Beyond access: 1.18 billion in energy poverty... | Data Futures Exchange (2024)

Without consistent access to reliable and affordable energy, even those in electrified areas miss out on the many benefits of electricity. The consequences of energy poverty can be severe, including serious harms to physical health and mental well-being, social exclusion, stigmatization, and the impairment of social, political, and economic opportunities.

Leveraging recent advances in satellite image analysis, we provide the first computational classifications of electricity poverty across the developing world, combining high-resolution nighttime and daytime satellite imagery to evaluate light output signatures across up to 3,000 nights over all human settlements in the developing world.

These new estimates rely on large-scale analysis of the complete historical record of VIIRS-DNB nighttime satellite imagery (available through the World Bank’s Light Every Night dataset, described here and UNDP’s Data Futures Exchange described here), linked with recent data on the location of all human-built structures on the planet.

These computational methods leverage nightly images to estimate power usage over individual settlements, controlling for local and systemic sources of noise. By relying on nightly estimates, we exploit important variation in temporal signals that are smoothed over in monthly and annual composites. The nightly comparisons allow for direct accounting of variations in surface reflectance due to differences in land cover albedo, lunar illumination cycles, atmospheric conditions, and other unmeasured differences. Statistical aggregation of these nightly parameters over time yields estimates of electricity usage that increase in reliability and robustness over longer periods.

The data reveal some stark patterns. For example, in Sub-Saharan Africa, most of the variation in energy poverty rates is explained by within-country differences in population density, remoteness, and land terrain characteristics, not between-country variation in factors such as country wealth or power-generating capacity. One implication is that many pockets of energy poverty lie right next to areas where electrical networks are already established, suggesting that there are many local opportunities to reduce energy poverty, even without waiting for large-scale infrastructure projects to be realized.

To accelerate efforts to reduce energy poverty across the world, we are releasing settlement-level data on estimated electricity access and usage for 115 countries from 2013-2020. Energy poor settlements lie in areas that are so consistently dim at night that they are statistically indistinguishable from the background light levels in similar unpopulated areas. The data are part of the High Resolution Electricity Access (HREA) project, a partnership to track settlement-level electricity availability between the University of Michigan, World Bank, United Nations Development Programme, and National Oceanic and Atmospheric Administration.

This new gridded data product of energy use has the potential to accelerate research on the causes and correlates of energy poverty, as well as on the impacts of energy poverty on welfare and development at the local and global scales. Digital tools on sustainable energy are also key to accelerate innovation in electricity planning and assessment efforts, and increase the value of local and disaggregated data collection. By linking these high-resolution energy poverty maps with other geospatial data of socioeconomic indicators, more integrated approaches can be pursued to address the just energy transition as a priority for fundamental economic development.

Reaching the SDG7 target of affordable, reliable, sustainable and modern energy for all by 2030 depends more than ever on candid, consistent, and timely insights into where and why communities lack access to energy.