Abstract: Rural revitalization can be facilitated to explore the spatiotemporal evolution of green development level, spatial diffusion, and convergence effect in modern agriculture. In this study, an evaluation system was constructed for green rural development. The global principal component analysis was carried out to measure the rural green development value in the 30 provincial administrative regions in China during 2006-2020. Visualized mapping and descriptive statistical analysis were used to depict the temporal characteristics, spatial patterns, and regional differences of green rural development levels. And then the spatial autocorrelation and convergence models were utilized to analyze the spatial diffusion and convergence effects of green rural development. The results show that: 1) There was a steady upward trend in the overall level of green development in the rural areas during the study period, with an average annual growth rate of 3.127%. A spatial pattern was found in the "High in the eastern region and low in the western region, while high in the southern region and low in the northern region". The temporal feature of the transition from the "low level and high gap" to the "high level and low gap". 2) There was a significant positive correlation in the spatial diffusion effect of green rural development level. The number of the "high-high" and "low-low" clusters was more than that of the "high-low" and "low-high" ones. The "high-high" cluster was mainly distributed in the eastern Beijing, Shandong, Jiangsu, and Shanghai Provinces, whereas, the "low-low" cluster was mainly concentrated in the western region. 3) The convergence effect of rural green development appeared in the whole country, except for the northeast region. The spatial absolute β convergence coefficient was ranked in the western region (β=-0.243) > eastern region (β=-0.069 2) > central region (β=-0.039), while the convergence rate was in the western region (0.02) > eastern region (0.005)> central region (0.003). The green rural development converged to a stable level under the influence of urbanization rate, per capita GDP, and per capita expenditure on science and technology. The direction and degree of each factor varied significantly over the country. The finding can also provide the guiding significance and decision-making support to narrow the gap in green rural development.