【Objective】Accurately and efficiently monitoring the spatio-temporal distribution characteristics of the ecological environment quality and its evolving trends in the source area of the Yangtze River is of great significance for maintaining the high-standard protection of the ecological environment. It also serves as a fundamental basis for formulating long-term and effective ecological protection and restoration strategies in the Sanjiangyuan region. The remote sensing ecological index (RSEI) has distinct advantages over traditional evaluation methods relying on single monitoring indices. It boasts rapid assessment capabilities, objectivity, high efficiency, strong visual interpretability, and reliable predictability. Nevertheless, the spatial resolution constraints and the complexity of data acquisition and processing in remote sensing images still present challenges to the large-scale and accurate evaluation of the RSEI.【Method】In this study, the Google Earth Engine (GEE) platform was utilized, with Landsat series images as the data source. Remote sensing images of the Yangtze River source area during the vegetation-growing season (from June to September) from 1990 to 2020 were obtained. Subsequently, long-time-series RSEI data were calculated. To comprehensively analyze the RSEI in the Yangtze River source area from 1990 to 2020, the coefficient of variation was applied to measure its stability, the Sen + Mann-Kendall (Sen + MK) trend analysis was used to explore the spatio-temporal change trends, the Hurst index was employed to predict future evolution, and the trend analysis method was adopted to identify the driving forces behind these changes.【Result】(1) From 1990 to 2020, the RSEI values in the Yangtze River source region were predominantly distributed within the range of 0.4-0.6. Geographically, the region exhibited a clear pattern where the RSEI values were higher in the eastern and southern parts and lower in the western and northern parts.(2) The average coefficient of variation of the RSEI in the source region was 6.52%. This indicates that the ecological environment in the eastern and western regions underwent relatively more pronounced fluctuations, while the central region remained relatively stable. Overall, the RSEI showed a slow oscillating trend, with an average annual growth rate of 0.004 7. Spatially, the RSEI presented an overall upward trend, and the area with improved ecological conditions accounted for 83.63% of the total study area.(3) The average Hurst index value of the RSEI in the source region was 0.53, implying that the future changes of the RSEI were more likely to be continuous rather than show anti-sustainability. The future ecological environment quality in the Yangtze River source region was expected to experience continuous improvement, yet the overall trend was relatively mild, and there still existed an underlying risk of degradation.(4) In the Yangtze River source region, the RSEI was positively correlated with air temperature, night-light index, and potential evapotranspiration. This reveals that both natural factors and human activities had a certain degree of influence on the enhancement of the ecological environment quality.【Conclusion】The integration of using GEE for remote sensing data acquisition and time-series data analysis has significant potential for rapidly and comprehensively monitoring the ecological environment quality on a large scale. This approach can offer valuable references and technical support for ecological monitoring and protection efforts in the Sanjiangyuan area, thereby contributing to the sustainable development of the regional ecological environment.