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Datasets:
1aurent
/
PovertyMap

Tasks:
Image Classification
Size Categories: 10K<n<100K
Tags: map poverty satellite
License:
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PovertyMap-wilds: Poverty mapping across different countries

Homepage: https://github.com/sustainlab-group/africa_poverty
Publication Date: 2020-05-22
License: LandSat/DMSP/VIIRS data is U.S. Public Domain.
Citation:

@article{yeh2020using,
  author = {Yeh, Christopher and Perez, Anthony and Driscoll, Anne and Azzari, George and Tang, Zhongyi and Lobell, David and Ermon, Stefano and Burke, Marshall},
  day = {22},
  doi = {10.1038/s41467-020-16185-w},
  issn = {2041-1723},
  journal = {Nature Communications},
  month = {5},
  number = {1},
  title = {{Using publicly available satellite imagery and deep learning to understand economic well-being in Africa}},
  url = {https://www.nature.com/articles/s41467-020-16185-w},
  volume = {11},
  year = {2020}
}

Description

This is a processed version of LandSat 5/7/8 satellite imagery originally from Google Earth Engine under the names LANDSAT/LC08/C01/T1_SR,LANDSAT/LE07/C01/T1_SR,LANDSAT/LT05/C01/T1_SR, nighttime light imagery from the DMSP and VIIRS satellites (Google Earth Engine names NOAA/DMSP-OLS/CALIBRATED_LIGHTS_V4 and NOAA/VIIRS/DNB/MONTHLY_V1/VCMSLCFG) and processed DHS survey metadata obtained from https://github.com/sustainlab-group/africa_poverty and originally from https://dhsprogram.com/data/available-datasets.cfm.

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