1. 南阳市水利建筑勘测设计院,河南,南阳,473068
2. 杭州大地科技有限公司,浙江,杭州,310004
3. 华北水利水电大学 水利学院,河南,郑州,450046
4. 华北水利水电大学, 测绘与地理信息学院,河南,郑州,450046
纸质出版:2020
移动端阅览
贾大周, 赵喜鹏, 刘少博, 等. 基于灰色关联度模型的生态敏感区贫困化成因分析——以南水北调中线河南省水源区贾营小流域为例[J]. 水土保持通报, 2020,40(1):191-197.
Jia Dazhou, Zhao Xipeng, Liu Shaobo, et al. Analysis of Causes of Impoverishment in Ecologically Sensitive Areas Based on Grey Relational Degree Model—A Case Study at Jiaying Small Watershed in He'nan Province Water Source Area of Middle Route Rroject of South to North Water Diversion[J]. Bulletin of Soiland Water Conservation, 2020, 40(1): 191-197.
贾大周, 赵喜鹏, 刘少博, 等. 基于灰色关联度模型的生态敏感区贫困化成因分析——以南水北调中线河南省水源区贾营小流域为例[J]. 水土保持通报, 2020,40(1):191-197. DOI: 10.13961/j.cnki.stbctb.2020.01.028.
Jia Dazhou, Zhao Xipeng, Liu Shaobo, et al. Analysis of Causes of Impoverishment in Ecologically Sensitive Areas Based on Grey Relational Degree Model—A Case Study at Jiaying Small Watershed in He'nan Province Water Source Area of Middle Route Rroject of South to North Water Diversion[J]. Bulletin of Soiland Water Conservation, 2020, 40(1): 191-197. DOI: 10.13961/j.cnki.stbctb.2020.01.028.
[目的] 探究生态敏感区农村贫困化的主要影响因素,为扶贫工作提供理论基础。[方法] 以南水北调中线水源区贾营生态清洁小流域为研究对象,运用基于熵权的灰色关联度模型,计算了小流域贫困化率与影响因素的关联度,分析了小流域内影响贫困化率的主要因素。[结果] ①小流域2017年贫困化率为5.69%,是同时期河南省平均水平的2.21倍;②小流域内中游地区平均贫困化率为7.13%,明显高于上游地区(6.26%)和下游地区(5.65%);③影响小流域贫困化的主要因素为人均耕地资源占有量、劳动力占总人口比重及家庭年均饮食消费支出、初中以上学历比例、家庭年均工资性收入、地面坡度及家庭年均医疗支出等指标;④影响小流域内各个村的贫困化主要因素各有不同,呈现区域差异化。[结论] 在小流域内因地制宜地采取扶贫措施,充分利用流域内剩余劳动力和剩余劳动时间,加大教育投入力度以及处理好因残及因病致贫问题是解决小流域贫困问题的关键。
[Objective] The primary factors which are responsible for poverty in ecologically sensitive areas were studied in order to provide a theoretical basis for implementing anti-poverty measures.[Methods] This study selected an eco-clean watershed as the research target
which was located at Jiaying in the He'nan Province. In particular it was situated in the area of the water source of the Middle Route Project of South to North Water Diversion. The gray correlation model based on the entropy weight was employed to calculate the correlation degree between the poverty rate and the influencing factors in the small watershed; further
the primary factors affecting the poverty rate in the small watershed were analyzed.[Results] ①The poverty rate in Jiaying eco-clean watershed was 5.69% in 2017
which was regarded as 2.21 times higher than that of the average in the He'nan Province at the same period. ②The average poverty rate in the middle reaches of small basins was 7.13%
which was significantly higher than that in the upper (6.26%) and the lower reaches (5.65%). ③Various factors were observed to affect the poverty in small watersheds
namely:the amount of cultivated land per capita
proportion of the labor force in the total population
annual household dietary expenditures
proportion of junior middle schools
household annual average wage incomes
ground slope
and annual average medical expenditures of households. ④However
the primary factors affecting the poverty of each village in the small watershed were different
exhibiting regional differentiation.[Conclusion] The key to solve the problem of poverty in small watersheds is to take measures to alleviate the poverty according to the local specific conditions
and by rendering the complete use of the surplus labor force and the surplus working time. Further
an increase in the investment with regard to education is necessitated with appropriate solutions for tackling poverty caused by disability and disease.
中华人民共和国商务部.中共中央国务院关于实施乡村振兴战略的意见[EB/OL](2018-05-02)[2018-06-26].http://big5.mofcom.gov.cn/gate/big5/www.mofcom.gov.cn/article/b/g/201805/20180502738786.shtml
汪为,吴海涛,彭继权.农村家庭多维贫困动态性及其影响因素研究:基于湖北数据的分析[J].中南财经政法大学学报,2018(1):51-60.
刘彦随,李进涛.中国县域农村贫困化分异机制的地理探测与优化决策[J].地理学报,2017,72(1):161-173.
杨慧敏,罗庆,李小建,等.生态敏感区农户多维贫困测度及影响因素分析:以河南省淅川县3个村为例[J].经济地理,2016,36(10):137-144.
隋佳.辽宁省贫困地区留守老人的生存质量现状及其影响因素的研究[D].辽宁锦州:锦州医科大学,2017:11-21.
杨慧敏,罗庆,许家伟.中国农村贫困的动态发展及影响因素分析:基于CHNS数据[J].经济经纬,2016,33(5):42-47.
程名望,张帅,史清华.农户贫困及其决定因素:基于精准扶贫视角的实证分析[J].公共管理学报,2018,15(1):135-146,159-160.
杨慧敏,罗庆,李小建.河南省县域贫困程度及影响因素分析[J].人文地理,2017,32(5):48-55.
曾勇,徐长乐.基于灰色关联的贵州连片特困地区贫困影响因素分析[J].世界地理研究,2017,26(1):158-167.
李贝,李海鹏,苏祖勤.家庭生命周期、农户贫困及其影响因素分析:基于湖北恩施州的微观数据[J].干旱区资源与环境,2017,31(3):32-37.
王艳慧,钱乐毅,段福洲.县级多维贫困度量及其空间分布格局研究:以连片特困区扶贫重点县为例[J].地理科学,2013,33(12):1489-1497.
李俊杰,李海鹏.民族地区农户多维贫困测量与扶贫政策创新研究:以湖北省长阳土家族自治县为例[J].中南民族大学学报(人文社会科学版),2013,33(3):127-132.
叶慧,陈敏莉.边境地区贫困农户多维特征及致贫因素分析:基于广西崇左市贫困户调查数据[J].北方民族大学学报(哲学社会科学版),2016(4):102-106.
张永丽,张佩,卢晓.农户多维贫困测度及其影响因素分析[J].西北农林科技大学学报(社会科学版),2017,17(5):138-147.
韩彦东.人口较少民族贫困原因及扶贫开发对策研究[J].贵州民族研究,2005,26(6):55-62.
张蕴萍.中国农村贫困形成机理的内外因素探析[J].山东社会科学,2011(8):33-37.
郭文泽. 中国农村贫困文化研究:以内蒙古C旗S乡为个案[D].天津:天津师范大学, 2016:26-28.
盛伟.空间地理环境约束下的藏区贫困问题研究:基于空间面板数据的贫困溢出效应实证分析[D].成都:西南民族大学,2016:27-36.
国家地理信息中心.http://www.gscloud.cn/sources/?cdataid=302&pdataid=10.html
符蕾.基于熵权法的旅游公路景观评价体系研究[D].重庆:重庆交通大学,2014:19-23.
Shannon C E. A mathematical theory of communication[J].Mobile Computing and Communications Review, 2001,5(1):3-55.
王卓,高丛.基于信息论的熵值法的算法改进:以陕西省环境规制强度评价为例[J].西安石油大学学报(社会科学版),2016,25(1):22-26.
余华银,李超,黄萍.熵值法在EXCEL中的VBA实现[J].统计教育,2004(3):12-14.
Deng J L. Control problems of grey systems[J]. Systems & Control Letters, 1982,1(5):288-294.
刘思峰,杨英杰,吴利丰.灰色系统理论及其应用[M]. 7版.北京:科学出版社, 2017.
0
浏览量
1112
下载量
1
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621