Rural Home Annotation Dataset Mapped by Citizen Scientists in Satellite Imagery

• Published in: Data in brief Vol. 42; p. 108262
• Main Authors: Leonard, Alycia, Wheeler, Scot, McCulloch, Malcolm
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01-06-2022; Elsevier
• Subjects: Citizen science; Computer vision; Data; Geographic information systems; Object detection; Online participation; Remote sensing; Satellite mapping; Computer vision; Online participation; Citizen science; Object detection; Satellite mapping; Remote sensing; Geographic information systems
• ISSN: 2352-3409; 2352-3409
• DOI: 10.1016/j.dib.2022.108262

This article presents a geolocated dataset of rural home annotations on very high resolution satellite imagery from Uganda, Kenya, and Sierra Leone. This dataset was produced through a citizen science project called “Power to the People”, which mapped rural homes for electrical infrastructure planning and computer-vision-based mapping. Additional details on this work are presented in “Power to the People: Applying citizen science to home-level mapping for rural energy access” [1]. 578,010 home annotations were made on approximately 1,267 km2 of imagery over 179 days by over 6,000 volunteers. The bounding-box annotations produced in this work have been anonymized and georeferenced. These raw annotations were found to have a precision of 49% and recall of 93% compared to a researcher-generated set of gold standard annotations. Data on roof colour and shape were also collected and are provided. Metadata about the sensors used to capture the original images and the annotation process are also attached to data records. While this dataset was collected for electrical infrastructure planning research, it can be useful in diverse sectors, including humanitarian assistance and public health.