Remote sensing time-series-based vegetation functional zonation for power transmission corridors in Northern Shaanxi, China

Résumé fourni par la source

To characterize the spatial differentiation of intra-annual vegetation growth rhythms in the Shaanbei transitional zone and to quantify the composition of transmission-line crossings across vegetation dynamic backgrounds, this study develops an integrated framework of “NDVI time series–feature construction–spatial dimensionality reduction–robust clustering–line statistics.” Fifteen dynamic features were derived from the 2025 annual NDVI time series. PC1–PC3 scores were obtained using geographically weighted principal component analysis (GWPCA) and used as inputs to K-medoids clustering (CLARA) to delineate vegetation functional zones with an optimal K = 3. The crossing length and proportion of transmission lines within each zone were then calculated. Results show that the cumulative local variance explained by PC1–PC3 ranges from 83.281% to 94.076% (median: 91.099%). The three zones are clearly separated in PC1–PC3 score distributions and form spatially continuous, clustered functional regions, exhibiting a sparse–moderate–dense gradient in vegetation cover/activity. Line statistics further indicate that the proportions of transmission-line length within the three zones are 8.20%, 61.50%, and 30.30%, respectively, implying that crossings of the Shaanbei high-voltage and ultra-high-voltage transmission network are unevenly distributed across vegetation dynamic backgrounds. These findings provide quantitative support for zonation-based corridor risk assessment and management strategy development.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.