结构方程建模
感知
地理
生态学
计算机科学
心理学
生物
机器学习
神经科学
作者
Songlin Jiang,Xi Li,Jiayi Lin,Xinmiao Ji,Wenli Ji
标识
DOI:10.1016/j.ecolind.2025.113252
摘要
• Create a model for the mechanisms of restorative perception in rural landscapes. • Place attachment is the key mediating variable for restorative perception. • Woodland have the highest factor loading, followed by farmland, buildings, water, and roads. • Gender, age, professionalism and the degree of familiarity have moderating effects. • Offer guidance for crafting rural landscapes and enhancing recreational experiences. To alleviate the emotional stress in modern urban life, people are increasingly relying on restorative environments to retain their physical and mental well-being. The rural landscape is an underestimated potential restorative environment. This study took the traditional rural settlement “Linpan” in Chengdu as representative rural landscape, which was further divided into tourist and agricultural rural landscapes. A structural equation model was used to construct a restoration perception mechanism consisting of landscape elements perception, place attachment, recreational activity preference, and restorative perception. The results showed that the perception score of farmland and woodland in agricultural rural landscapes were the highest, and buildings in tourism rural landscapes were more effective. Landscape elements perception, place attachment, recreational activity preference all have a significant impact on restorative perception (P < 0.05), with place attachment being the most critical mediating factor affecting restorative perception (Standardized path coefficient = 0.805, P < 0.001). Gender (positive moderating effect for male), age (positive), professionalism and the degree of familiarity with the rural landscape (negative) had significant moderating effects (P < 0.05). The results of the study provide recommendations for rural landscape construction and tourism development, especially through the design of landscape elements and pro-natural activities to improve tourists' place attachment and further enhance restorative perception.
科研通智能强力驱动
Strongly Powered by AbleSci AI