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

Author

Listed:
  • Ayush Patnaik

    (xKDR Forum)

  • Ajay Shah

    (xKDR Forum)

  • Anshul Tayal

    (xKDR Forum)

  • Susan Thomas

    (xKDR Forum)

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.

Suggested Citation

  • Ayush Patnaik & Ajay Shah & Anshul Tayal & Susan Thomas, 2021. "But clouds got in my way: Bias and bias correction of VIIRS nighttime lights data in the presence of clouds," Working Papers 7, xKDR.
    • Handle: RePEc:anf:wpaper:7
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    File URL: https://papers.xkdr.org/papers/Patnaiketal2021_nighttimeLightsData.pdf
    File Function: First version, 2021
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    More about this item

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • E0 - Macroeconomics and Monetary Economics - - General
    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics

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