肖铁桥, 杜景莉, 杨婷. 安徽县域乡村振兴发展的时空特征及影响因素[J]. 云南农业大学学报(社会科学), 2023, 17(1): 10−17. doi: 10.12371/j.ynau(s).202208038
引用本文: 肖铁桥, 杜景莉, 杨婷. 安徽县域乡村振兴发展的时空特征及影响因素[J]. 云南农业大学学报(社会科学), 2023, 17(1): 10−17. doi: 10.12371/j.ynau(s).202208038
XIAO Tieqiao, DU Jingli, YANG Ting. Spatiotemporal Characteristics and Influencing Factors of Rural Revitalization and Development in Counties in Anhui Province[J]. Journal of Yunnan Agricultural University (Social Science), 2023, 17(1): 10-17. DOI: 10.12371/j.ynau(s).202208038
Citation: XIAO Tieqiao, DU Jingli, YANG Ting. Spatiotemporal Characteristics and Influencing Factors of Rural Revitalization and Development in Counties in Anhui Province[J]. Journal of Yunnan Agricultural University (Social Science), 2023, 17(1): 10-17. DOI: 10.12371/j.ynau(s).202208038

安徽县域乡村振兴发展的时空特征及影响因素

Spatiotemporal Characteristics and Influencing Factors of Rural Revitalization and Development in Counties in Anhui Province

  • 摘要: 以安徽省59个县级单元(县、县级市)为研究对象,构建乡村振兴发展水平评价体系,借助熵值法、空间自相关、地理探测器等研究方法探寻2010—2019年安徽省县域乡村振兴发展水平时空演化特征及影响因素。研究表明:(1)2010—2019年,安徽省县域乡村振兴水平呈现上升势态,区域差异较为显著。(2)乡村振兴发展水平呈现出正自相关性特征,由西到东呈现递增势态,由南到北呈现倒“三角”形;热点区的县集聚在合肥、滁州和马鞍山市,冷点区的县主要集中在大别山革命老区。(3)经济、产业、区位等多因素综合作用影响2010—2019年安徽省乡村振兴发展时空演化。其中人均地区生产总值是影响安徽省乡村振兴发展的主导因素,碳排放量、设施农业占地面积、第二、三产业增加值占比和与所属地级市的距离对安徽省乡村振兴发展具有显著的影响。未来安徽省应充分考虑各地乡村振兴水平差距,因地制宜,确定差异化乡村振兴路径及发展方向。

     

    Abstract: Based on 59 county-level units (counties and county-level cities) in Anhui Province, an evaluation system of rural revitalization development level was constructed, and the temporal and spatial evolution characteristics and influencing factors of rural revitalization development level at county level in Anhui Province from 2010 to 2019 were explored by means of entropy method, spatial autocorrelation and geographic detector. The results show that: (1)From 2010 to 2019, the level of rural revitalization at county level in Anhui Province showed an increasing trend, with significant regional differences. (2)The development level of rural revitalization showed positive autocorrelation, increasing trend from west to east, and inverted triangle from south to north; Counties in hot spots were concentrated in Hefei, Chuzhou and Maanshan, while counties in cold spots were mainly concentrated in dabie Mountain old revolutionary base area. (3)The comprehensive effects of multiple factors such as economy, industry and location affected the spatio-temporal evolution of rural revitalization development in Anhui Province from 2010 to 2019. Among them, per capita GDP was the leading factor affecting rural revitalization development in Anhui Province. Carbon emissions, area occupied by facility agriculture, proportion of added value of secondary and tertiary industries and distance from prefecture-level cities had a significant impact on rural revitalization development in Anhui Province. In the future, Anhui province should fully consider the gap in the level of rural revitalization, adjust measures to local conditions, and determine the path and development direction of differentiated rural revitalization.

     

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