Evaluation and Driving Force Analysis of Ecological Environment Quality in Arid Region with Typical Case Study

To objectively and accurately evaluate the ecological environment quality in arid regions,based on the remote sensing ecological index (RSEI) and according to the characteristics of arid regions,the ERSEI evaluation system was proposed by integrating five factors: SAVI,LST,WET,NDBSI and SI.Four LandsatTM/OLI remote sensing images were selected to quantitatively evaluate the ecological environment quality of Yongchang County from 1994 to 2023.Based on principal component analysis,coefficient of variation and Moran's I index,the spatial and temporal distribution characteristics and trends of ERSEI in Yongchang County in the past 30 years were discussed.The Geodetector model was further applied to quantify the driving factors.The results showed that:①The introduced SI was highly negatively correlated with ERSEI,and the average contribution rate of PC1 in ERSEI was 1.47% higher than that in RSEI,which could comprehensively reflect the ecological environment characteristics of the study area.②From 1994 to 2023,the annual average of ERSEI index in Yongchang County was 0.469,the proportion of areas classified as having "poor" ecological quality expanded significantly,indicating a notable overall decline,with the average proportion of deteriorating areas being 36.25% and the average proportion of improving areas being 26.94%,suggesting a trend toward ecological deterioration in Yongchang County.③Analysis of the variation coefficient indicated that,ecological environment quality in most areas of Yongchang County exhibited low fluctuation.Moran's I index analysis showed spatially significant clustering in Yongchang County,with high quality ecological areas concentrated in high-altitude forest areas,and low quality ecological areas mainly distributed in saline-alkali land and densely populated areas.④The analysis of geodetector showed that land use is the main driving factor of ERSEI change,followed by precipitation,elevation and temperature.The interaction between land use and elevation,precipitation and temperature demonstrated a high explanatory power.