1. Can Poverty Levels Be Estimated Using Satellite Data? Chris Elvidge NOAA – National Geophysical Data Center 325 Broadway, E/GC2 Boulder, Colorado 80305, U.S.A Email: chris.elvidge@noaa.gov K.E. Baugh, B.T. Tuttle, A.T. Howard and P.J. Hayes University of Colorado – CIRES 325 Broadway E/GC2 Boulder, Colorado 80305, U.S.A E.H. Erwin NOAA – National Geophysical Data Center 325 Broadway, E/GC2 Boulder, Colorado 80305, U.S.A July 17, 2006

2. Global Poverty The World Bank estimates that 40% of all people live in poverty (2.6 billion). The World Bank estimates that 40% of all people live in poverty (2.6 billion). The primary source for poverty estimates are household surveys and government statistics (from tax reports, etc.). The primary source for poverty estimates are household surveys and government statistics (from tax reports, etc.). Poverty levels are reported for entire countries or states. Poverty levels are reported for entire countries or states.

3. Problems in Estimating Poverty Levels It is difficult to define a uniform definition or method for measuring poverty. It is difficult to define a uniform definition or method for measuring poverty. National definitions of poverty tend to be subjective. For instance many people counted as in poverty in the USA own automobiles – a sign of wealth in many other countries. National definitions of poverty tend to be subjective. For instance many people counted as in poverty in the USA own automobiles – a sign of wealth in many other countries. Difficult to reconcile income versus consumption based data from surveys. Difficult to reconcile income versus consumption based data from surveys. Not all countries measure or report poverty levels and the methods and timetables used vary substantially. Not all countries measure or report poverty levels and the methods and timetables used vary substantially. It is possible for governments to bias poverty estimates. It is possible for governments to bias poverty estimates.

4. World Bank’s World Development Indicator’s Poverty Map - 2005

5. Temporal Distribution of the National Poverty Data for 2005

6. Estimation of Poverty Using Satellite Data Global coverage – making estimates where no other data are available. Global coverage – making estimates where no other data are available. Standardized measurement. Standardized measurement. Uniform timing. Uniform timing. Disaggregated grid of poverty levels has more applications than national level estimates for understanding poverty and planning solutions. Disaggregated grid of poverty levels has more applications than national level estimates for understanding poverty and planning solutions.

7. DOE LandScan 2004 Population Density Sources: Census data, MODIS land cover, SRTM topography and high resolution satellite imagery.

8. DMSP Nighttime Lights - 2003

9. LandScan / Lights

10. Calibration

11. Population Count in Poverty Green 1-10, Yellow 11-50, Red > 50

12. National Poverty Estimates

13. Sub-national Poverty Estimates

14. Poverty Estimates in South and East Asia (in percent) East Timor85.11 East Timor85.11 Bhutan77.784.31 Bhutan77.784.31 PNG81.45 PNG81.45 Laos73.279.50 Laos73.279.50 Myanmar78.476.26 Myanmar78.476.26 Nepal80.973.03 Nepal80.973.03 DPRK64.94 DPRK64.94 Mongolia74.956.52 Mongolia74.956.52 Bangladesh82.852.94 Bangladesh82.852.94 China46.744.60 China46.744.60 India80.641.94 India80.641.94 Philippines47.541.13 Philippines47.541.13 Thailand32.540.39 Thailand32.540.39 Vietnam33.428.28 Vietnam33.428.28 Indonesia52.433.38 Indonesia52.433.38 Sri Lanka50.730.24 Sri Lanka50.730.24 Malaysia 9.318.23 Malaysia 9.318.23 Japan 7.03 Japan 7.03 ROK 2.0 6.54 ROK 2.0 6.54 ROC 6.33 ROC 6.33 Singapore 5.47 Singapore 5.47 $2/day Satellite

15. Issues Found High poverty rates assumed for population with no detected lights – which may overestimate poverty in wealthier countries. High poverty rates assumed for population with no detected lights – which may overestimate poverty in wealthier countries. The nighttime lights product used has saturation in urban centers – introducing inaccuracies in poverty estimates in urban cores. The nighttime lights product used has saturation in urban centers – introducing inaccuracies in poverty estimates in urban cores. There are cultural and technological differences in lighting that have not been accounted for. There are cultural and technological differences in lighting that have not been accounted for.

16. Conclusions The first consistent global map of poverty levels has been produced. The first consistent global map of poverty levels has been produced. Poverty levels have been estimated in a large number of countries where data were not available previously. Poverty levels have been estimated in a large number of countries where data were not available previously. Discrepancies between reported poverty levels and the satellite estimates probably arise both from inaccuracies in the reported data and the satellite data / methodology / assumptions. Discrepancies between reported poverty levels and the satellite estimates probably arise both from inaccuracies in the reported data and the satellite data / methodology / assumptions. A new class of poverty map has been produced and can be expectd to impove in accuracy over time. A new class of poverty map has been produced and can be expectd to impove in accuracy over time.