Objective Quantitative analysis of the coupling coordination relationship between the ecological environment and socioeconomic development in China's poverty-alleviated counties, along with the identification of influencing factors, is of great significance for summarizing poverty alleviation experiences and consolidating the achievements of poverty eradication efforts.Method Based on long-term and high-resolution remote sensing datasets, this study constructed a comprehensive evaluation index system for both the ecological environment and socioeconomic development across 832 poverty-alleviated counties in China. It quantitatively assessed the development levels and coupling coordination status of these two dimensions in 2010, 2015, and 2020. Furthermore, a Boosted Regression Tree model was employed to identify the contribution rates of various indicators to the regional coupling coordination development.Result The results indicated that, overall, the ecological environment in poverty-alleviated counties exhibited a higher level of comprehensive development compared with socioeconomic factors. However, the socioeconomic development progressed at a faster pace than ecological improvements. In addition, the average annual growth rates of both dimensions from 2015 to 2020 were higher than those from 2010 to 2015. Spatially, the coupling coordination degree was the highest in northeastern counties and the lowest in the northwest, showing a distribution pattern of “high in the east and low in the west” and a trend of progressive improvement from coastal to inland areas. Most counties were categorized as “economically lagging”. Among all indicators, population size, gross domestic product, and nighttime light intensity made particularly significant contributions to the coupling coordination.Conclusion Drawing from the poverty alleviation paths and practical experiences of typical regions, the study concludes that implementing context-specific industrial poverty alleviation strategies is crucial for accelerating socioeconomic development in poverty-alleviated counties. Establishing diversified, locally distinctive industries is identified as a key approach for consolidating poverty alleviation achievements and preventing a return to poverty.

poverty-alleviated counties;ecological environment;socioeconomic development;Remote sensing dataset;coupling coordination;boosted regression tree model;contribution rate;spatial distribution pattern;industrial poverty alleviation