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Abstract Chinese classical gardens are a significant cultural heritage in the history of world gardening, with their central architectural principle of "scenes changing as steps move" (步移景异) embodying traditional Chinese aesthetic ideals. This study employed the variation of visual complexity during a tour as a representation of this principle, using Jingxinzhai (静心斋) Garden as a case study. The visual environmental characteristics were quantified using the Fraclab box-counting, Canny edge detection, and DeepLab V3 + model, and the spatial distribution of fractal dimension and visual index of landscape elements were analyzed. Through partial correlation analysis, hierarchical regression analysis, and one-way ANOVA, the relevant factors (BVI, RVI, GVI, WVI) and influencing factors (BVI, RVI, GVI) and the differences among landscape element combinations of visual complexity were identified. Furthermore, the distribution patterns and causes of visual complexity in Chinese classical gardens were then discussed. This study proposes an effective method for quantifying the visual environmental characteristics of Chinese classical gardens and provides an explanation of the concept of "scenes changing as steps move" from the perspective of visual environment. It offers important references for a deeper understanding of Chinese classical garden design and planning.

Chinese classical gardens are a significant cultural heritage in the history of world gardening, with their central architectural principle of "scenes changing as steps move" (步移景异) embodying traditional Chinese aesthetic ideals. This study employed the variation of visual complexity during a tour as a representation of this principle, using Jingxinzhai (静心斋) Garden as a case study. The visual environmental characteristics were quantified using the Fraclab box-counting, Canny edge detection, and DeepLab V3 + model, and the spatial distribution of fractal dimension and visual index of landscape elements were analyzed. Through partial correlation analysis, hierarchical regression analysis, and one-way ANOVA, the relevant factors (BVI, RVI, GVI, WVI) and influencing factors (BVI, RVI, GVI) and the differences among landscape element combinations of visual complexity were identified. Furthermore, the distribution patterns and causes of visual complexity in Chinese classical gardens were then discussed. This study proposes an effective method for quantifying the visual environmental characteristics of Chinese classical gardens and provides an explanation of the concept of "scenes changing as steps move" from the perspective of visual environment. It offers important references for a deeper understanding of Chinese classical garden design and planning. [ABSTRACT FROM AUTHOR]