Impact of temporal compositing on nighttime light data and its applications

• Published in: Remote sensing of environment 2022-06, Vol.274, p.113016, Article 113016
• Main Authors: Zheng, Qiming, Weng, Qihao, Zhou, Yuyu, Dong, Baiyu
• Format: Article
• Language: English
• Subjects: Cities; Cloud cover; Daily VIIRS images; Data processing; Geographic variation; Human influences; Night; Nighttime; Nighttime light imagery; NTL applications; Outliers (statistics); Pixels; Temperate climates; Temporal compositing; Uncertainty; Urbanization
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2022.113016

In recent decades, nighttime light (NTL) images have been widely explored to portray human footprints. Most of the studies used monthly or yearly temporal composite NTL products as a solution for invalid observations due to cloud coverage and outlier signals. However, the impact of temporal compositing on NTL data and its applications remains largely unclear. Here, we utilized over 180,000 daily NTL tiles from NASA's Black Marble VIIRS product (VNP46A2, 2012–2020), covering 230 cities from China and the United States, to delve into the influence of temporal compositing on valid pixel coverage and spatiotemporal pattern of NTL data and the performance of three representative types of NTL-based applications. Our analysis showed temporal compositing was an imperative and efficient solution to the prevailing invalid observations. On average a 16-day composite was required to ensure at least 95% of valid pixel coverage for a city, where a longer composite period was needed for cities in a pluvial temperate climate zone. Compositing daily NTL data into a 3-day to 31-day period markedly reduced its spatiotemporal variation and incurred a 3–9 nWatts/cm2/sr, or 22%–37%, absolute difference in NTL magnitude, which was particularly high in developed cities and intra-city areas. We attributed such effect to the number of valid observations available for generating the composite data and the extremely high variation in daily NTL stemmed from human activities, as well as the uncertainties in VNP46 product and VIIRS instrument. The impact of temporal compositing on NTL-based applications varied greatly, from insignificant to very sensitive, across application types and spaces. Our analysis provides a comprehensive understanding of the capability and uncertainties in NTL data processing and applications, facilitating end-users to make the best use of NTL observations in high temporal frequency. •The impact of temporal compositing on the quality, pattern, and application of NTL data was explored.•Ensuring >95% valid observations coverage required at least a 16-day composite.•Temporal compositing incurred noticeable differences in the pattern of NTL data.•The impact of temporal compositing on NTL applications varied greatly across type and space.