Assessment of Systematic Errors in Mapping Electricity Access Using Night-Time Lights: A Case Study of Rwanda and Kenya

dc.contributor.authorRaji, Tunmise;
dc.contributor.authorTaneja, Jay;
dc.contributor.authorWilliams, Nathaniel
dc.date.accessioned2025-04-04T11:33:00Z
dc.date.available2025-04-04T11:33:00Z
dc.date.issued2024-10
dc.description.abstractRemotely sensed nighttime light data have become vital for electrification mapping in data-scarce regions. However, uncertainty persists regarding the veracity of these electrification maps. This study investigates how characteristics of electrified areas influence their detectability using nighttime lights. Utilizing a dataset comprising the locations, installation date, and electricity purchase history of thousands of electric meters and transformers from utilities in Rwanda and Kenya, we present a systematic error assessment of electrification maps produced with nighttime lights. Descriptive analysis is employed to offer empirical evidence that the likelihood of successfully identifying an electrified nighttime light pixel increases as characteristics including the time since electrification, the number of meters within a pixel, and the total annual electricity purchase of meters in a pixel increase. The performance of models trained on various temporal aggregations of nighttime light data (annual, quarterly, monthly, and daily) was compared, and it was determined that aggregation at the monthly level yielded the best results. Additionally, we investigate the transferability of electrification models across locations. Our findings reveal that models trained on data from Rwanda demonstrate strong transferability to Kenya, and vice versa, as indicated by balanced accuracies differing by less than 5% when additional data from the test location are included in the training set. Also, models developed with data from the centralized grid in East Africa were found to be useful for detecting areas electrified with off-grid systems in West Africa. This research provides valuable insight into the characterization of sources of nighttime lights and their utility for mapping electrification.
dc.identifier.citationRaji, Tunmise, Jay Taneja, and Nathaniel Williams. 'Assessment of Systematic Errors in Mapping Electricity Access using Night-Time Lights: A Case Study of Rwanda and Kenya', Remote Sensing (Basel, Switzerland), vol. 16/no. 19, (2024), pp. 3561.
dc.identifier.issnISSN 2072-4292
dc.identifier.issnEISSN 2072-4292
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/10370
dc.language.isoen
dc.publisherMDPI AG
dc.titleAssessment of Systematic Errors in Mapping Electricity Access Using Night-Time Lights: A Case Study of Rwanda and Kenya
dc.typeArticle
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
remotesensing-16-03561-v2.pdf
Size:
24.05 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Collections