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Bará, S., Tapia, C., & Zamorano, J. (2019). Absolute Radiometric Calibration of TESS-W and SQM Night Sky Brightness Sensors. Sensors, 19(6), 1336.
Abstract: We develop a general optical model and describe the absolute radiometric calibration of the readings provided by two widely-used night sky brightness sensors based on irradiance-to-frequency conversion. The calibration involves the precise determination of the overall spectral sensitivity of the devices and also the constant G relating the output frequency of the light-to-frequency converter chip to the actual band-weighted and field-of-view averaged spectral radiance incident on the detector (brightness). From these parameters, we show how to define a rigorous astronomical absolute photometric system in which the sensor measurements can be reported in units of magnitudes per square arcsecond with precise physical meaning.
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Coesfeld, J., Kuester, T., Kuechly, H. U., & Kyba, C. C. M. (2020). Reducing Variability and Removing Natural Light from Nighttime Satellite Imagery: A Case Study Using the VIIRS DNB. Sensors, 20(11), 3287.
Abstract: Temporal variation of natural light sources such as airglow limits the ability of night light sensors to detect changes in small sources of artificial light (such as villages). This study presents a method for correcting for this effect globally, using the satellite radiance detected from regions without artificial light emissions. We developed a routine to define an approximate grid of locations worldwide that do not have regular light emission. We apply this method with a 5 degree equally spaced global grid (total of 2016 individual locations), using data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB). This code could easily be adapted for other future global sensors. The correction reduces the standard deviation of data in the Earth Observation Group monthly DNB composites by almost a factor of two. The code and datasets presented here are available under an open license by GFZ Data Services, and are implemented in the Radiance Light Trends web application.
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Tamir, R., Lerner, A., Haspel, C., Dubinsky, Z., & Iluz, D. (2017). The spectral and spatial distribution of light pollution in the waters of the northern Gulf of Aqaba (Eilat). Sci Rep, 7, 42329.
Abstract: The urbanization of the shores of the Gulf of Aqaba has exposed the marine environment there, including unique fringing coral reefs, to strong anthropogenic light sources. Here we present the first in situ measurements of artificial nighttime light under water in such an ecosystem, with irradiance measured in 12 wavelength bands, at 19 measurement stations spread over 44 square km, and at 30 depths down to 30-m depth. At 1-m depth, we find downwelling irradiance values that vary from 4.6 x 10(-4) muW cm(-2) nm(-1) 500 m from the city to 1 x 10(-6) muW cm(-2) nm(-1) in the center of the gulf (9.5 km from the city) in the yellow channel (589-nm wavelength) and from 1.3 x 10(-4) muW cm(-2 )nm(-1) to 4.3 x 10(-5) muW cm(-2) nm(-1) in the blue channel (443-nm wavelength). Down to 10-m depth, we find downwelling irradiance values that vary from 1 x 10(-6) muW cm(-2 )nm(-1) to 4.6 x 10(-4) muW cm(-2) nm(-1) in the yellow channel and from 2.6 x 10(-5) muW cm(-2) nm(-1) to 1.3 x 10(-4) muW cm(-2) nm(-1) in the blue channel, and we even detected a signal at 30-m depth. This irradiance could influence such biological processes as the tuning of circadian clocks, the synchronization of coral spawning, recruitment and competition, vertical migration of demersal plankton, feeding patterns, and prey/predator visual interactions.
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Stone, J. E., Phillips, A. J. K., Ftouni, S., Magee, M., Howard, M., Lockley, S. W., et al. (2019). Generalizability of A Neural Network Model for Circadian Phase Prediction in Real-World Conditions. Sci Rep, 9(1), 11001.
Abstract: A neural network model was previously developed to predict melatonin rhythms accurately from blue light and skin temperature recordings in individuals on a fixed sleep schedule. This study aimed to test the generalizability of the model to other sleep schedules, including rotating shift work. Ambulatory wrist blue light irradiance and skin temperature data were collected in 16 healthy individuals on fixed and habitual sleep schedules, and 28 rotating shift workers. Artificial neural network models were trained to predict the circadian rhythm of (i) salivary melatonin on a fixed sleep schedule; (ii) urinary aMT6s on both fixed and habitual sleep schedules, including shift workers on a diurnal schedule; and (iii) urinary aMT6s in rotating shift workers on a night shift schedule. To determine predicted circadian phase, center of gravity of the fitted bimodal skewed baseline cosine curve was used for melatonin, and acrophase of the cosine curve for aMT6s. On a fixed sleep schedule, the model predicted melatonin phase to within +/- 1 hour in 67% and +/- 1.5 hours in 100% of participants, with mean absolute error of 41 +/- 32 minutes. On diurnal schedules, including shift workers, the model predicted aMT6s acrophase to within +/- 1 hour in 66% and +/- 2 hours in 87% of participants, with mean absolute error of 63 +/- 67 minutes. On night shift schedules, the model predicted aMT6s acrophase to within +/- 1 hour in 42% and +/- 2 hours in 53% of participants, with mean absolute error of 143 +/- 155 minutes. Prediction accuracy was similar when using either 1 (wrist) or 11 skin temperature sensor inputs. These findings demonstrate that the model can predict circadian timing to within +/- 2 hours for the vast majority of individuals on diurnal schedules, using blue light and a single temperature sensor. However, this approach did not generalize to night shift conditions.
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Sanchez de Miguel, A., Kyba, C. C. M., Zamorano, J., Gallego, J., & Gaston, K. J. (2020). The nature of the diffuse light near cities detected in nighttime satellite imagery. Sci Rep, 10, 7829.
Abstract: Diffuse glow has been observed around brightly lit cities in nighttime satellite imagery since at least the first publication of large scale maps in the late 1990s. In the literature, this has often been assumed to be an error related to the sensor, and referred to as “blooming”, presumably in relation to the effect that can occur when using a CCD to photograph a bright light source. Here we show that the effect seen on the DMSP/OLS, SNPP/VIIRS-DNB and ISS is not only instrumental, but in fact represents a real detection of light scattered by the atmosphere. Data from the Universidad Complutense Madrid sky brightness survey are compared to nighttime imagery from multiple sensors with differing spatial resolutions, and found to be strongly correlated. These results suggest that it should be possible for a future space-based imaging radiometer to monitor changes in the diffuse artificial skyglow of cities.
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