Measurement and coupling coordination promotion path of agricultural green development level in the Hexi Region
Researching the level of agricultural green development and its internal coupling coordination promo-tion path is conducive to promote resource conservation,agricultural ecological restoration,green technology support and high-quality development in the Hexi Region.Responding to the national policy arrangements,we adopt the latest monitoring and evaluation index system proposed in the"Agricultural Green Development Level Monitoring and Evaluation Method(Trial)".Based on the panel data of 5 cities in the Hexi Region of Gansu Province from 2018 to 2022,using the entropy weight method and coupling coordination degree model,we mea-sured the level of agricultural green development in the region,deeply explored its internal coupling coordination relationship,and to analyze the reasons from the perspective of temporal and spatial evolution.The results show:(1)The level of agricultural green development in the Hexi Region shows a good upward trend,but the overall level is still relatively low.Resource conservation and utilization and green technology support are the shortcom-ings of development.There are still unbalanced and insufficient development issues among cities.(2)The cou-pling coordination degree of agricultural green development in the Hexi Region has been increasing year by year,with the characteristics of high overall level,slow improvement speed,and spatial imbalance,showing a development feature of central leadership,southeastern follow-up,and northwestern catch-up.To improve the coupling coordination degree,it is necessary to achieve this by improving resource conservation and utilization,strengthening the level of agricultural ecological restoration,paying attention to agricultural pollution issues,narrowing the development gap between regions,and adjusting each influencing factor in a targeted manner.
agricultural green developmententropy weight methodcoupling coordination degreeHexi Region
NETL
NSTL
万方数据
