Monitoring and Analysis of Eco-Environmental Quality in Daihai Lake Basin from 1985 to 2022 Based on the Remote Sensing Ecological Index

Exploring eco-environmental quality dynamics in the Daihai Lake Basin has significant implications for the conservation of ecological environments in the semi-arid and arid regions of northern China. Based on the Google Earth Engine (GEE) platform, the remote sensing ecological index (RSEI) was constructed by coupling Landsat SR remote sensing data from 1985 to 2022. The spatial significance of the RSEI was analyzed using linear regression equations and an F-test. The spatial correlation, distribution characteristics, and driving factors behind the RSEI were explored using Moran's index and a geodetector. The results indicated that (1) the RSEI was appropriate for evaluating eco-environmental quality in the Daihai Lake Basin. (2) From 1985 to 2022, the eco-environmental quality of the Daihai Lake Basin exhibited a positive trend but remained subpar. (3) A positive spatial autocorrelation was demonstrated for eco-environmental quality with increasing spatial aggregation. (4) Significant eco-environmental quality degradation (slope < 0) occurred primarily in Sanyiquan Town in the northeastern region of the basin and in Tiancheng Township in the southeastern region. Conversely, a notable improvement (slope > 0) was predominantly observed in Yongxing and Liusumu in southwestern Daihai. (5) The improvement in the ecological environment of the Daihai Lake Basin was primarily attributed to an increase in NDVI and WET and a decrease in NDBSI and LST. The interaction between NDVI and LST had the greatest explanatory power for the ecological environment. Among the external driving factors, DEM (elevation) was the dominant factor in the RSEI and had the strongest explanatory power. The interaction between DEM and LST was the most significant, and the driving factors were enhanced. This study provided a theoretical basis for the sustainable development of the Daihai Lake Basin, which is crucial for the local ecological environment and economic development.