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[Display omitted] • We utilized the RSEI feature space to map the level and change of ecosystem quality in the east region of Loess Plateau. • The long-term implementation of ecological restoration projects has improved the ecosystem quality in Shanxi. • Temperature, slope, and elevation are the primary factors influencing ecosystem quality in the east of Loess Plateau. • Compared to the past, economic development has exerted a greater negative impact on ecosystem quality. • The geographically weighted regression model can better explain the local variations affecting ecosystem quality. The fragile ecological environment and intensive human activities in the Loess Plateau region of China have led to serious soil erosion and adverse weather disasters. To address these issues, the Chinese government has implemented a series of large-scale ecological restoration projects with significant investments and broad public participation. Throughout this process, the ecosystems have undergone substantial artificial intervention. This study utilizes MODIS data to establish a remote sensing ecological index (RSEI) for evaluating the ecosystem quality of Shanxi Province, located in the eastern Loess Plateau, over the past 20 years (2000–2020). Furthermore, the study analyzed the natural and socio-economic factors that influence the local ecosystem quality using Geodetector analysis. The research findings revealed the following: 1) Over the 20-year period of large-scale ecological restoration projects, the ecosystem quality in Shanxi has significantly improved, as indicated by the average RSEI index increasing from 0.48 to 0.57. 2) The southern part of the province has experienced relatively better ecosystem recovery, while the ecosystem quality in the northern and western regions, particularly along the Yellow River, remains poor. 3) Overall, the major factors influencing ecosystem quality are natural geographical factors such as temperature and slope. However, with rapid urbanization, the negative impacts from socio-economic factors represented by GDP have intensified, particularly in the northern regions. Additionally, this study demonstrated that the geographically weighted regression model can better explain the local variations affecting the RSEI and exhibits a high degree of reliability. The research findings provide scientific and effective references for evaluating the ecosystem quality in the Loess Plateau and implementing ecological restoration projects. [ABSTRACT FROM AUTHOR]