Abstract: Under the strategic background of ecological protection and high-quality development in the Yellow River Basin, it is of great significance to carry out ecological quality evaluation and time-series analysis of the Fenhe River Basin, which would be helpful for the policymaking of ecological protection and sustainable development. Based on the Google Earth Engine platform, using greenness (NDVI), humidity (Wet), heat (LST) and dryness (NDBSI), as well as soil salinity (BCSI) and PM_2.5 concentration as indicators, we constructed a standardized remote sensing ecological index (SRSEI) by principal component analysis and used it to evaluate the ecological quality of the Fenhe River Basin. We further analyzed the time-series dynamic characteristics of the ecological quality of the Fenhe River Basin using Theil-Sen median trend analysis, Mann-Kendall test, and Hurst index. The multi-year (from 2000 to 2020) average correlation between SRSEI and various indicators was 0.8191. From 2000 to 2020, the average value of SRSEI of the Fenhe River Basin increased from 0.4133 to 0.5176. In the basin, the ecological quality of the mountains was the best, and that of the depression was the worst. In the basin, the area proportion of ecological improvement and deterioration area was 83.32% and 15.96%, respectively. The area proportion of ecological continuous improvement and deterioration was 19.3% and 5.98% respectively. The areas with ecological deterioration in mountains and depression accounted for 26.21% and 52.87% of the ecological deterioration areas of the river basin, respectively. In conclusion, the results of ecological assessment of Fenhe River Basin by SRSEI were reliable. From 2000 to 2020, the ecological quality of the Fenhe River Basin showed an overall improvement trend. The ecological deterioration mainly occurred in the depression. The ecological management of the basin should be strengthened, ecological facilities should be built, and ecological shelter forests should be planted to avoid excessive damage to nature by humans.

Key words: Fenhe River Basin, standardized remote sensing ecological index, ecological quality evaluation, time series dynamic characteristic, principal component analysis