Analysis of the temporal and spatial changes of ecological environment quality using the optimization remote sensing ecological index in the middle Yellow River Basin, China

Abstract

Monitoring and assessing spatiotemporal changes and driving factors of ecological environment quality in the middle Yellow River Basin (MYRB) is significant for ecological environment protection, management, and high-quality development. We reconstructed data from 1986‒2023 Landsat series images using the harmonic analysis of time series (HANTS) algorithm on the Google Earth Engine platform to optimize the remote-sensing ecological index (RSEI) calculation process, and analyzed the trends and sustainability of ecological environment quality changes. The HANTS algorithm reduced dispersion and anomalies, filled in missing images, and enhanced the Landsat series image quality. The RSEI accurately reflected the ecological environment quality from 1986‒2023 in the MYRB, reducing the "pseudo-variation" conclusion of multi-year evaluations, and enhancing the stability of regional ecological environment quality assessments. Ecological environment quality in the MYRB generally showed an improving trend from 1986‒2023, with significant improvement covering 71.6% of the area; however, the change in ecological environment quality showed weak sustainability. The results reflected the positive effects of ecological restoration and the negative impact of urban construction. The optimized RSEI effectively reflected the ecological environment quality of the MYRB, improved the long-term RSEI stability, and satisfied the requirements of large-scale and long-term ecological environment quality monitoring.