But clouds got in my way: Bias and bias correction of VIIRS nighttime lights data in the presence of clouds

Abstract

The VIIRS nighttime lights dataset constitutes progress in the measurement of night lights radiance, with monthly data at a pixel of roughly 0.5km iA 0.5km. We identify a downward bias in the reported radiance when the number of cloud-free images in a month is low. This bias often takes on large values from -10% to -30%. We develop a cautious bias-correction scheme which partially addresses this problem. This scheme is applied upon the pixel-level dataset to create an improved dataset. The bias-corrected data hews closer to the ground truth as seen in household survey data.