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Open AccessArticle

Estimation and Mapping of Sub-National GDP in Uganda Using NPP-VIIRS Imagery

1
Department of Geography and the Environment, University of Denver, Denver, CO 80208, USA
2
The Frederick S. Pardee Center for International Futures Josef Korbel School of International Studies, University of Denver, 2201 South Gaylord Street, Denver, CO 80208, USA
3
USAID/Uganda Monitoring, Evaluation and Learning Program, Kampala, Uganda
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(2), 163; https://doi.org/10.3390/rs11020163
Received: 20 November 2018 / Revised: 3 January 2019 / Accepted: 9 January 2019 / Published: 16 January 2019
(This article belongs to the Special Issue Advances in Remote Sensing with Nighttime Lights)
Uganda is one of the poorest nations in the world. It is important to obtain accurate, timely data on socio-economic characteristics sub-nationally, so as to target poverty reduction strategies to those most in need. Many studies have demonstrated that nighttime lights (NTL) can be used to measure human activities. Nevertheless, the methods developed from these studies (1) suffer from coarse resolutions, (2) fail to capture the nonlinearity and multi-scale variability of geospatial data, and (3) perform poorly for agriculture-dependent regions. This study proposes a new enhanced light intensity model (ELIM) to estimate the gross domestic product (GDP) for sub-national units within Uganda. This model is developed by combining the NTL data from the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS), the population data from the Global Human Settlement Layer (GHSL), and information on agricultural production and market prices across several commodity types. This resulted in a gridded dataset for Uganda’s GDP at sub-national levels, to capture the spatial heterogeneity in the economic activity. View Full-Text
Keywords: GDP; nighttime lights; agriculture; development GDP; nighttime lights; agriculture; development
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MDPI and ACS Style

Wang, X.; Rafa, M.; Moyer, J.D.; Li, J.; Scheer, J.; Sutton, P. Estimation and Mapping of Sub-National GDP in Uganda Using NPP-VIIRS Imagery. Remote Sens. 2019, 11, 163.

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