【摘要】 区域贫困是一个动态变化过程,客观准确地度量区域贫困程度对于国家扶贫工作十分重要。文中利用研究区DMSP/OLS稳定夜光遥感数据和县域尺度上的经济、健康、教育三个维度社会经济数据,选取与夜间灯光指数相关性较大的社会经济指标,构建了用来衡量贫困的多维贫困指数(MPI);利用回归分析方法建立了夜间灯光指数与MPI间模型关系,并从时空维度和可靠性等方面验证了模型的适用性。该研究为区域贫困程度的自动化预测提供了一种新的方法手段。更多还原

【Abstract】 Regional poverty was a dynamic process,and it was very important for national poverty alleviation to measure the degree of regional poverty objectively and accurately. Multidimensional poverty index( MPI) was constructed to measure poverty using DMSP/OLS stable nighttime light remote sensing data in the study area and the socio-economic data in three dimensions of economy,health and education on county scale and selecting the socio-economic indicators with strong correlation with nighttime light Index. The relationship between nighttime light index and MPI model was established by using the regression analysis method,the applicability of the model was validated from the aspects of space-time dimension and reliability. The study could provide a new technical tool for automating the monitoring of regional poverty.更多还原