Abstract
In response to the growing urban–rural dichotomy and escalating human–land conflicts in rural China, this study investigates the role of soundscapes as emotional mediators to enhance environmental satisfaction and foster sustainable human–land symbiosis. To address this need, we carried out a series of systematic field surveys at five representative traditional villages in a major provincial capital city in China, and we implemented a comprehensive questionnaire and surveyed 524 residents about their perceptions of sound, land affection, and environment. We employed a mixed-methods approach combining questionnaire surveys, association rule mining (ARM), and structural equation modeling (SEM) to explore the ‘sound–land–environment’ interaction chain. ARM analysis identified strong associations among tour guide narratives, local dialects, natural sounds (e.g., rustling leaves, birdsong), and tourist-generated sounds (support = 50%, confidence = 78%, lift = 1.33). SEM results revealed that soundscapes significantly and positively influence land dependence (β = 0.952, p < 0.001) and land rootedness (β = 1.812, p < 0.001), which in turn jointly affect environmental satisfaction (β = –0.192, p = 0.027) through a chain mediation pathway. These findings suggest that optimizing rural soundscapes can strengthen emotional bonds between people and land, thereby enhancing environmental satisfaction and promoting performance of sustainable human–land symbiosis. The study contributes theoretically by elucidating the emotional mechanisms linking soundscapes to human–land relationships and offers insights for incorporating soundscape considerations into village planning and developing policies to cultivate land attachment, supporting the sustainable development of traditional villages.
Author supplied keywords
Cite
CITATION STYLE
Wang, J., Wen, X., Zhou, S., Zhang, Z., & Zhao, D. (2025). Towards Sustainable Human–Land Symbiosis: An Empirical Study of Chinese Traditional Villages. Land, 14(8). https://doi.org/10.3390/land14081676
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.