Previous studies have identified climate warming as a major driver of increased productivity in China's Qinghai-Tibet Plateau (QTP), where temperature serves as the primary driver of productivity changes [11]. In contrast, precipitation and radiation are noted as the main influences on productivity in Northeastern and Southwestern China [12]. Recent research highlights precipitation as a critical factor in vegetation change in Northwestern China's arid and semi-arid regions, with even slight increases significantly boosting vegetation [13]. However, some studies indicate that climatic factors have inhibited vegetation growth in the Three Rivers Source Region [14]. The impact of climatic factors on vegetation productivity changes in Northern China remains debated, especially concerning future climate scenarios. Given these findings, this study focused on temperature, precipitation, radiation, and forest cover as the primary factors influencing GPP. These factors were selected due to their demonstrated effects on vegetation growth: temperature affects metabolic rates, precipitation is essential for moisture availability, and radiation provides the energy for photosynthesis. Additionally, forest cover serves as a key indicator of human influence on vegetation dynamics, reflecting the impact of extensive ecological restoration projects across the region. Furthermore, with the implementation of large-scale ecological engineering initiatives, human activities have increasingly become significant drivers of vegetation changes, largely dominating vegetation greening across many parts of the country [15; 16]. While these restoration efforts are credited with contributing to greening [17; 18], urban expansion has adversely affected urban vegetation [19]. Notably, research quantifying the effects of climate factors and changes in vegetation coverage on productivity in Northern China--an area critical for afforestation and reforestation--has not been adequately evaluated. Several studies have employed the residual method, using vegetation indices (e.g., normalized difference vegetation index) or vegetation productivity models combined with climate data. However, this method may not fully capture the influence of climate factors or effectively separate the distinct effects of different variables. It also falls short in assessing the impact of ecological engineering on vegetation [20]. Unlike vegetation indices, gross primary production (GPP) directly measures carbon fixation through photosynthesis [21], offering a more nuanced view of vegetation activity and its feedback on the carbon cycle and climate change [12; 22]. Therefore, this study adopted GPP as a measure to examine vegetation changes and the contributions of climate factors in Northern China's ecological engineering areas, considering radiation, precipitation, and temperature as climate indicators. In addition to introducing GPP as an indicator of vegetation productivity, this study utilized continuous forest cover data from MODIS, which provides high-resolution, temporally continuous observations, allowing for detailed, large-scale assessments of vegetation dynamics over time. These data are particularly well-suited for capturing subtle changes in forest cover, thereby offering a comprehensive representation of vegetation changes in the ecological restoration areas. Furthermore, the study employed ridge regression analysis to examine the relative contributions of driving variables. This approach can effectively distinguish the complex interactions between vegetation and climate factors and avoid the multicollinearity problem [23; 24], and aim to provide a comprehensive understanding of contributions of vegetation dynamics and climate factors on vegetation productivity in the region. Northern China, a significant contributor to global vegetation greening with diverse ecosystems, has experienced widespread human impact through afforestation.