Quantifying the relative roles of climate change and human activities in vegetation change is essential for sustainable restoration planning, yet the impacts of extreme climate events and their time-lagged effects are often overlooked, biasing assessments of climatic controls. Here, we developed an integrated pattern-process-attribution framework to evaluate vegetation dynamics across China's four major climatic zones using a long-term, high-resolution kernel normalized difference vegetation index (kNDVI) dataset for 2000-2024. Theil-Sen trend estimation and the coefficient of variation (CV) were used to characterize long-term changes and interannual stability. Partial correlation analysis was applied to isolate the independent associations between kNDVI and extreme climate indices while controlling for background mean temperature and precipitation, and lagged correlation analysis with 0-3-month lags was used to quantify delayed responses. A regression-based residual attribution was further used to decompose observed kNDVI changes into a climate-driven component and a human-activity-related component (approximated by the residual not explained by temperature and precipitation). Results show widespread greening with pronounced spatial heterogeneity, with the most extensive improvement in the Tropical and Subtropical Humid Region and the Temperate Humid and Semi-humid Region. Vegetation stability exhibits a southeast-northwest contrast, and the highest variability occurs in the Temperate Arid and Semi-arid Region and the western Qinghai-Tibet Plateau. Responses to climate extremes are region-dependent and generally short-lagged (mean 0.35-1.05 months), with drought constraints dominating in arid regions and thermal extremes (TXx) most relevant on the plateau. Nationally, human activities contribute 70.8% of vegetation change, exceeding the climate-driven contribution (29.2%).