The Chengdu-Chongqing Economic Circle, as an essential demonstration area for urbanization in western China, is critical in determining the quality of the natural environment. This exploration intends to support high-quality regional socio-economic development as well as ecological environmental protection in the upper reaches of the Yangtze River. Based on Landsat series image data from 2000 to 2020, we constructed a Remote Sensing Ecological Index (RSEI) containing greenness, wetness, heat, and dryness indicators. The spatial and temporal changes in regional ecological quality were explored using a trend analysis method combining Sen (Theil-Sen median) slope estimation and MK (Mann-Kendall) test. Furthermore, we employed the Optimal Parameters Geographic Detector (OPGD) model to optimise the scale and zoning effects of the spatial data, and to analyzed the driving forces of ecological environment quality in the study area. The results showed that: (1) From 2000 to 2020, the ecological environment quality in the study area was generally high, with a multi-year RSEI average value of 0.63. The ecological environment quality mainly classified as good or Excellent, covering 61.37% of the area. The ecological environment quality has obviously spatial heterogeneity.The spatial distribution pattern indicates "poor ecological quality in the core city of Chengdu-Chongqing, average quality in the plains and hills region in the central part of the study area, and excellent quality in the surrounding area". (2) According to the Sen-MK trend analysis showed that the degraded area of regional ecological environment quality is larger than the improved area, with the difference of 14.33%. This implies a considerable decline in the ecological environment quality of the research area, needing stronger steps to protect and restore the regional ecological environment. (3) The Optimal Parameters Geographic Detector model detection results showed that the optimal spatial scale for the drivers was 5 km. Additionally, five discrete methods-natural breaks, equal breaks, quantile breaks, geometric breaks, and standard deviation breaks were effective in detecting the optimal classification intervals of the drivers. Greenness, wetness, dryness, heat, slope, and average annual temperature were the dominant factors affecting regional ecological quality, with an explanatory power q-value greater than 56.95%. Land use type, population density, GDP, and nighttime light were secondary drivers. The interaction of these driving factors enhanced their influence on ecological environment quality. The results of this study can serve as model for the development of other western cities, as well as a scientific basis for promoting ecological environmental protection and sustainable, high-quality socio-economic development in the upper reaches of the Yangtze River.