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.