Variation of Individual Location Radiance in VIIRS DNB Monthly Composite Images

Abstract

With the growing size and use of night light time series from the Visible Infrared Imaging Radiometer Suite Day/Night Band (DNB), it is important to understand the stability of the dataset. All satellites observe differences in pixel values during repeat observations. In the case of night light data, these changes can be due to both environmental effects and changes in light emission. Here we examine the stability of individual locations of particular large scale light sources (e.g., airports and prisons) in the monthly composites of DNB data from April 2012 to September 2017. The radiances for individual pixels of most large light emitters are approximately normally distributed, with a standard deviation of typically 15–20% of the mean. Greenhouses and flares, however, are not stable sources. We observe geospatial autocorrelation in the monthly variations for nearby sites, while the correlation for sites separated by large distances is small. This suggests that local factors contribute most to the variation in the pixel radiances and furthermore that averaging radiances over large areas will reduce the total variation. A better understanding of the causes of temporal variation would improve the sensitivity of DNB to lighting changes.

Testing for changes in light emissions from certified International Dark Sky Places

“…Each location in this study was imaged 1-2 times per night, and the EOG used nights with clear conditions, without twilight or moon illumination, and with no stray light falling on the satellite [29] to assign a single value to each location. This procedure reduces the intrinsic variability of the data, but monthly variations at typically the 15-20% level remain for single pixels [33]. These variations are reduced when a larger area is considered [33].…”

“…This procedure reduces the intrinsic variability of the data, but monthly variations at typically the 15-20% level remain for single pixels [33]. These variations are reduced when a larger area is considered [33].…”

“…A major source of variation in the monthly DNB composites is due to seasonal changes, particularly snow cover [2,33]. For this reason, for each IDSP we examined radiance trends for nearby areas that were not part of the main analysis, in order to select a set of months that experienced relatively little variation.…”

“…It is critical to note that the fit changes for each town are not truly independent observations, because the towns are located fairly close to each other, and experience similar seasonal variations (see [33]). For example, if the radiance observed for a town in IDSR Westhavelland fluctuates upward in one October, it must be expected that the neighboring towns will experience a similar upward fluctuation.…”

The Interannual Calibration and Global Nighttime Light Fluctuation Assessment Based on Pixel-Level Linear Regression Analysis

“…Meanwhile, the PBPIF-based model has also achieved better correction results in comparison with the existing two widely used calibration models. Although the wide selection of PIF pixels globally can best avoid PIF low variation and satellite observation interference [60], the use of a strictly constant physical calibrator will be the key to the next phase of NTL interannual correction. Finally, based on the corrected time series NTL datasets, the global LICC is produced ( Figure S8).…”