摘要
针对农业生态环境质量评价,以推进农业经济和实现可持续发展。使用2005-2017年安徽农业生态环境质量相关数据,采用熵值法和时间序列分析法,从农业环境、生态资源、保护力度、农业发展度4个方面开展安徽省农业生态环境质量评级和预测研究。结果表明:2005-2017年,安徽省农业生态环境质量总体水平不断提高,质量等级从劣-差-中-良的方向不断增级,农业生态环境质量的各指标分数呈波动状态,但整体具有上升趋势。2018-2022年,预测综合分数将继续提高,数值接近1。基于该研究结果,建议提出专项农业生态环境保护法规,积极开展植树造林、退耕还林等工作,同时应加强农业环境保护宣传教育,重视科技发展。
In order to promote agricultural economy and realize sustainable development,evaluate agricultural ecological environment quality.Using the data related to agricultural ecological environment quality of Anhui Province from 2005 to 2017,entropy method and time series analysis method were used to carry out the research on agricultural ecological environment quality rating and prediction of Anhui Province from four aspects:agricultural environment,ecological resources,protection intensity and agricultural development degree.The results showed that from 2005 to 2017,the overall level of agricultural ecological environment quality in Anhui Province has been continuously improved,and the quality level has been continuously increased from the direction of bad-bad-medium-good.The index scores of Anhui agricultural ecological environment quality fluctuated,but the overall trend was rising.In 2018-2022,the forecast composite score will continue to improve,with the value approaching 1.Based on the results of this paper,it is suggested that special laws and regulations on agro-ecological environmental protection should be put forward,afforestation and conversion of farmland to forests should be actively carried out,and publicity and education of agricultural environmental protection should be strengthened and scientific and technological development should be emphasized.
作者
潘紫媗
朱家明
张腾
PAN Zixuan;ZHU Jiaming;ZHANG Teng(Anhui University of Finance and Economics,Bengbu Anhui 233030,China)
出处
《延边大学农学学报》
2020年第2期88-95,共8页
Agricultural Science Journal of Yanbian University
基金
国家自然科学基金(71934001)
教育部人文社会科学研究项目(19YJCZH069)
安徽省教研项目(2018jyxm1305)。
关键词
农业生态环境
质量等级
熵值法
时间序列预测
评价指标体系
agricultural ecological environment
quality level
entropy method
time series prediction
evaluation index system