Figure 1

Data processing and spatial disaggregation of unelectrified populations: close-up on the Mandalay Region, Myanmar. (a) Identification of electricity network and nightlights data¹⁷. (b) Delimitation of zones according to proximity to the electricity grid and presence of nightlights. Dark green-coloured areas correspond to communities that are close to the existing electricity grid (5 km buffer), show nightlights, and have access to electricity. These communities correspond to electrified areas. Orange indicates communities that are within a maximum of 5 km of the existing electricity grid, but lack nightlights. These areas correspond to the last-mile energy-access population—that is, communities with no connection to the grid today, but in which grid connection is feasible. Red-coloured areas correspond to communities that show nightlights, but are far from the existing grid. Light green-coloured areas lack access to electricity (no nightlights and far from the grid). (c) Distribution of the total population (inhabitants per 1 km² grid) based on the Global Human Settlement Layer (GHSL)¹⁶. (d) Distribution of the unelectrified population (inhabitants per 1 km² grid) as estimated through the study’s calculations. Starting with the World Bank electrification rates²⁰, the study uses the total population in each pixel and the zone—coefficients for each country group are included in Table 1—as proxies to spatially disaggregate the unelectrified population. The maps were generated using the following data, collected and processed by the authors: GHS POPULATION GRID—GHS-POP¹⁶ data, produced and made publicly available by the European Commission—JRC (https://ghsl.jrc.ec.europa.eu/data.php); Nighttime lights Version 4 DMSP-OLS¹⁷, produced and made publicly available by NOAA's National Geophysical Data Center (https://ngdc.noaa.gov/eog/dmsp/downloadV4composites.html); the Electrification access rates²⁰ (EG.ELC.ACCS.ZS) made publicly available by the World Bank through The Open Data Portal (https://data.worldbank.org); and Electricity Grid Vector data publicly available by several sources^18,19 ( OpenStreetMap, https://www.openstreetmap.org/ , NREL—Geospatial Toolkit https://www.nrel.gov/international/geospatial_toolkits.html and EnergyData https://energydata.info). The spatial classification was made and mapped using ArcGIS 10.6 (https://desktop.arcgis.com/). GIMP 2.10 (https://www.gimp.org) was used for image editing. Sources: World Bank²⁰; Global Human Settlement Layer¹⁶; Authors' compilation based on the analysis.