Reducing Variability and Removing Natural Light from Nighttime Satellite Imagery: A Case Study Using the VIIRS DNB

Area of Science:

• Earth Observation
• Remote Sensing
• Atmospheric Science

Background:

• Natural light sources like airglow fluctuate, complicating the detection of subtle artificial light emissions from sources such as villages using night light sensors.
• Accurate monitoring of artificial light is crucial for various applications, including urbanization studies, disaster response, and ecological impact assessments.

Purpose of the Study:

• To develop and present a global method for correcting satellite-detected radiance data for the effects of natural light variations, specifically airglow.
• To enhance the capability of night light sensors to detect small, localized changes in artificial light emissions.

Main Methods:

• A routine was developed to identify a global grid of locations with minimal to no regular artificial light emissions.
• Data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB) were analyzed using a 5-degree equally spaced global grid (2016 locations).
• Satellite radiance from unlit regions was used to establish a baseline for correcting light emission data.

Main Results:

• The developed correction method significantly reduces the standard deviation in Earth Observation Group monthly DNB composites by nearly a factor of two.
• The method provides a more accurate representation of artificial light by mitigating the influence of natural light variability.
• The developed code is adaptable for use with other future global remote sensing instruments.

Conclusions:

• The presented method offers a robust solution for globally correcting natural light interference in satellite-based night light observations.
• This advancement improves the reliability of detecting and quantifying small-scale artificial light sources.
• The associated code and datasets are openly available, fostering further research and application development, including the Radiance Light Trends web application.