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image
sequence
label
int64
lat
float64
lon
float64
wealthpooled
float64
country
int64
year
int64
urban
bool
nl_mean
float64
nl_center
float64
households
int64
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[[[-0.6055570840835571,-0.5837477445602417,-0.4659774899482727,-0.36129286885261536,-0.4616157114505(...TRUNCATED)
0
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[[[-0.4419873356819153,-0.4572537839412689,-0.5532147288322449,-0.5444909930229187,-0.45725378394126(...TRUNCATED)
0
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2,011
true
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[[[-0.2151706963777542,-0.4158162474632263,-0.23916083574295044,0.06616932153701782,0.19266344606876(...TRUNCATED)
1
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2,011
true
0.032012
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[[[-0.26097017526626587,-0.4179970324039459,-0.32203611731529236,-0.5008724927902222,-0.596833407878(...TRUNCATED)
0
4.948354
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2,011
true
0.021436
0.178322
21
[[[-0.27841758728027344,-0.1344762146472931,-0.4332636296749115,-0.2915032207965851,-0.4136352539062(...TRUNCATED)
0
4.914035
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2,011
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[[[0.38458529114723206,0.15340669453144073,0.2799004912376404,0.15776830911636353,0.2341008484363556(...TRUNCATED)
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[[[-0.33948367834091187,-0.3438454568386078,-0.3634738326072693,-0.24134181439876556,-0.265331953763(...TRUNCATED)
0
4.847395
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2,011
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[[[0.4107562303543091,0.22755827009677887,0.3191572427749634,0.044359974563121796,0.5023552179336548(...TRUNCATED)
0
4.709088
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[[[-0.33730271458625793,-0.4245399236679077,-0.10394316911697388,-0.19118037819862366,-0.33730271458(...TRUNCATED)
0
4.710434
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3
2,011
true
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0.046684
19
End of preview.

PovertyMap-Wilds: Poverty mapping across different countries

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.

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}
}
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