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摘要翻译：
我们开发了一个基于机器学习的工具，用于从白天的卫星图像中准确预测社会经济指标。不同的一套指标往往与卫星图像中可观察到的特征没有直观的联系，甚至彼此之间也不总是很好地相关联。我们的预测工具比以夜光作为代用工具更准确，可用来预测缺失数据、消除勘测中的噪音、监测区域的发展进展和标记潜在的异常。最后，我们利用预测变量对印度高发育迟缓率的回归研究进行稳健性分析。
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英文标题：
《On monitoring development indicators using high resolution satellite
images》
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作者：
Potnuru Kishen Suraj, Ankesh Gupta, Makkunda Sharma, Sourabh Bikas
Paul, Subhashis Banerjee
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最新提交年份：
2018
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分类信息：
一级分类：Economics 经济学
二级分类：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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一级分类：Computer Science 计算机科学
二级分类：Computers and Society 计算机与社会
分类描述：Covers impact of computers on society, computer ethics, information technology and public policy, legal aspects of computing, computers and education. Roughly includes material in ACM Subject Classes K.0, K.2, K.3, K.4, K.5, and K.7.
涵盖计算机对社会的影响、计算机伦理、信息技术和公共政策、计算机的法律方面、计算机和教育。大致包括ACM学科类K.0、K.2、K.3、K.4、K.5和K.7中的材料。
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英文摘要：
We develop a machine learning based tool for accurate prediction of socio-economic indicators from daytime satellite imagery. The diverse set of indicators are often not intuitively related to observable features in satellite images, and are not even always well correlated with each other. Our predictive tool is more accurate than using night light as a proxy, and can be used to predict missing data, smooth out noise in surveys, monitor development progress of a region, and flag potential anomalies. Finally, we use predicted variables to do robustness analysis of a regression study of high rate of stunting in India.
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PDF链接：
https://arxiv.org/pdf/1712.02282
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