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Assessment of Poor Regions in Hebei Province Using NPP/VIIRS Nighttime Light Composite Data

机译:利用NPP / VIIRS夜间光综合数据评估河北省贫困地区。

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This study aims to assess multidimensional poverty at the county level in Hebei Province in 2015 through a new method using NPP/VIIRS nighttime light composite data, and to put forward constructive suggestions for the government's policy on poverty alleviation. The eradication of poverty is a major mission of the Chinese government. Accurate measurements and identifications of poor regions critically influence both research and policy. Here we demonstrate an accurate and inexpensive method to assess multidimensional poverty from satellite imagery while reliable data on economic livelihoods remain scarce. This study referenced the Sustainable Livelihoods Approach and constructed the corresponding multidimensional poverty index system. Taking Hebei Province as a sample, it established the logarithmic model between the multidimensional poverty index (MPI) and the average nighttime light index (ANLI). The method of this paper can provide an important reference for the Chinese government to identify and evaluate the accurate poverty alleviation in the future. It is feasible to use nighttime light data to assess the multidimensional poverty of China. In the future, we can use nighttime light data to monitor and predict the multidimensional poverty in a long and dynamic way.
机译:本研究旨在通过NPP / VIIRS夜间光综合数据的一种新方法,对2015年河北省县域的多维贫困状况进行评估,并对政府的扶贫政策提出建设性建议。消除贫困是中国政府的一项重大任务。贫困地区的准确测量和识别会严重影响研究和政策。在这里,我们展示了一种准确而廉价的方法,可从卫星图像评估多维贫困,而有关经济生计的可靠数据仍然匮乏。这项研究参考了可持续生计方法,并构建了相应的多维贫困指数系统。以河北省为样本,建立了多维贫困指数(MPI)和夜间平均光照指数(ANLI)之间的对数模型。本文的方法可以为中国政府未来识别和评估准确的扶贫提供重要参考。利用夜间光数据评估中国的多维贫困是可行的。将来,我们可以使用夜间灯光数据来长期动态地监视和预测多维贫困。

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