Abstract
Green development is a concept of sustainable development, aiming to protect the environment and ecosystems while meeting economic development needs. In the field of agriculture, green development has emerged as a crucial pathway for reconciling the conflicts between agricultural development and ecological conservation. To investigate the level of green development in Chinese agriculture, regional variations, and the evolutionary patterns, this paper is based on the framework of sustainable development theory. This study establishes a comprehensive evaluation system for agricultural green development and applies methods such as entropy-weighted TOPSIS, Dagum’s Gini coefficient, kernel density estimation, Moran’s I index, and Markov chains to analyze the level of agricultural green development, regional disparities, and dynamic evolution in China. The findings of this study reveal that: (1) The overall level of agricultural green development in China is steadily improving, with notable differences in the level of agricultural green development among different regions and provinces. There are significant disparities in agricultural green development between regions, and the overall disparities exhibit a fluctuating downward trend characterized by periods of increase followed by decrease. The regional disparities are identified as the primary cause of the overall disparities in agricultural green development in China. (2) The eight major economic regions in China are experiencing steady development in agricultural green practices, but there are varying degrees of polarization due to different development speeds. (3) This study also highlights a clear spatial positive correlation in the level of agricultural green development in China, with most provinces showing clustering in the first and third quadrants, indicating a “high–high” (H-H) and “low–low” (L-L) agglomeration pattern. (4) The study reveals that the level of agricultural green development in China exhibits a certain degree of stability. Over time, the probability of transitioning from lower-level regions to neighboring higher-level regions increases, and the agricultural green development level in neighboring regions can influence the spatial transfer probability within a given region. Therefore, agricultural green development demonstrates significant spatial dependence.
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