Study on Temporal and Spatial Evolution and Influencing Factors of the Agricultural Modernization Development Level in Hunan Province
By constructing the evaluation index system of the agricultural modernization development level in Hunan Province from 2012 to 2021 and using the entropy weight method and spatial autocorrelation analysis method,this study analyzed its temporal and spatial evolution,and the obstacle degree model and spatial Dubin model were introduced to explore related influencing factors,so as to promote the agricultural modernization development in Hunan Province.The results showed that from 2012 to 2021,the agricultural modernization development level of Hunan Province showed a zigzag upward trend,but it still needed to be improved,and its spatial distribution had the characteristic of"high in the northeast and low in the southwest".It presented a spatial positive autocorrelation agglomeration distribution pattern,and the agglomeration degree was increasing,and main agglomeration types were HH agglomeration type and LL agglomeration type.The main obstacles to the development level of agricultural modernization in Hunan Province were the urbanization level and per capita disposable income of rural residents.The government support,regional transportation level,scientific and technological development level,medical condition level and opening-up level all had significant positive impacts on it,and the scientific and technological development level also had a significant positive spatial spillover effect.Hence,the study put forward some suggestions:to optimize the industrial structure and improve the regional layout,and to adapt to local conditions;to strengthen regional exchanges and cooperation to achieve common development;to develop agricultural industrialization consortium and build a modern agricultural management system;to improve the policy support system and strengthen financial,talent and technological support.
agricultural modernizationtemporal and spatial evolutioninfluencing factorsHunan Province
NETL
NSTL
万方数据
