Power to the people: Applying citizen science and computer vision to home mapping for rural energy access
Summary. Researchers combined citizen science, satellite imagery, and computer vision to map remote homes in Uganda, Kenya, and Sierra Leone for rural electricity planning. Thousands of volunteers annotated 578,010 homes on the Zooniverse platform, achieving 93% recall. These annotations trained a machine learning model that mapped homes at scale with 67% precision, demonstrating that citizen science and computer vision can rapidly identify where rural populations live to support energy system design.
Cite this article
Leonard, A., Wheeler, S., & McCulloch, M.. (2022). Power to the people: Applying citizen science and computer vision to home mapping for rural energy access. International Journal of Applied Earth Observation and Geoinformation. https://doi.org/10.1016/j.jag.2022.102748
Leonard, Alycia, et al. “Power to the people: Applying citizen science and computer vision to home mapping for rural energy access.” International Journal of Applied Earth Observation and Geoinformation, 2022. https://doi.org/10.1016/j.jag.2022.102748.
Leonard, Alycia, Scot Wheeler, and Malcolm McCulloch. 2022. “Power to the people: Applying citizen science and computer vision to home mapping for rural energy access.” International Journal of Applied Earth Observation and Geoinformation. https://doi.org/10.1016/j.jag.2022.102748.
@article{leonard-2022-power-people-applying-citizen-science,
title = {Power to the people: Applying citizen science and computer vision to home mapping for rural energy access},
author = {Alycia Leonard and Scot Wheeler and Malcolm McCulloch},
journal = {International Journal of Applied Earth Observation and Geoinformation},
year = {2022},
doi = {10.1016/j.jag.2022.102748},
url = {https://doi.org/10.1016/j.jag.2022.102748}
}
TY - JOUR TI - Power to the people: Applying citizen science and computer vision to home mapping for rural energy access AU - Alycia Leonard AU - Scot Wheeler AU - Malcolm McCulloch JO - International Journal of Applied Earth Observation and Geoinformation PY - 2022 DO - 10.1016/j.jag.2022.102748 UR - https://doi.org/10.1016/j.jag.2022.102748 ER -
Details
- DOI
- 10.1016/j.jag.2022.102748
- Countries
- Uganda, Kenya, Sierra Leone
- Regions
- Africa
- Categories
- energy, broadband-and-digital
- Added
- 2026-04-28