Intercalibration and Gaussian Process Modeling of Nighttime Lights
Imagery for Measuring Urbanization Trends in Africa 2000–2013

Nighttime lights (NTL) imagery, maintained by the National Oceanic and Atmospheric Administration, offers a unique vantage point for studying urbanization, human settlements, population dynamics, electricity consumption, natural disasters, and military actions, to name a few. A well-documented deficiency of this dataset is the lack of sensor calibration between individual satellites and their annual acquisition dates, which makes the imagery unsuitable for temporal analysis in its raw format. Here we have generated a corrected time series of annual NTL images for Africa (2000-2013) by building on a widely used intercalibration method pioneered by NOAA scientists. Post intercalibration residual noise was removed using Gaussian process methods (GP) to identify NTL latent functions independent from the temporal noise signals in the annual datasets. Preliminary validation tests have indicated that the GP smoothed time series improved the established correlation between NTL and Gross Domestic Product. The smoothed datasets are made available here for use in the public domain.



Citation: Savory DJ, Gething PW, Bennett, Andrade-Pacheco R, Midekisa A, Sturrock HJW. Intercalibration and Gaussian Process Modeling of Nighttime Lights Imagery for Measuring Urbanization Trends in Africa 2000–2013. Remote Sens. 2017, 9(7), 713; doi:10.3390/rs9070713



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