中文摘要：

贫困人口及其分布区域的有效瞄准和识别是新阶段连片特困区农村扶贫开发需要解决的首要问题。从多维角度把握贫困的实质并进行多维贫困的具体度量和分析成为近年来国内外研究的焦点。在系统设计多维贫困识别指标体系及多维贫困测算算法流程的基础上，以河南省南阳市连片特困区扶贫重点县为研究区域，构建基于“双临界值”的“维度加总／分解”算法进行了“县级一村级”的贫困人口多维贫困量算和分析；借助Kriging法对村级多维贫困测算结果进行空间插值处理，系统分析研究区多维贫困状况空间分布格局。结果显示：研究区多维贫困发生率和多维贫困指数都呈现“西高东低”趋势，其中，内乡县和淅川县的综合贫困指数MPI最大，镇平县MPI最小。其主要致贫因素为收入和健康，收入指标对贫困的贡献度在空间上呈现“西北一东南”条带状分布，健康问题集中在镇平县；次要致贫因素为教育年限、儿童入学率以及燃料类型。此外，淅川县山区地区多维贫困发生率最高，县城附近的MPI相对较低。

英文摘要：

In special poverty-stricken rural areas, the primary problem of poverty alleviation is effective target- ing and identifying of the poor and their distribution area. In recent years, researchers around the world fo- cused on grasping the essence of multidimensional poverty and measurement. Based on systematic design of multidimensional poverty identifying indices system and algorithm flow, this article takes key country in Nan- yang, Henan Province from national contiguous special poverty-stricken areas as the study area, constructs al- gorithm based on the ＂dual cutoff＂ and ＂dimension aggregated/decomposition＂ to measure and analyze the multidimensional poverty of the poor at ＂county-village＂scale,uses Kriging method to interpolate results of multidimensional poverty measurements and systematically analyze spatial distribution pattern of multidimen- sional poverty at village scale in study area.The result shows： in the study area,the trend of multidimensional poverty headcount ratio and multidimensional poverty index（MPI） is that the value of west is higher than that of the east;the MPI of Neixiang country and Xichuan country is the highest,that of Zhenping country is the low- est.Their primary factors contributing to poverty are income and health,contribution of income index to the poverty appears as strip from ＂northwest-southeast＂,healthy problem mainly concentrates around Zhenping country. Their secondary factors contributing to poverty are education,schooling and fuel.Besides,the multidi- mensional poverty incidence is the highest in mountainous area in Xichuan country, MPI is relatively lower around the center of the country.