Brian Min and Zachary O'Keeffe
University of Michigan

This project leverages high resolution satellite data to generate estimates of electrification access at a higher spatial resolution than ever before. The estimates are derived from the first long-scale analysis of the complete archive of nighttime light imagery from the VIIRS sensor, from 2012–present, tracked against new population estimates based on computer vision techniques identifying all human-built settlement structures.

Data Contents

Data are available in country-year format. Each compressed annual package contains the following 15arcsecond GeoTIFFs:

  • rade9lnmu_xxxx.tif: Nighttime light annual composite
  • set_zscore_sy_xxxx.tif: Statistically estimated brightness levels. Higher levels indicate more robust usage of outdoor lighting, which is correlated with overall energy consumption.
  • set_lightscore_sy_xxxx.tif: Predicted likelihood that a settlement is electrified (0 to 1)
  • set_prplit_conf90_sy_xxxx.tif: Proportion of nights a settlement is statistically brighter than matched uninhabited areas.
  • How to Cite

    If you use the HREA data, please cite as follows:

    Min, Brian and O'Keeffe, Zachary. 2021. High Resolution Electricity Access Indicators Dataset. Ann Arbor, MI: Center for Political Studies, University of Michigan.

    Data Download [more countries soon]