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

Ayush Patnaik (), Ajay Shah (), Anshul Tayal () and Susan Thomas ()

No 7, Working Papers from xKDR

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 ¡Á 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.

JEL-codes: C8 E0 E1 R1 (search for similar items in EconPapers)
Pages: 39 pages
Date: 2021-10
New Economics Papers: this item is included in nep-big, nep-geo and nep-mac
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https://papers.xkdr.org/papers/Patnaiketal2021_nighttimeLightsData.pdf First version, 2021 (application/pdf)

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