Spectrometry of the Urban Lightscape

TL;DR

This study analyzes multispectral images of urban night lights from the ISS to characterize spectral features, correct atmospheric effects, and develop a linear mixture model for quantifying light source compositions across urban lightscapes.

Contribution

It introduces a method for intercalibrating urban night light spectra and modeling their composition using spectral endmembers and linear mixing, enabling quantitative analysis of urban lighting.

Findings

Spectral slopes are insensitive to atmospheric model variations.

Four spectral endmembers effectively characterize urban light sources.

Urban lightscapes are dominated by warm, low-luminance background lighting.

Abstract

NASA's Gateway to Astronaut Photography of Earth Contains over 30000 photos of 2500 cataloged urban lightscapes (urban night lights) taken from the International Space Station. Over 100 of these multispectral DSLR photos are of sufficient spatial resolution, sharpness and exposure to be used for broadband spectral characterization of urban lightscapes. Analysis of simulated atmospheric transmissivity from the MODTRAN radiative transfer model shows that spectral slopes of transmissivity spectra are relatively insensitive to choice of model atmopshere, with variations in atmospheric path length and aerosol optical depth primarily affecting the bias of the spectrum rather than the slope. This suggests that color tempterature-calibrated RGB channels can be corrected for relative differences in atmospheric scattering and absorption to allow for quantitative intercomparison. A mosaic of 18 intercalibrated RGB photos renders a spectral feature space with four clearly defined spectral endmembers corresponding to white, yellow and red light sources, with brightness modulated by a dark background endmember. These four spectral endmembers form the basis of a linear spectral mixture model which can be inverted to provide estimates of the areal fraction of each endmember present within every pixel instantaneous field of view. The resulting spectral feature space shows two distinct mixing trends extending from the dark endmember to near flat spectrum (white-yellow) and warm spectrum (orange) sources. The distribution of illuminated pixels is strongly skewed toward a lower luminance background of warm spectrum street lighting, with brighter lights generally corresponding to point sources and major thoroughfares. Intercomparison of 18 individual urban lightscape spectral feature spaces show consistent topology, despite variations in exposure and interior mixing trends.