Rural Transformation in Northern Anhui, China: Spatio-Temporal Patterns and Driving Mechanisms in Traditional Agricultural Areas

Abstract

Rural transformation is crucial to alleviating development pressure on traditional agricultural areas and stimulating rural vitality. This study aims to comprehensively analyze the spatio-temporal patterns, identify the key influencing factors, and propose targeted development strategies for rural transformation specifically within Northern Anhui, a quintessential traditional agricultural area in China. Utilizing the entropy method, exploratory spatial analysis, and geographic detector, we systematically evaluated the level of rural transformation and its spatial distribution characteristics across 35 counties and districts in Northern Anhui from 2011 to 2023. The results demonstrate a significant 35.93% increase in the average rural transformation level over the past decade, evolving from an initially low-level pattern to one characterized by “Central high, peripheral low”, with significantly narrowing disparities between counties and districts. Significant global positive spatial autocorrelation was consistently observed, alongside distinct localized clustering, including high-value clusters (H-H) and low-value clusters (L-L). A driver analysis identified investment efficiency, economic development level, industrialization, transportation accessibility, and fiscal revenue level as the predominant factors driving the spatial differentiation of rural transformation, with interaction detection revealing crucial synergistic effects among these factors. These findings provide valuable empirical insights and a scientific basis for formulating differentiated rural development strategies tailored to specific county types within traditional agricultural areas like Northern Anhui, thereby facilitating the rural transformation process in developing countries.