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supplemental archive 2 disk0/00/01/59/82 2019-07-04 07:21:00 2024-09-09 12:49:45 2019-07-04 07:21:00 article show Falchetta G. 9187 0000-0003-2607-2195 Pachauri S. 1816 0000-0001-8138-3178 Parkinson S. 2028 0000-0002-4753-5198 Byers E. 2115 0000-0003-0349-5742 pub prog_ene Spatially explicit data on electricity access and use are essential for effective policy-making and infrastructure planning in low-income, data-scarce regions. We present and validate a 1-km resolution electricity access dataset covering sub-Saharan Africa built on gridded nighttime light, population, and land cover data. Using light radiance probability distributions, we define electricity consumption tiers for urban and rural areas and estimate the by-tier split of consumers living in electrified areas. The approach provides new insight into the spatial distribution and temporal evolution of electricity access, and a measure of its quality beyond binary access. We find our estimates to be broadly consistent with recently published province- and national-level statistics. Moreover, we demonstrate consistency between the estimated electricity access quality indicators and survey-based consumption levels defined in accordance with the World Bank Multi-Tier Framework. The dataset is readily reproduced and updated using an open-access scientific computing framework. The data and approach can be applied for improving the assessment of least-cost electrification options, and examining links between electricity access and other sustainable development objectives. 2019-07-03 Nature Publishing Group 10.1038/s41597-019-0122-6 3119 222 225 2585 public Scientific Data 6 1 art. 110 TRUE 2052-4463 FALSE info:eu-repo/semantics/article