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引用本文:徐英.贵州省县域贫困测度及空间格局分析[J].中国农业资源与区划,2019,40(8):95~102
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贵州省县域贫困测度及空间格局分析
徐英
兴义民族师范学院经济与管理学院,贵州兴义562400
摘要:
[目的]区域贫困识别一直是贫困研究中重点关注的课题。文章通过对贵州省县域贫困度进行等级划分以及空间格局特征分析,可为地方政府实施区域扶贫开发的优先顺序提供一定的决策依据。[方法]从自然、社会、经济维度,构建县域贫困测度指标体系,利用SPSS进行因子分析,计算各个县域综合得分,用以测度各县域贫困程度; 运用ArcGIS的制图功能,呈现县域贫困度的空间分布格局,借以分析县域贫困度的地域分异规律; 运用ArcGIS自然间断点分级法划分县域贫困度等级。[结果](1)贵州省66个贫困县中,综合得分最高的威宁县贫困度最大,综合得分最低的铜仁市碧江区贫困度最轻; (2)县域贫困度可划分为极重度贫困、重度贫困、中度贫困、轻度贫困及轻微贫困5个等级; (3)县域贫困度与区域地貌类型具有一定的空间关联,极重度贫困县及重度贫困县大多分布在省际边界地区。[结论]贵州省县域贫困程度差异较大; 自然地理环境条件如地貌是贵州县域致贫的重要原因。
关键词:  贫困贫困县贫困度贵州省空间格局
DOI:
分类号:K901
基金项目:贵州省哲学社会科学规划项目“精准扶贫视角下贵州民族贫困地区农民主体性与可持续生计研究”(16GZYB12)
ANALYSIS OF COUNTY POVERTY MEASUREMENT AND SPATIAL PATTERN IN GUIZHOU PROVINCE
Xu Ying
College of Economics and Management, Xingyi National Normal University, Xingyi, Guizhou 562400, China
Abstract:
Regional poverty identification has always been a focus of attention in poverty research. This paper attempts at conducting grading over county poverty and analyzing spatial pattern characteristics of Guizhou province, with a view of providing a decision making basis for local governments to set their priorities of implementing regional poverty alleviation and development. A county poverty measurement index system was constructed from the dimensions of nature, society and economy. Moreover, factor analysis was conducted by using SPSS to calculate the comprehensive scores of each county, so as to measure their poverty degrees. And the spatial distribution pattern of county poverty degrees was displayed by drawing on the mapping function of ArcGIS, so as to summarize the rules of regional differentiation in county poverty degree. In addition, county poverty degrees were graded by using ArcGIS natural break point method. Among the 66 poverty stricken counties in Guizhou province, Weining County was the most poverty stricken one with the highest scores, while Bijiang district in Tongren city is the least poverty stricken one with the lowest scores. County poverty degrees can be divided into five grades, including extremely severe poverty, severe poverty, moderate poverty, mild poverty and slight poverty. County poverty has a certain spatial correlation with regional geomorphic types, with most of the extremely severe poverty stricken counties and the severe poverty stricken ones distributing in the interprovincial border areas. Different counties of Guizhou province are characterized by greatly varying poverty degrees. It is noteworthy that natural geographical conditions such as landform are the major cause leading to county poverty of Guizhou province.
Key words:  poverty  poverty stricken counties  poverty degree  Guizhou province  spatial pattern
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