A monthly night-time light composite dataset of NOAA-20 in China: a multi-scale comparison with S-NPP

Abstract

ABSTRACT Night-Time light (NTL) data have been widely used for monitoring the dynamics of human activities and socioeconomics. As a new-generation satellite for acquiring NTL data, the National Oceanic and Atmospheric Administration-20 (NOAA-20) was successfully launched in November 2017. To support broad-scale environmental applications, it is necessary to generate monthly NTL composites of NOAA-20. Taking China as the study area, we produced NOAA-20 monthly NTL composites from April 2019 to December 2019. First, we performed a series of de-noising steps to eliminate NOAA-20 NTL pixels affected by sunlight, moonlight, high scan angles, clouds and further eliminated NTL outliers in time series by using a modified z-score method. Then, we aggregated daily NOAA-20 NTL data to produce monthly NTL composites to improve data coverage and stability. Subsequently, we examined the consistency of monthly composites between NOAA-20 and S-NPP at multiple scales, including provincial, prefectural, and pixel levels. Our results show that the monthly NTL composites of NOAA-20 are in good agreement with that of S-NPP with an R2 ranging from 0.81 to 0.99. Besides, we found that the spatial variation trends of the NOAA-20 monthly NTL composites are similar to that of S-NPP monthly NTL composites. We believe that the monthly NTL composites of NOAA-20 are very close to that of S-NPP and will open up more opportunities for relevant NTL studies.