Abstract: Zhouqu County is located in the transition region from the Qinghai-Tibet Plateau to the Qinba Mountains, and is an important part of the ecological barrier in the upper stream of the Yangtze River. In this study, we used the Google Earth Engine cloud processing platform to perform inter-image optimal reconstruction of Landsat surface reflectance images from 1998-2019. We calculated four indicators of regional wet, green, dry, and hot. The component indicators were coupled by principal component analysis to construct remote sensing ecological index (RSEI) and to analyze the spatial and temporal variations of ecological environment quality in Zhouqu County. The results showed that the contribution of the four component indicators to the eigenvalues of the coupled RSEI were above 70%, with even distribution of the loadings, indicating that the RSEI integrated most of the features of the component indicators. From 1998 to 2019, the RSEI of Zhouqu County ranged from 0.55 to 0.63, showing an increasing trend with a growth rate of 0.04·(10 a)^-1, and the area of better grade increased by 425.56 km². The area with altitude ≤2200 m was dominated by medium and lower ecological environment quality grade, while the area of better ecological environment quality grade area increased by 16.5%. The ecological and environmental quality of the region from 2200 to 3300 m was dominated by good grades, increasing to 71.3% in 2019, with the area of medium and below ecological and environmental quality grades decreasing year by year. The area with altitude ≥3300 m was dominated by the medium ecological quality grade. The medium and below ecological quality grades showed a “U” shape trend during the study period. The trend of ecological environment quality in Zhouqu County was becoming better, but with fluctuations. It is necessary to continuously strengthen the protection and management of ecological environment in order to guarantee the continuous improvement of ecological environment quality.

Key words: Google Earth Engine, remote sensing based ecological index, principal component analysis, ecological quality