Search Results (49)

Light pollution is a rapidly growing environmental challenge, with the global brightness of the night sky increasing by an average of 9.6% per year. This study assessed the ecological impact of artificial light at night (ALAN) on protected areas in Poland, including all 23 national and 125 landscape parks, from 2012 to 2023. Based on VIIRS satellite radiance data and modelled sky surface brightness (Sa), we developed and applied the Ecological Light Pollution (ELP) scale, which classifies areas into four classes of ecological impact: strong (ELP-A), pronounced (ELP-B), noticeable (ELP-C), and weak or none (ELP-D). The analysis revealed that 38.5% of protected areas are affected by artificial skyglow at levels classified as ELP-B or ELP-C. Under cloudy conditions, which intensify light pollution effects, 22% of national parks and 41.8% of landscape parks fell into these classes. Notably, Wielkopolski National Park exhibited the most pronounced impact (ELP-B) even under clear skies, primarily due to its proximity to the Poznań metropolitan area. In contrast, Bieszczadzki and Białowieski National Parks recorded near-natural darkness (ELP-D). These light pollution effects can disrupt nocturnal species’ behaviour, reduce biodiversity, and degrade opportunities for dark-sky tourism. The findings emphasise the need for targeted mitigation, including stricter outdoor lighting regulations, formal dark-sky protection zones, and public education to preserve protected areas’ ecological integrity and tourism potential. Full article

With the rapid pace of urbanization, light pollution has emerged as a critical environmental issue. Evaluating and managing light pollution effectively is challenging, as traditional monitoring methods often fail to capture its spatial distribution and driving factors comprehensively. To address this limitation, this study integrates Sky Quality Meter (SQM) observational data from three diverse locations—Chaozhou (China), Urumqi (China), and Ghent (Belgium)—with multi-source remote sensing data to construct predictive models of night sky brightness (NSB) using machine learning approaches. Among the tested models, the voting ensemble model demonstrated superior performance, achieving high predictive accuracy and robust generalization across diverse regional datasets. The generated local-scale NSB distribution maps reveal substantial regional variations in light pollution, highlighting the critical influence of local environmental and anthropogenic factors. By combining remote sensing and machine learning, this study offers a scalable and efficient method for evaluating and monitoring light pollution levels at regional scales. The findings underscore the value of these methods in providing actionable insights for light pollution mitigation and management strategies, supporting efforts to reduce its adverse impacts on the environment and society. Full article

This study aimed to address the unexplored relaxing effects of stargazing with different night sky darknesses in a planetarium by conducting an experiment to investigate the physiological effects of the relaxation/stress state on brain and autonomic nervous system activity, as well as the psychological healing effects. Five healthy young women participated in our experiment. We conducted physiological measurements of oxygenated hemoglobin (OxyHb) concentration in the left and right prefrontal cortices by near-infrared spectroscopy, heart rate variability as a measure of the relaxation/stress state, and a psychological assessment of healing on an 11-point Likert scale. We used 9 types of stimuli: 6-star image stimuli that imitated dark star fields (low light pollution) to bright night sky (high light pollution), and movie stimuli that were viewed daily. The results showed that (1) visual stimulation with images of dark night sky significantly reduced the concentration of OxyHb in the right prefrontal cortex and (2) the psychological rating of healing was significantly higher compared to bright night sky. The results of this study will help solve the problems of the mental and physical effects of light pollution on astronomical observations and the reproduction of star images in planetariums. Full article

To suppress the influence of aerosols scattering on the double-edge detection technique and achieve high-accuracy measurement of the wind field throughout the troposphere to the lower stratosphere, an ultraviolet 355 nm Rayleigh–Brillouin Doppler lidar technology based on a dual-pass dual Fabry–Perot interferometer (FPI) is proposed. The wind speed detection principle of this technology is analyzed, and the formulas for radial wind speed measurement error caused by random noise and wind speed measurement bias caused by Mie scattering signal contamination are derived. Based on the detection principle, the structure of the lidar system is designed. Combining the wind speed measurement error and measurement bias on both sides, the parameters of the dual-pass dual-FPI are optimized. The free spectral range (FSR) of the dual-pass dual-FPI is selected as 12 GHz, the bandwidth as 1.8 GHz, and the peak-to-peak spacing as 6 GHz. Further, the detection performance of this new type of Rayleigh–Brillouin Doppler lidar with the designed system parameters is simulated and analyzed. The simulation results show that at an altitude of 0–20 km, within the radial wind speed dynamic range of ±50 m/s, the radial wind speed measurement bias caused by aerosol scattering signal is less than 0.17 m/s in the cloudless region; within the radial wind speed dynamic range of ±30 m/s, the bias is less than 0.44 m/s and 0.91 m/s in the simulated cumulus cloud at 4 km where aerosol backscatter ratio R_β = 3.8 and cirrus cloud at 9 km where R_β = 2.9, respectively; using a laser with a pulse energy of 350 mJ and a repetition frequency of 50 Hz, a 450 mm aperture telescope, setting the detection zenith angle of 30°, vertical resolution of 26 m@0–10 km, 78 m@10–20 km, and 260 m@20–30 km, and a time resolution of 1 min, with the daytime sky background brightness taking 0.3 WSr⁻¹m⁻²nm⁻¹@355 nm, the radial wind speed measurement errors of the system during the day and night are below 2.9 m/s and 1.6 m/s, respectively, up to 30 km altitude, below 0.28 m/s at 10 km altitude, and below 0.91 m/s at 20 km altitude all day. Full article

The most widely used radiance sensor for monitoring Night Sky Brightness (NSB) is the Sky Quality Meter (SQM), making its measurement stability fundamental. A method using the Sun as a calibrator was applied to analyse the quality of the measures recorded in the Veneto Region (Italy) and at La Silla (Chile). The analysis mainly revealed a tendency toward reductions in measured NSB due to both instrument ageing and atmospheric variations. This work compared the component due to instrumental ageing with the contribution of atmospheric conditions. The spectral responsivity of two SQMs working outdoors were analysed in a laboratory after several years of operation, revealing a significant decay, but not enough to justify the measured long-term trends. The contribution of atmospheric variations was studied through the analysis of solar irradiance at the ground, considering it as an indicator of air transparency, and values of the aerosol optical depth obtained from satellite measurements. The long-term trends measured by weather stations at different altitudes and conditions indicated an increase in solar irradiance in the Italian study sites. The comparison among the daily irradiance increase, the reduction in the aerosol optical depth, and the NSB measurements highlighted a darker sky for sites contaminated by light pollution (LP) and a brighter sky for sites not affected by LP, showing a significant and predominant role of atmospheric conditions in relation to NSB change. In the most significant case, the fraction of the variation in NSB explained by AOD changes exceeded 75%. Full article

Growing light pollution is increasingly studied in terrestrial environments. However, research on night lights in coastal ecosystems is limited. We aimed to complement spaceborne remote sensing with ground-based hemispheric photos to quantify the exposure of coastal habitats to light pollution. We used a calibrated DSLR Canon camera with a fisheye lens to photograph the night sky in 24 sites in the rapidly developing area of Moreton Bay, Queensland, Australia, extracting multiple brightness metrics. We then examined the use of the LANcubeV2 photometer and night-time satellite data from SDGSAT-1 for coastal areas. We found that the skies were darker in less urbanized areas and on islands compared with the mainland. Sky brightness near the zenith was correlated with satellite observations only at a coarse spatial scale. When examining light pollution horizontally above the horizon (60–80° degrees below the zenith), we found that the seaward direction was brighter than the landward direction in most sites due to urban glow on the seaward side. These findings emphasize the importance of ground measurements of light pollution alongside satellite imagery. In order to reduce the exposure of coastal ecosystems to light pollution, actions need to go beyond sites with conservation importance and extend to adjacent urban areas. Full article

A neural network was developed using the Multilayer Perceptron (MLP) model to predict the darkness value of the night sky in rural areas. For data collection, a photometer was placed in three different rural locations in the province of Cáceres, Spain, recording darkness values over a period of 23 months. The recorded data were processed, debugged, and used as a training set (75%) and validation set (25%) in the development of an MLP capable of predicting the darkness level for a given date. The network had a single hidden layer of 10 neurons and hyperbolic activation function, obtaining a coefficient of determination (R²) of 0.85 and a mean absolute percentage error (MAPE) of 6.8%. The developed model could be employed in unpopulated rural areas for the promotion of sustainable astronomical tourism. Full article

The pervasive use of anthropogenic light at night has significantly increased the brightness of the night sky, which negatively affects human wellbeing, the ecology of plants and animals, night sky aesthetics, and astronomical observations. However, public awareness of light pollution remains limited. This study evaluates the effectiveness of an ‘eco-art installation’ in raising awareness about the impacts of anthropogenic light at night (ALAN). The installation, ‘Scope’, used light as a medium to convey the adverse effects of anthropogenic light at the Te Ramaroa festival in Nelson, New Zealand, which is held to celebrate light in the depths of winter. An online survey assessed the awareness of Nelson region residents, comparing responses between those who experienced the installation and those who did not, and assessing the self-reported knowledge increase after engagement with the installation. The findings indicated that eco-art installations can significantly enhance the public’s understanding of ALAN’s environmental and health impacts. The installation successfully increased self-reported specific knowledge about ALAN, with 92% of visitors reporting learning something new; however, overarching knowledge and levels of concern were largely similar between the groups. Emotional engagement was high, with 62% of viewers stating that the installation invoked an emotional response. While the study did not measure beha-vioural changes, 94% of festival participants found it at least ‘somewhat appropriate’ and 64% found it ‘very’ or ‘entirely appropriate’ to raise awareness of these issues at such events, suggesting a potential foundation for future action. This research underscores the promise of art–science collaborations in environmental education and public engagement. Full article

Solid-state lighting technology, such as LED devices, is critical to improving energy efficiency in street lighting systems. In Ecuador, government policies have established the obligation to exclusively use LED systems starting in 2023, except in special projects. Ecuador, known for its vast biodiversity, protects its national parks, which are rich in flora, fauna and natural resources, through international institutions and agreements such as UNESCO, CBD and CITES. Although reducing electrical consumption usually measures energy efficiency, this article goes further. It considers aspects such as the correlated color temperature in the lighting design of protected areas, light pollution and the decrease in energy quality due to harmonic distortion. Measurements of the electromagnetic spectrum of the light sources were made in an area in the Galápagos National Park of Ecuador, revealing highly correlated color temperatures that can affect ecosystem cycles. In addition, the investigation detected levels of light pollution increasing the night sky brightness and a notable presence of harmonic distortion in the electrical grid. Using simulations to predict the behavior of these variables offers an efficient option to help preserve protected environments and the quality of energy supply while promoting energy savings. Full article

A smarter city should be a safer city. Nighttime safety in metropolitan areas has long been a global concern, particularly for large cities with diverse demographics and intricate urban forms, whose citizens are often threatened by higher street-level crime rates. However, due to the lack of night-time urban appearance data, prior studies based on street view imagery (SVI) rarely addressed the perceived night-time safety issue, which can generate important implications for crime prevention. This study hypothesizes that night-time SVI can be effectively generated from widely existing daytime SVIs using generative AI (GenAI). To test the hypothesis, this study first collects pairwise day-and-night SVIs across four cities diverged in urban landscapes to construct a comprehensive day-and-night SVI dataset. It then trains and validates a day-to-night (D2N) model with fine-tuned brightness adjustment, effectively transforming daytime SVIs to nighttime ones for distinct urban forms tailored for urban scene perception studies. Our findings indicate that: (1) the performance of D2N transformation varies significantly by urban-scape variations related to urban density; (2) the proportion of building and sky views are important determinants of transformation accuracy; (3) within prevailed models, CycleGAN maintains the consistency of D2N scene conversion, but requires abundant data. Pix2Pix achieves considerable accuracy when pairwise day–and–night-night SVIs are available and are sensitive to data quality. StableDiffusion yields high-quality images with expensive training costs. Therefore, CycleGAN is most effective in balancing the accuracy, data requirement, and cost. This study contributes to urban scene studies by constructing a first-of-its-kind D2N dataset consisting of pairwise day-and-night SVIs across various urban forms. The D2N generator will provide a cornerstone for future urban studies that heavily utilize SVIs to audit urban environments. Full article

Recent smart telescopes allow the automatic collection of a large quantity of data for specific portions of the night sky—with the goal of capturing images of deep sky objects (nebula, galaxies, globular clusters). Nevertheless, human verification is still required afterwards to check whether celestial targets are effectively visible in the images produced by these instruments. Depending on the magnitude of deep sky objects, the observation conditions and the cumulative time of data acquisition, it is possible that only stars are present in the images. In addition, unfavorable external conditions (light pollution, bright moon, etc.) can make capture difficult. In this paper, we describe DeepSpaceYoloDataset, a set of 4696 RGB astronomical images captured by two smart telescopes and annotated with the positions of deep sky objects that are effectively in the images. This dataset can be used to train detection models on this type of image, enabling the better control of the duration of capture sessions, but also to detect unexpected celestial events such as supernova. Full article

Prior to assimilating hyperspectral infrared data on the FengYun (FY) satellite in the numerical weather prediction (NWP) system, it is necessary to identify the quality and bias characteristics of these data, especially as China’s first early-morning-orbit satellite data. Using the numerical model CMA-GFS (China Meteorological Administration Global Forecast System) and the observation of FY-3E HIRAS-II (Hyperspectral Infrared Atmospheric Sounder-II), the differences between observed and simulated brightness temperatures (O-Bs) are comprehensively analyzed, with a focus on evaluating the long-wave (LW) temperature sounding channels of HIRAS-II observation in the clear sky. The results show that the O-Bs in the LW channels are between ±1.0 K, except for the ${\mathrm{C}\mathrm{O}}_2$ absorption line peak at 667 ${\mathrm{c}\mathrm{m}}^{-1}$. Only a tiny variation in O-Bs, with relative consistency, could be observed during the day, the line of dawn and dusk, and night. The difference in the standard deviations of O-Bs in the three cases is less than 0.1 K. The O-Bs of two typical channels (channels 14 and 47) in the stratosphere have disturbances at individual times, whereas the O-Bs are much more stable in time series in the tropospheric channels. The O-Bs in different channels show the characteristics of changing with the latitude, but the bias and standard deviations of O-Bs during the ascending and descending stages are not much different, except for the bias of channel 47 in low latitude. The optimal ranking of Fields of View (FOVs) in assimilation is derived from a priori analysis of O-Bs. The results demonstrate that FOV4 and FOV5 are the best in a Field of Regard (FOR) compared to all LW channels of HIRAS-II in constructions of their O-Bs and magnitude of O-B standard deviations, and they can be used as the preferred FOVs for assimilation. While the O-Bs in FOV1 and FOV2 are slightly larger, the O-Bs’ characteristics also meet the assimilation requirements and can be used as assimilation FOVs in HIRAS-II LW channels after FOV4 and FOV5 lose their efficacy. Full article

The use of RGB cameras in photometric applications has grown over the last few decades in many fields such as industrial applications, light engineering and the analysis of the quality of the night sky. In this last field, they are often used in conjunction with a Sky Quality Meter (SQM), an instrument used for the measurement of night sky brightness (NSB), mainly when there is a significant amount of artificial light at night (ALAN). The performances of these two instruments are compared here. A simple source composed of nine narrowband LEDs in an integrating sphere was used to excite the two instruments and therefore measure the spectral responsivity of the SQM and of the three channels of the camera. The estimated uncertainties regarding spectral responsivity were less than 10%. A synthetic instrument approximating the SQM’s responsivity can be created using a combination of the R, G and B channels. The outputs of the two instruments were compared by measuring the spectral radiance of the night sky. An evaluation of the spectral mismatch between the two instruments completed the analysis of their spectral sensitivity. Finally, the measurements of real SQMs in four sites experiencing different levels of light pollution were compared with the values obtained by processing the recorded RGB images. Overall, the analysis shows that the two instruments have significantly different levels of spectral responsivity, and the alignment of their outputs requires the use of a correction which depends on the spectral distribution of the light coming from the sky. A synthetic SQM will always underestimate real SQM measures; an average correction factor was evaluated considering nine sky spectra under low and medium levels of light pollution; this was determined to be 1.11 and, on average, compensated for the gap. A linear correction was also supposed based on the correlation between the NSB levels measured by the two instruments; the mean squared error after the correction was 0.03 mag arcsec⁻². Full article

The data retrieved from satellite imagery and ground-based photometers are the two main sources of information on light pollution and are thus the two main tools for tackling the problem of artificial light pollution at night (ALAN). While satellite data offer high spatial coverage, on the other hand, photometric data provide information with a higher degree of temporal resolution. Thus, studying the proper correlation between both sources will allow us to calibrate and integrate them to obtain data with both high temporal resolution and spatial coverage. For this purpose, more than 15,000 satellite measurements and 400,000 measurements from 72 photometers for the year 2022 were used. The photometers used were the Sky-Glow Wireless Autonomous Sensor (SG-WAS) and Telescope Encoder and Sky Sensor WIFI (TESS-W) types, located at different ground-based locations, mainly in Spain. These photometers have a spectral sensitivity closer to that of VIIRS than to the Sky Quality Meter (SQM). In this study, a good correlation of data from the Day–Night Band (DNB) from the Visible Infrared Imaging Radiometer Suite (VIIRS) with a red photometric network between 19.41 mag/arcsec${}^2$ and 21.12 mag/arcsec${}^2$ was obtained. Full article

For improving the night recognition of road markings and enhancing the driving safety of asphalt pavements, single-factor optimization is used to investigate the effects of the component materials, including luminescent power, pigment, filler, and anti-sedimentation agent, on the luminous performance of a coating. Additionally, their composition ratios are optimized using response surface methodology. A phosphorescent marking coating is prepared to investigate the micromorphology, excitation, and emission properties using scanning electron microscopy (SEM) and molecular fluorescence spectroscopy (MFS). The optimum thickness of the coating on an asphalt pavement is investigated, and the durability of the coating on asphalt pavement using a wheel rutting test is evaluated. The results show that the 300 mesh yellow-green luminous powder has the optimal overall performance, with an initial luminescence that exceeds that of orange and sky blue by three times. Initial brightness is mainly influenced by aluminate luminescent powder (ALP), which increases with the dosage. ALP and fumed silica powder (FSP) have a positive effect on brightness after centrifugation, and the effect of FSP dosage is more significant. ALP, rutile titanium dioxide powder (RTDP), and FSP influence the wear value of the coating, and the magnitude of the effect is RTDP > FSP > ALP. The optimal dosages of the main component are 27% ALP, 5% RTDP, and 0.8% FSP. The results of SEM show that the components in the coating are evenly dispersed, and the surface of the coating is rough. The peak excitation wavelength of 420 nm means that the coating has the best excitation effect in UV light, and its emission spectrum in the 440–760 nm wavelength range is well within the sensitive recognition zone of the human eye. The initial brightness gradually reached 4.38 cd/m² when the coating thickness was increased from 482 μm to 546 μm, and the optimal application thickness of the luminous coating was determined to be 500 μm. At high and normal temperatures, the rutting stripping rates of the luminous marking coating are 16.8% and 8.2%, indicating its satisfactory durability. This study provides an experimental basis for the ratio optimization design of a luminous coating for asphalt pavements. Full article