Optimization Study of Terrace Restoration Sampling Governance Model Based on Fuzzy Clustering Algorithm

A novel governance model for terrace restoration in the UNESCO-listed Honghe Hani Rice Terraces, China, demonstrates how fuzzy clustering algorithms (FCA) can optimize ecosystem management by analyzing farmer participation and trust in a 'four elements homogeneous' system. This approach reveals that the terraces' resilience to extreme drought—such as the once-in-a-century event studied—relies on the interplay of forest water retention, irrigation ditches, village governance, and terrace productivity. By comparing Hani farmers' trust in these ecosystem functions against tribal bonds, the study identifies key behavioral patterns that could empower autonomous management. The findings suggest a data-driven strategy to enhance sustainability in culturally significant landscapes.

Ji, B., Shang, X., & Li, L. (2024). Optimization Study of Terrace Restoration Sampling Governance Model Based on Fuzzy Clustering Algorithm. 2024 Asia-Pacific Conference on Software Engineering, Social Network Analysis and Intelligent Computing (SSAIC), 288–291. https://doi.org/10.1109/ssaic61213.2024.00060