Evaluating Human Photoreceptoral Inputs from Night-Time Lights Using RGB Imaging Photometry

Abstract

Night-time lights interact with human physiology through different pathways starting at the retinal layers of the eye; from the signals provided by the rods; the S-, L- and M-cones; and the intrinsically photosensitive retinal ganglion cells (ipRGC). These individual photic channels combine in complex ways to modulate important physiological processes, among them the daily entrainment of the neural master oscillator that regulates circadian rhythms. Evaluating the relative excitation of each type of photoreceptor generally requires full knowledge of the spectral power distribution of the incoming light, information that is not easily available in many practical applications. One such instance is wide area sensing of public outdoor lighting; present-day radiometers onboard Earth-orbiting platforms with sufficient nighttime sensitivity are generally panchromatic and lack the required spectral discrimination capacity. In this paper, we show that RGB imagery acquired with off-the-shelf digital single-lens reflex cameras (DSLR) can be a useful tool to evaluate, with reasonable accuracy and high angular resolution, the photoreceptoral inputs associated with a wide range of lamp technologies. The method is based on linear regressions of these inputs against optimum combinations of the associated R, G, and B signals, built for a large set of artificial light sources by means of synthetic photometry. Given the widespread use of RGB imaging devices, this approach is expected to facilitate the monitoring of the physiological effects of light pollution, from ground and space alike, using standard imaging technology.

Keeping light pollution at bay: a red-lines, target values, top-down approach

“…This approach seeks to reduce their excessive light emissions, especially the most detrimental ones, and is formulated basically (although not exclusively) in terms of intensive quantities, that is, indicators of relative performance. Some examples of these intensive quantities are the fraction of light emitted by a luminaire toward the upper hemisphere, the average number of lumen per square meter (lx) on the lit surfaces, the fraction of the light emitted by a lamp that effectively reaches the area intended to be illuminated (utilization factor), the luminous efficacy of the lighting system, measured in lm per W, or the relative spectral content of the light, usually described by CCT for visual purposes and by other metrics for non-visual applications (Bará et al, 2019b;Galadí-Enríquez, 2018;Lucas et al, 2014;Rea and Figueiro, 2016;Rea et al, 2012;Sánchez de Miguel et al, 2019).…”

Multispectral estimation of retinal photoreceptoral inputs

“…Salvador Bará, *1 Maria Angeles Bonmati-Carrion, 2,3 Juan Antonio Madrid, 2,3 Maria Angeles Rol, 2,3 and Jaime coefficients, in order to obtain accurate photoreceptoral input estimates. The optimum coefficients of these linear combinations can be determined by means of minimum variance estimators applied to the expected set of spectra to which persons will be exposed [4,6], or, even more generally, by directly fitting in a least-squares sense the available multispectral sensitivity curves to the photoreceptoral ones. The latter approach has the advantage of not requiring any a priori choice of an initial spectral set to build the exposure estimator.…”

“…A total of 205 lamp spectra were used to compute these plots, comprising compact fluorescent, metal halide, ceramic metal-halide, T-type fluorescent, halogen, high-pressure sodium vapour, incandescent, light-emitting diodes with CCT in the range 1900÷7400 K, and mercury vapor lamps available on the market. The detailed characteristics of this lamp dataset can be found in reference [4].…”

“…Evaluating photoreceptoral exposure in these bands is a requirement for quantitatively assessing the non-visual effects of light, both for basic, clinical, and population studies, and for the design and development of new * E-mail: salva.bara@usc.gal photonic lighting components and applications. Although retinal irradiance is strictly determined by the corneal spectral radiance and the spectral attenuation of the eye tissues [4], the current trend in experimental studies and theoretical phototransduction models formulation is using corneal irradiance as a proxy for determining retinal exposures [3,5]. The reasons behind this extended practice are that corneal irradiance is easier to measure in most everyday life conditions than radiance, besides it provides a scaled and field-of-view averaged estimation of the actual retinal exposure.…”

Mapping the Melatonin Suppression, Star Light and Induced Photosynthesis Indices with the LANcube

“…However, spectral measurements are not the easiest to obtain, especially if many of them are required. It has been shown that three-band Red, Green, Blue (RGB) photometric data can be used to determine spectral indices or photoreceptor stimuli from values recorded by a Digital single-lens reflex camera (DSLR) [19,20]. This method is much faster and easier to perform.…”