This study focuses on the spatiotemporal variations of ecological environment quality and its driving factors in the Yellow River Basin from 2000 to 2024. Based on MODIS (Moderate-Resolution Imaging Spectroradiometer) data and the Google Earth Engine (GEE) platform, an improved Remote Sensing Ecological Index incorporating the kernel-based normalized difference vegetation index (kRSEI) was constructed using principal component analysis (PCA). The spatiotemporal evolution of ecological environment quality was analyzed by integrating the Theil-Sen median trend analysis, Mann-Kendall test, Hurst exponent, and coefficient of variation. In addition, a Gradient Boosting model combined with SHapley Additive exPlanations (SHAP) was employed to identify the dominant driving factors of ecological environment quality. The results indicate that: (1) the first principal component (PC₁) of kRSEI explains 66.90%-78.05% of the total variance, consistently higher than that of the traditional RSEI across representative years, and the loading of kNDVI on PC₁ is generally higher than that of NDVI, demonstrating that the kernel-based approach enhances the representation of greenness information in integrated ecological assessment; (2) from 2000 to 2024, kRSEI in the Yellow River Basin exhibits a significant increasing trend (Slope=0.004 a^-1, P< 0.05), with mean values increasing from 0.36 to 0.52 (multi-year average of 0.46). Spatially, ecological environment quality shows a gradual improvement from north to south. SEN-MK analysis reveals that 67.67% of the basin experienced significant improvement, whereas Hurst exponent results indicate that 69.92% of the areas may exhibit anti-persistent upward trends in the future, suggesting potential risks of trend reversal in some improved regions; (3) soil moisture (SM), precipitation (PRE), and land use and land cover change(LUCC) are the primary drivers of spatial heterogeneity for kRSEI. Among them, SM has the highest mean SHAP value (>0.06), while PRE and LUCC both exceed 0.03, and the interaction between water conditions and land use exerts the strongest regulatory effect on ecological environment quality. These findings provide a quantitative basis for ecological environment assessment and zoning regulation in the Yellow River Basin.