<p>Monitoring the spatio-temporal variations of vegetation net primary productivity (NPP) and identifying its climatic drivers are crucial for achieving carbon neutrality and mitigating climate change. Using the Geographic Detector Model, Theil-Sen Median analysis, Mann-Kendall test, and Hurst index, this study investigated the spatio-temporal variations and driving factors of vegetation NPP across China from 2001 to 2023. The analysis was based on MODIS NPP time series data combined with environmental variables, including 10m wind speed, downward surface shortwave radiation, Palmer Drought Severity Index (PDSI), soil moisture, temperature, and precipitation. Results indicated that vegetation NPP in China showed an increasing trend with a growth rate of 29×10⁻³gC/(m² yr) from 2001 to 2023. Spatially, vegetation NPP showed a distribution pattern characterized by higher values in the south than in the north, and higher values in the southeast than in the northwest, with an average value of 410.03gC/ (m² yr). Over the past 23 years, the trend of vegetation NPP changes has shown a significantly increasing trend, accounting for 77.6% of the total area of the study area. Geographic Detector result showed that among the six influencing factors, precipitation had the greatest impact on vegetation NPP, followed by soil moisture, temperature, wind speed, and radiation, whereas PDSI had the weakest influence. The interaction factor analysis indicates the presence of bi-linear interactions, including precipitation and downward surface shortwave radiation, precipitation and PDSI, temperature and soil moisture, and precipitation and soil moisture. Hurst index was 0.42, indicating short-term dependence that changes in China’s vegetation NPP are mainly influenced by short-term factors, with weak persistence of long-term trends, affecting 81.54% of the study area.</p>