长江流域资源与环境 >> 2020, Vol. 29 >> Issue (1): 113-124.doi: 10.11870/cjlyzyyhj202001011

• 自然资源 • 上一篇    下一篇

贵州省农村贫困化的时空分异与影响因素分析:2003~2015

夏四友1,赵  媛1,2,4*,文  琦3,崔盼盼1,许  昕1,孔德明1   

  1. (1.南京师范大学地理科学学院,江苏 南京 210023;2.南京师范大学金陵女子学院,江苏 南京 210097;3.宁夏大学资源环境学院,宁夏 银川 750021;4.江苏省地理信息资源开发与利用协同创新中心,江苏 南京 210023)
  • 出版日期:2020-01-20 发布日期:2020-03-24

Study on Spatiotemporal Variation and Influencing Factors of Rural Poverty in Guizhou Province from 2003 to 2015

XIA Si-you1, ZHAO Yuan1,2, WEN Qi3, CUI Pan-pan1, XU Xin1, KONG De-ming3   

  1. (1.School of Geography Science, Nanjing Normal University, Nanjing 210023, China; 2.Jinling College, Nanjing Normal University, Nanjing 210097, China; 3.School of Resources and Environment, Ningxia University, Yinchuan 750021, China)
  • Online:2020-01-20 Published:2020-03-24

摘要: 研究农村贫困化的时空分异与影响因素对因地制宜制定脱贫战略具有重要意义。以贵州省县域为研究单元,选取贫困发生率为研究指标,采用变异系数、空间统计模型、空间变差函数、双变量LISA模型等定量方法对2003~2015农村贫困化的时空分异格局演变及影响因素进行了探讨,得出以下结论:(1) 贵州省农村贫困程度整体在加深,区域差异日益加剧,在空间上呈东部、南部、西部高,而中部和北部低的“U”形空间分布格局。(2) 县域贫困化重心在107.047 2°E~107.174 4°E,26.668 5°N~26.713 2°N之间变动,总体上向东南方向移动,贫困化大体呈现“东北-西南”的空间分布格局。(3) 农村贫困化空间格局演变同时受到随机性和结构性因素影响,其空间分异主要体现为南—北向,而西北—东南方向则较为均衡。(4)农村贫困化与影响因素的相关性存在较大差异,农民人均可支配收入、人均粮食产量与农村贫困化的负相关关系最为明显,各因素与农村贫困化的双变量LISA聚类图的空间差异明显。最后,从统筹区域协调发展、制定差异化扶贫措施和走产业扶贫的道路等方面提出了破解贵州省农村贫困的对策建议。

Abstract: Exploring spatial-temporal variation and influencing factors of rural poverty has important theoretical and practical significance for formulating a reasonable policy to reduce poverty. Taking the incidence of poverty during 2003-2015 in Guizhou Province, this paper makes a quantitative comprehensive analysis of spatiotemporal variation and influencing factors by using the variable coefficient, spatial statistical model, spatial variogram and Bivariate LISA model. Results showed that: 1) The rural poverty in Guizhou Province is deepening as a whole, and the regional differences are increasing. It is spatially high in the east, south, and west, and low in the middle and north. 2) Rural poverty gravity center was between 107.047 2°-107.174 4°E, 26.668 5°-26.713 2°N and was moving to the southeast. The spatial distribution of rural poverty presented a northeast-southwest pattern. 3) The spatial pattern of rural poverty is affected by both random and structural factors. The spatial differentiation is mainly reflected in the south-north direction, while the northwest-southeast direction is more balanced. 4) There is a significant difference in the rural poverty and influencing factors, and the negative correlation between peasant per capita disposable income, per capita grain production and rural poverty is the most obvious. The spatial difference of the Bivariate LISA clustering map between rural poverty and influencing factors are obvious. Finally, from the aspects of coordinating regional coordinated development, formulating differentiated poverty alleviation measures and taking the road of industrial poverty alleviation, this paper also provides a framework for solving rural poverty in Guizhou Province.

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