Abstract: Based on Landsat-5/TM and Lansat-8/OLI remote sensing images from the central region of Urumqi in 1990, 2000, 2010 and 2020. Greenness （NDVI）, humidity （Wet）, dryness （NDBSI）, heat index （LST） were selected, and the RSEI （Remote Sensing Ecological Index）model was constructed by the Principal Component Analysis（PCA） method to evaluate the changes in ecological environment quality in the central urban area of Urumqi over the past 30 years. The results showed that： ①Wet and NDVI had a positive impact on the quality of the ecological environment, and Wet had the greatest contribution rate to the quality of the ecological environment. LST and NDBSI had a negative impact on the quality of the ecological environment, and NDBSI had the greatest contribution rate to the quality of the ecological environment. ②Over the past 30 years, the ecological environment quality in the central district of Urumqi had been on the rise. ③Through the analysis of RSEI changes, it could be seen from the change trend of ecological environment quality in Urumqi’s central urban area that the area proportion of “general”“good” and “excellent” grades increased, the change of “poor” grade was stable, and the area proportion of “poor” grade decreased significantly. Therefore, it can be seen that the ecological environment base of Urumqi’s downtown area is poor and developing in a good direction, but the development process is slow.

Key words: ecological environment quality, remote sensing ecological index, principal component analysis