Remote Sensing-Enhanced Structural Equation Modeling for Evaluating the Health of Ancient Juglans regia L. in Tibetan Traditional Villages

Ancient walnut trees (Juglans regia L.), revered as “cultural heritage in motion,” have coexisted harmoniously with dense clusters of Tibetan traditional villages for centuries. However, accelerating climate change and expanding human activities along the middle reaches of the Yarlung Tsangpo River have increasingly threatened their survival. To quantitatively evaluate the health of these ancient trees and identify the underlying driving mechanisms, this study developed a remote sensing-enhanced Structural Equation Model (SEM) that integrated satellite-derived ecological indices, land-use intensity, and field-measured morphological and physiological indicators. A total of 135 ancient walnut trees from villages such as Gamai in Jiacha County, Tibet, were examined. Key findings: (1) The SEM demonstrated an excellent model–data fit (Minimum Discrepancy Divided by Degrees of Freedom (CMIN/DF) = 1.372, Root Mean Square Error of Approximation (RMSEA) = 0.053, Tucker–Lewis Index (TLI) = 0.956, and Comparative Fit Index (CFI) = 0.962), confirming its robustness. (2) Among the latent variables, overall condition exerted the strongest influence (weight = 0.360), whereas foliage condition contributed least (0.289). (3) Approximately 35.56% of trees were healthy or sub-healthy, while 61.48% showed varying levels of decline. (4) Tree health was jointly shaped by intrinsic and extrinsic factors, with intrinsic drivers exhibiting stronger explanatory power. Externally, human disturbance negatively affected health, whereas ecological quality was positively associated. These results highlight the effectiveness of integrating remote sensing and SEM for ancient tree assessment and underscore the urgent need for long-term monitoring and adaptive conservation strategies to enhance ecological resilience.