Combining satellite imagery and machine learning to predict poverty

@article{Jean2016CombiningSI,
  title={Combining satellite imagery and machine learning to predict poverty},
  author={Neal Jean and Marshall Burke and Michael Xie and W. Matthew Davis and David B. Lobell and Stefano Ermon},
  journal={Science},
  year={2016},
  volume={353},
  pages={790-794}
}
Reliable data on economic livelihoods remain scarce in the developing world, hampering efforts to study these outcomes and to design policies that improve them. Here we demonstrate an accurate, inexpensive, and scalable method for estimating consumption expenditure and asset wealth from high-resolution satellite imagery. Using survey and satellite data from five African countries—Nigeria, Tanzania, Uganda, Malawi, and Rwanda—we show how a convolutional neural network can be trained to identify… CONTINUE READING
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