Vegetation across Asia exhibits complex structural and functional adjustments under intensifying climatic and anthropogenic pressures. However, the spatial coherence between vegetation greenness and photosynthetic function remains poorly understood at continental scales. Here we integrate satellite-derived solar-induced chlorophyll fluorescence (SIF) and normalized difference vegetation index (NDVI) with machine-learning attribution and residual diagnostics to disentangle the respective roles of climate variability and human influence from 2001 to 2021. Our results reveal that nearly 60% of the vegetated area in Asia experienced concurrent increases in SIF and NDVI, while about 40% displayed pronounced divergence between vegetation structure (NDVI) and function (SIF), particularly in high-elevation and arid ecosystems. Temperature predominantly controls photosynthetic efficiency, precipitation governs canopy greenness in croplands and grasslands, and solar radiation modulates mixed-forest productivity. Residual analysis further identifies strong human-induced functional enhancement in intensively managed regions of East and Southeast Asia, contrasting with degradation in overgrazed or fragmented drylands. By integrating these climatic and anthropogenic signals, we delineate eleven vegetation sensitivity zones based on dominant climate and anthropogenic driver combinations that capture the heterogeneity of ecosystem resilience and vulnerability. This structural-functional framework provides a mechanistic basis for assessing vegetation responses to global change and supports the design of spatially targeted ecological and carbon-neutrality strategies across Asia.