贫困村空间分布及影响因素分析——以乌蒙山连片特困区为例

Analyzing spatial distribution of poor villages and their poverty contributing factors:A case study from Wumeng Mountain Area

针对目前贫困分布研究以大尺度为主而缺乏对小尺度的关注和致贫因素分析忽略个体效应或背景效应的不足,基于空间贫困视角,以乌蒙山片区为研究区域、贫困村为研究对象,运用空间点模式分析方法探究贫困村空间分布特征,并设计多层线性回归模型从贫困村和县域两个层面综合定量剖析贫困影响因素。研究发现:(1)贫困村的空间聚集特征较为明显,总体分布呈现大分散小集中、散点-极核-轴带-团块并存的空间格局。(2)贫困村的贫困程度受多层因素的显著影响。其中,村级影响因素为:人口密度、通路率、劳动力比例、遭受自然灾害频次、安全饮用水比例;县级影响因素为:人均地方生产总值、高中阶段毛入学率、植被覆盖率。(3)农村贫困来源于贫困村与县域的双重作用。因此在精准扶贫工作中,政府及相关部门可针对不同尺度对象有针对性地施策,合理配置扶贫资金。

Current research mainly focuses on large scale and ignores individual effect or background effect in the exploration of poverty contributing factors.Based on the perspective of spatial poverty,this paper,taking the Wumeng Mountain Area as an example and poor villages as the research object,uses spatial point pattern method to explore the spatial distribution characteristics of the poor villages and designs multi-level linear regression models to comprehensively and quantitatively analyze the poverty contributing factors at both village and county levels.The results were concluded as follows.(1)The spatial clustering characteristics of the poor villages in the study area were obvious.The overall distribution showed a spatial pattern of both large scatters and small concentrations,and scatter points-polar core-axis-cluster coexisted.(2)The poverty degree of poor villages was significantly affected by multilevel factors.The village-level factors were:population density,road access ratio,labor force ratio,frequency of suffered natural disasters,and safe drinking water ratio.The county-level factors were:per capita GDP,second gross enrollment ratio,and vegetation coverage.(3)The rural poverty in the study area came from the dual role of poor villages and counties.Hence,the government and relevant departments can take targeted measures according to different scales in the poverty alleviation,and allocate funds reasonably for poverty relief.