Abstract: Vegetation dynamics play a critical role in regulating global carbon balance and maintaining ecosystem stability, rendering the elucidation of their driving mechanisms a central topic in ecological research. Hydrothermal conditions—principally temperature and precipitation—are widely recognized as primary factors governing vegetation growth and distribution; nevertheless, the long-term effects of these climatic factors on vegetation, particularly their time-lag characteristics, remain insufficiently understood at the national scale, and the differential response times of various vegetation types to temperature versus precipitation, as well as the spatial heterogeneity of these lag effects, have yet to be systematically quantified for China's diverse terrestrial ecosystems. To address these gaps, the present study investigated the spatiotemporal dynamics of vegetation across China and quantified the time-lag effects of vegetation response to hydrothermal factors, utilizing the NDVI dataset in conjunction with monthly precipitation and temperature data from 2001 to 2021. The analytical framework integrated three complementary methods, namely time-lagged partial correlation analysis, the Mann-Kendall trend test, and Sen's slope estimation, with the maximum lag time set to 3 months based on data-driven sensitivity analysis and physiological considerations—specifically, that a quarterly lag corresponds to the typical duration from water input through soil infiltration and root uptake to measurable canopy biomass accumulation in temperate monsoon climates. The results revealed three major findings. First, the spatial distribution of NDVI in China exhibited pronounced heterogeneity, with values lower in western than in eastern China and lower in northern than in southern regions; despite this spatial disparity, the overall trend was significantly positive, indicating widespread greening over the past two decades. Second, the time-lag effects differed substantially between temperature and precipitation: for temperature, the mean lag time across all vegetation types was approximately 0.8 months, with regions exceeding 3 months concentrated primarily in forested areas such as the Qinling-Daba Mountains, where dense forest cover and deep root systems allow vegetation to integrate thermal signals over extended phenological phases; for precipitation, the mean lag time was approximately 0.5 months, shorter than that for temperature, suggesting more rapid response to water availability, although partial correlation coefficients were relatively weak (below 0.3) in some areas of Southwest China, implying that water availability is not the primary limiting factor in these regions, possibly due to high background humidity and frequent cloud cover. Third, the response patterns varied significantly among vegetation types: for most categories—including forests, shrublands, and croplands—the lag time for precipitation was shorter than that for temperature; notably, however, grasslands presented an exception, where the relative magnitudes of temperature and precipitation lag times deviated from the general rule, likely attributable to shallower root systems and more direct dependence of herbaceous plants on immediate surface soil moisture, which may alter the timing balance between thermal and water constraints. Collectively, these findings demonstrate that the time-lag effects of vegetation to hydrothermal factors in China are shaped by the interplay of climatic background, vegetation functional type, and local environmental conditions, with the shorter lag for precipitation suggesting that water availability exerts more immediate control over vegetation greenness, whereas the longer lag for temperature reflects the cumulative nature of thermal effects on plant phenology and biomass accrual. This study contributes to a deeper understanding of vegetation–climate interactions in China's diverse ecosystems and provides empirical evidence for improving the prediction of vegetation responses under future climate change scenarios, with insights that may also inform adaptive ecosystem management and the formulation of regional strategies for ecological conservation.