以国务院扶贫开发领导小组2012年最新确定的国家扶贫重点县名单中涉及西南地区(重庆、四川、云南、贵州、广西)的267个贫困县为研究对象,利用ArcGIS空间分析软件和SPSS统计分析软件,将西南地区贫困县空间数据与属性数据进行叠加分析,揭示西南地区贫困乡村的空间分异特征.通过高程、坡度、人均GDP、少数民族占比、距省府距离等因素的分级和聚类分析,划分西南地区贫困乡村地域类型,针对各类贫困乡村的关键致贫因子,提出减贫脱贫措施.结果表明:1)西南地区贫困乡村的分异表现为:地势较低,坡度相对较缓的地区,贫困的发生率及贫困乡村的密度相对较低;而地势较高、坡度变化较大的地区,贫困县的分布较为集中;少数民族比重较高、距省府较远的区域,贫困的发生率及贫困乡村分布越广泛;2)通过综合聚类分析,西南地区贫困乡村共划分成九类;3)针对九类贫困乡村的关键致贫因子提出相应减贫对策:深化三产融合发展,进一步加强区域特色产业发展,并延长产业链;促进生态、经济、社会文化互动共进与协调发展;加强基础设施与公共服务设施建设,缩短贫困乡村与经济中心时间距离和经济距离,改善其通达状况.%Based on the spatial data of 267 state-level poverty-stricken counties in Southwest China and applying the ArcGIS and SPSS software, this paper analyzed the spatial distribution of these counties. In addition, based on the analysis of the differences among elevation, slope, per capita GDP, the proportion of ethnic minorities, and the distance between the provincial capital and poor counties, this paper also tried to classify rural poverty counties into different types in Southwest China and to provide some poverty alleviation measures. Results show that: 1) in Southwest China, it shows that those counties with lower altitude and flatter terrain have lower poverty rates and lighter poverty densities, vice versa; besides, the higher proportion of ethnic minorities and the farther away from the province capital, the larger number of the poor counties and higher poverty rates; 2) by cluster analysis these countries can be divided into 9 types in total. 3) Based on the above analysis results, this paper provides the following poverty alleviation measures: to further strengthen the integration of the developments of three industries, to enhance the development of regional characteristics, to focus on the extension of the industry chain, to accelerate the interacted and coordinated development of ecological, economic, socio-cultural pillars, to improve infrastructure and rural public service facilities, and to shorten the time distance, economic distance between the rural poor counties and the economic hub to improve its accessibility.
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