A Study on the relationship between Landscape Elements, Landscape Preferences and Health Benefits in Urban Parks

Public health and well-being are closely linked to the quality of the human landscape environment. As a vehicle for studying human-landscape interactions, landscape preferences are closely linked to landscape resilience. Numerous studies have shown that individuals exhibit different preferences for different environments, with more preferred environments producing greater health benefits. Natural environments are also subject to differences in individual preferences and offer greater health benefits than urban environments. To investigate the relationship between landscape elements, landscape preferences, health benefits and their influence mechanisms, an influence pathway and evaluation model was constructed for this study between these three variables, using the South Lake Urban Central Ecological Park in Tangshan, China as the research object and social media network evaluation as the data source. Quantitative and qualitative analyses were used to extract landscape element measures, in combination with existing landscape preference and health benefit assessment scales. Field research was conducted to obtain evaluation data, and a structural relationship model was constructed for validation to examine the interactions between landscape elements, landscape preferences, and health benefits. The results showed that landscape elements had a significant positive effect on landscape preferences (β is 0.699, t=8.375, P<0.001); landscape preferences also had a significant positive effect on health benefits (β is 0.643, t=6.526, P<0.001); landscape elements also had a significant positive effect on health benefits (β is 0.42, t=2.816, P< 0.01), while landscape elements had an indirect effect through partial mediation of landscape preferences. In the landscape element measurement model, each latent variable can effectively explain landscape elements, but the explanation ability of each latent variable for landscape elements varies, indicating that different landscape elements have different effects on landscape preferences; in the landscape preference measurement model, the four measurement dimensions can effectively explain landscape preferences, among which consistency has the highest explanation ability for landscape preferences; in the health benefits assessment measurement model, all four measurement dimensions effectively captured the health benefits assessment, eliminating fatigue has the highest explanatory power for the health benefits assessment. From the final structural equation model, it can be seen that landscape elements have a significant effect on both landscape preferences and health benefits, and landscape preferences also has a significant effect on health benefits. Visitors moved from landscape element evaluation to landscape preferences and finally to health benefits assessment, which is a sequential experience.