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Satellite Hyperspectral Nighttime Light Observation and Identification with DESIS
Satellite Hyperspectral Nighttime Light Observation and Identification with DESIS
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Satellite Hyperspectral Nighttime Light Observation and Identification with DESIS
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Satellite Hyperspectral Nighttime Light Observation and Identification with DESIS
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Satellite Hyperspectral Nighttime Light Observation and Identification with DESIS
Satellite Hyperspectral Nighttime Light Observation and Identification with DESIS
Journal Article

Satellite Hyperspectral Nighttime Light Observation and Identification with DESIS

2024
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Overview
The satellite imagery of nighttime lights (NTLs) has been studied to understand human activities, economic development, and more recently, the ecological impact of brighter night skies. The Visible Infrared Imaging Radiometer Suite (VIIRS) Day–Night Band (DNB) offers perhaps the most advanced nighttime imaging capabilities to date, but its large pixel size and single band capture large-scale changes in NTL while missing granular but important details, such as lighting type and brightness. To better understand individual NTL sources in a region, the spectra of nighttime lights captured by the DLR Earth Sensing Imaging Spectrometer (DESIS) were extracted and compared against near-coincident VIIRS DNB imagery. The analysis shows that DESIS’s finer spatial and spectral resolutions can detect individual NTL locations and types beyond what is possible with the DNB. Extracted night light spectra, validated against ground truth measurements, demonstrate DESIS’s ability to accurately detect and identify narrow-band atomic emission lines that characterize the spectra of high-intensity discharge (HID) light sources and the broader spectral features associated with different light-emitting diode (LED) lights. These results suggest the possible application of using hyperspectral data from moderate-resolution sensors to identify lamp construction details, such as illumination source type and light quality in low-light contexts. NTL data from DESIS and other hyperspectral sensors may improve the scientific understanding of light pollution, lighting quality, and energy efficiency by identifying, evaluating, and mapping individual and small groups of light sources.