Regional Differences and Dynamic Evolution Trajectories of China’s Low-Altitude Economy Modernization and High-Quality Agricultural Development Levels

低空经济和农业高质量发展是一项紧迫而艰巨的任务。本文运用了熵权法、Dagum基尼系数、Kernel密度估计法定量评估2010年~2023年中国低空经济现代化与农业高质量发展水平的区域差异性和动态演进趋势。研究发现：低空经济与农业高质量发展在总体差异上分别呈现“先显著均衡化、后期微分化”、“强波动性收敛”的特征；两者的区域内差异主导全局差异，区域间差异形成时序反转与竞争的格局：低空经济区域间“反超式收敛”，农业高质量发展区域间差异形成“M形博弈”；由核密度图可知：2010年~2023年三个不同区域的低空经济经历了从“依赖少数顶尖主体拉动”转向“多数主体共同提升”；在农业高质量发展方面，多数地区的发展水平仍呈现上升趋势，多数地区摆脱了低水平阶段，向中高端水平迈进；然而，峰值频繁变化也凸显了不同地区农业可持续发展过程的复杂性。未来，我们应引入动态空间面板模型，揭示低空经济与农业高质量发展的空间交互效应。The modernization of the low-altitude economy and the high-quality development of agriculture are urgent and arduous tasks. This paper employs the Entropy Weight Method, the Dagum Gini coefficient, and Kernel density estimation to quantitatively assess the regional differences and dynamic evolution trends of China’s low-altitude economy modernization and high-quality agricultural development from 2010 to 2023. The study finds that: in terms of overall differences, the low-altitude economy and high-quality agricultural development exhibit the characteristics of “significant initial equalization followed by slight differentiation” and “strongly fluctuating convergence,” respectively. The intra-regional differences of both dominate the overall disparities, while the inter-regional differences form a pattern of temporal reversal and competition. Specifically, there is an “anti-overtaking convergence” among regions in the low-altitude economy, and an “M-shaped game” in inter-regional differences of high-quality agricultural development. According to the Kernel density maps, from 2010 to 2023, the low-altitude economy in three different regions has shifted from “being driven by a few top players” to “the collective improvement of multiple players”. In the context of high-quality agricultural development, the development levels of most regions have been on the rise, with many areas emerging from the low-level stage and advancing towards the mid-to-high-end. However, the frequent changes in peak values highlight the complexity of the sustainable development process in different regions. In the future, we should introduce a dynamic spatial panel model to reveal the spatial interaction effects between the low-altitude economy and high-quality agricultural development.