Bangladesh 1km Resolution Poverty Estimates - Mapping poverty using mobile phone and satellite data

DATASET: 2011 estimates of mean DHS wealth index score per grid square, and associated uncertainty metrics. REGION: Asia SPATIAL RESOLUTION: 0.00833333 decimal degrees (approx. 1km at the equator) PROJECTION: Geographic, WGS84 UNITS: DHS wealth index score (poverty dataset); standard deviation (uncertainty dataset) MAPPING APPROACH: Bayesian model-based geostatistics in combination with high resolution gridded spatial covariates and aggregated mobile phone data applied to GPS-located household survey data on poverty from the DHS Program. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: bgd2011wipov.tif = Bangladesh (bgd) asset-based poverty map for 2011 showing estimates of mean DHS wealth index score per grid square. bgd2011wipovsd.tif = uncertainty dataset showing standard deviation per grid square. DATE OF PRODUCTION: January 2017 CITATION: Steele, J. E. et al. Mapping poverty using mobile phone and satellite data. J. R. Soc. Interface 14, 20160690 (2017). Online here: http://rsif.royalsocietypublishing.org/content/14/127/20160690

DHS wealth index score Standard Deviation

DATASET: 2013 estimates of income in USD per grid square, and associated uncertainty metrics. REGION: Asia SPATIAL RESOLUTION: 0.00833333 decimal degrees (approx. 1km at the equator) PROJECTION: Geographic, WGS84 UNITS: USD (poverty dataset); standard deviation (uncertainty dataset) MAPPING APPROACH: Bayesian model-based geostatistics in combination with high resolution gridded spatial covariates and aggregated mobile phone data applied to mobile tower-located household survey data on income from Grameenphone Ltd. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: bgd2013incpov.tif = Bangladesh (bgd) income-based poverty map for 2013 showing estimates of mean household income in USD per grid square. bgd2013incpovsd.tif = uncertainty dataset showing standard deviation per grid square. DATE OF PRODUCTION: January 2017 CITATION: Steele, J. E. et al. Mapping poverty using mobile phone and satellite data. J. R. Soc. Interface 14, 20160690 (2017). Online here: http://rsif.royalsocietypublishing.org/content/14/127/20160690

Estimates of Income in USD Standard Deviation

DATASET: 2013 estimates of mean likelihood of living in poverty per grid square, as defined by $2.50 a day poverty line, and associated uncertainty metrics. REGION: Asia SPATIAL RESOLUTION: 0.00833333 decimal degrees (approx. 1km at the equator) PROJECTION: Geographic, WGS84 UNITS: Mean likelihood of living on less than $2.50 a day (poverty dataset); standard deviation (uncertainty dataset) MAPPING APPROACH: Bayesian model-based geostatistics in combination with high resolution gridded spatial covariates applied to GPS-located household survey data on poverty from the Progress out of Poverty Index. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: bgd2013ppipov.tif = Bangladesh (bgd) Poverty Index-based poverty map for 2013 showing estimates of mean likelihood of living in poverty per grid square. bgd2013ppipovsd.tif = uncertainty dataset showing standard deviation per grid square. DATE OF PRODUCTION: January 2017 CITATION: Steele, J. E. et al. Mapping poverty using mobile phone and satellite data. J. R. Soc. Interface 14, 20160690 (2017). Online here: http://rsif.royalsocietypublishing.org/content/14/127/20160690

Mean Likelihood of Living in Poverty Standard Deviation