[Improvement and Accuracy Analysis of Remote Sensing Evaluation Model for Yanhe River Basin Ecological Environment...

The ecological environment serves as the foundation for human survival and development, making the establishment of accurate and efficient evaluation models vital for assessing its stability and security. Based on the remote sensing ecological index (RSEI), this study employs the moving window and entropy weight methods to develop the regional optimized remote sensing ecological index (RO-RSEI) and the modified remote sensing ecological index (M-RSEI). Using the Yanhe River Basin as a case study, the optimization effects of the models are comparatively analyzed. The results indicate that: ① The RO-RSEI model, constructed by incorporating the moving window method into the RSEI framework, effectively addressed regional disparities but was limited in its capacity for large-scale application. ② Building upon the RO-RSEI model, the M-RSEI model, developed using the entropy weight method, significantly enhanced the evaluation accuracy of ecological environment quality, particularly in areas with high and low index values. It also enabled efficient large-scale monitoring. ③ From 2000 to 2020, the overall ecological environment quality of the Yanhe River Basin improved gradually, with most areas classified as "moderate." Spatially, the southeastern region exhibited better quality than the northwestern region, with the focus of ecological restoration shifting progressively northwestward. Comparative analysis demonstrated that the M-RSEI model offered superior precision for monitoring ecological environment quality at basin or regional spatial scales.