The Dynamic Distribution and Convergence Trends of Digital Agriculture Development in China
Promoting the development of digital agriculture is an essential pathway to comprehensively revitalize rural areas and achieve agricultural and rural modernization.A comprehensive analysis of the distribution characteristics and development trends of digital agriculture in China is of significant policy importance.Based on relevant 2012-2021 data of 31 provinces and municipalities in China,the dynamic development levels of digital agriculture in each region were calculated.Non-parametric kernel density estimation and Markov chain transition matrices were employed to reveal the dynamic evolution trends of its distribution.Convergence analyses,including σ-convergence and β-convergence,were conducted using the coefficient of variation method and spatial panel models to interpret spatial convergence trends.According to the study,the overall development level of digital agriculture in China shows an upward trend,but significant spatial differences exist among regions,presenting a gradient distribution pattern from east to west.There is an increasing trend in the overall gap in the development of digital agriculture nationwide,with evident polarization characteristics and significant convergence features and spatial effects.Regions in China should increase financial investment in the development of digital agriculture,improve agricultural digital infrastructure,and adopt a path of characteristic digital agriculture development based on local conditions.Additionally,regions should strengthen cross-regional and cross-industry collaboration in digital agriculture,optimize and improve support policies,and establish an effective support system to facilitate the digital transformation of agriculture.
digital agriculturedistribution dynamicskernel density estimationMarkov Chainconvergence
NETL
NSTL
万方数据
