Abstract: A comprehensive evaluation system for agricultural and rural modernization was constructed from five dimensions: Politics, economy, society, culture, and ecology. An improved entropy weight-grey correlation-TOPSIS model was utilized to calculate the comprehensive scores of 30 provinces (municipalities, autonomous regions) in China from 2013 to 2022, and their changing trends were analyzed. Meanwhile, exploratory spatial data analysis (ESDA) methods were employed to investigate the spatio-temporal evolution characteristics and regional disparities in the development level of agricultural and rural modernization. The results showed that the overall level of modern agricultural and rural development was on the rise. From the perspective of the average development level of each region, the pattern was mainly northeast region > eastern region > central region > western region. After 10 years of development, the number of provinces (municipalities, autonomous regions) with high, lower, and low levels decreased by one each, but the number of provinces (municipalities, autonomous regions) with higher levels increased significantly. The distribution of high and higher level areas shifted from being mainly concentrated in the eastern and northeast regions to being mainly concentrated in the central region. Modern agriculture and rural areas were mainly characterized by low-low clustering and high-high clustering in space. As time passed, the areas of low-low clustering gradually decreased.

Key words: agricultural and rural modernization, enhanced entropy weight-grey correlation-TOPSIS model, exploratory spatial data analysis