Spatio-temporal Distribution of Influencing Factors of Agricultural Sustainable Development in China

Guided by the United Nations Sustainable Development Goals, the research focuses on the sustainable development of agriculture. Based on the data of China's agricultural and economic development from 2013 to 2022, using entropy method to build the agricultural green development index (AGDI) system. Furthermore, the geographically and temporally weighted regression (GTWR) model was used to analyze the impact of seven factors on AGDI, namely, Urbanization rate (UR), Financial support for agricultural level (FSAL), Number of village health clinics (NVHC), Sulfur dioxide emissions (SDE), Chemical oxygen demand emissions (CODE), Education funding (EF), and educational attachment (EA). The results show that (1) AGDI in different regions is highly consistent in temporal evolution, but the spatial distribution is significantly different, showing a pattern of high in the south of the east – secondary high in the middle – low in the northwest and northern parts of the region. (2) The influence of each factor on AGDI has obvious spatiotemporal heterogeneity. For example, SDE had a negative impact throughout the investigation period, with the largest fluctuation amplitude; The effects of FSAL and NVHC are relatively stable. (3) The impact of EA remains consistent in different regions in 2013 and 2022. The impact of FASL and NVHC is mainly in the east and northeast, the impact of CODE is mainly in the east and central, and the impact of EF and SDE is mainly in the northeast. The research results not only reveal the spatiotemporal characteristics of green development in Chinese agriculture, but also provide reference for policy-making.