Garbasevschi, Oana Mihaela und Garcia de León, Andrea Sofia und Andersen, L. E. und Guzman Prudenico, G. und Wurm, Michael und Taubenböck, Hannes (2024) Spatio-Temporal Estimation of Electricity Consumption in Bolivian Municipalities Using Nighttime Lights. Geocarto International, 41 (1), Seiten 1-29. Taylor & Francis. doi: 10.1080/10106049.2026.2657705. ISSN 1010-6049.
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Offizielle URL: https://www.tandfonline.com/doi/full/10.1080/10106049.2026.2657705
Kurzfassung
Few research studies have focused on the nature of the relationship between nighttime lights and electricity consumption at subnational levels in South America, a region with heterogeneous geography and urbanization levels and complex socioeconomic dynamics. This study shows that it is possible to estimate, for Bolivia, a wide range of indicators of electricity consumption at the municipality level and two temporal scales using features derived from nighttime lights and other spatial data sources, in combination with readily available municipality characteristics. The prediction errors for annual electricity consumption range between 13% MAPE for average residential consumption and 59% MAPE for average commercial consumption. Similar accuracies are obtained when predicting monthly values. For both annual and monthly electricity consumption, we highlight the variation in estimation accuracy for various municipality subsets and show that prediction can be significantly improved when selecting municipalities based on population size, energy poverty, or levels of sustainable development.
| elib-URL des Eintrags: | https://elib.dlr.de/223992/ | ||||||||||||||||||||||||||||
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| Dokumentart: | Zeitschriftenbeitrag | ||||||||||||||||||||||||||||
| Titel: | Spatio-Temporal Estimation of Electricity Consumption in Bolivian Municipalities Using Nighttime Lights | ||||||||||||||||||||||||||||
| Autoren: |
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| Datum: | 17 April 2024 | ||||||||||||||||||||||||||||
| Erschienen in: | Geocarto International | ||||||||||||||||||||||||||||
| Referierte Publikation: | Ja | ||||||||||||||||||||||||||||
| Open Access: | Ja | ||||||||||||||||||||||||||||
| Gold Open Access: | Ja | ||||||||||||||||||||||||||||
| In SCOPUS: | Ja | ||||||||||||||||||||||||||||
| In ISI Web of Science: | Ja | ||||||||||||||||||||||||||||
| Band: | 41 | ||||||||||||||||||||||||||||
| DOI: | 10.1080/10106049.2026.2657705 | ||||||||||||||||||||||||||||
| Seitenbereich: | Seiten 1-29 | ||||||||||||||||||||||||||||
| Verlag: | Taylor & Francis | ||||||||||||||||||||||||||||
| ISSN: | 1010-6049 | ||||||||||||||||||||||||||||
| Status: | veröffentlicht | ||||||||||||||||||||||||||||
| Stichwörter: | Electricity forecast; machine learning; remote sensing; sustainable development; time series analysis | ||||||||||||||||||||||||||||
| HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||||||
| HGF - Programm: | Raumfahrt | ||||||||||||||||||||||||||||
| HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||||||||||
| DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||||||||||
| DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||||||||||
| DLR - Teilgebiet (Projekt, Vorhaben): | R - Fernerkundung u. Geoforschung | ||||||||||||||||||||||||||||
| Standort: | Oberpfaffenhofen | ||||||||||||||||||||||||||||
| Institute & Einrichtungen: | Deutsches Fernerkundungsdatenzentrum > Georisiken und zivile Sicherheit | ||||||||||||||||||||||||||||
| Hinterlegt von: | Wurm, Michael | ||||||||||||||||||||||||||||
| Hinterlegt am: | 22 Apr 2026 10:29 | ||||||||||||||||||||||||||||
| Letzte Änderung: | 22 Apr 2026 10:29 |
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