[Objectve] Using remote sensing technology to objectively and timely dynamic monitor the urban ecological environment status and change information was of great significance for urban ecological planning, management and protection. [Methods] Nanning, the most critical core city of the China-Asean economic circle and the Beibu Gulf urban agglomeration, located in the transitional zone from karst mountain to non-karst basin in Guangxi. Here, this paper collected Landsat TM/ETM+/OLS historical images of the same season from 2000 to 2020 year, and removed images clouds, chromatic aberration on Google Earth Engine (GEE) platform at the pixel level. Meantime, the median value composite was adopted to calculate four remote sensing indicators including greenness, wetness, dryness and heat, and the remote sensing ecological index (RSEI) was constructed by principal component analysis (PCA) to evaluate the dynamic changes and spatial differentiation characteristics of urban ecological environment quality in Nanning city, under the help of parallel cloud computing ability in GEE. [Results] The average value of RSEI was 0.615 in Nanning city, and its ecological environment quality had shown a fluctuating upward trend of "down- rise- stable". The spatial heterogeneity of ecological environment quality in Nanning city was obvious. The areas with better ecological environment quality mainly concentrated on the nature reserves, forest land, grassland and water area, while the degraded areas of ecological environment quality were mainly distributed in the cities, urban-rural combination zone and farming areas. RSEI had a positive correlation with greenness and wetness indicators, while negatively correlated with dryness and heat. [Conclusion] RSEI could well characterize the ecological environment quality of Nanning city, and the overall ecological environment quality was at a good level from 2000 to 2020. This paper provided and demonstrated that GEE could effectively improve the remote sensing images quality efficiency and be used as a computing platform for monitoring and assessing the ecological environmental quality in the urban region and long-term sequence.