imageability, Road, Bus station, TPBt-500, NQPTA-500, and TPBt-1200 are identified as key influencers.(2) Positive spatial autocorrelation is observed between the built environment and urban vitality on both weekdays and weekends.(3)GWR model analysis reveals distinct spatial distribution characteristics for urban vitality during weekdays and weekends.(4)GBDT model analysis highlights different importance rankings for variables influencing urban vitality on weekdays and weekends. The research offers tailored strategies for enhancing urban vitality in different areas and time periods, serving as a crucial reference for urban planning and sustainable development in Yinchuan City.

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