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Cottam, C. (1929). A shower of grebes. The Condor, 31(1), 80–81.
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Treanor, P. J. (1973). A simple propagation law for artificial night-sky illumination. The Observatory, 93, 117–120.
Abstract: The problem of locating new large astronomical observatories in sites which have a suitably dark night sky (artificial excess of the order of omi) is becoming increasingly difficult in Europe and the United States, on account of extensive urban development, the high luminous efficiency of modern discharge lighting, and the scattering of light in an atmosphere contaminated by aerosols. To investigate the artificial illumination of the sky over large regions on the basis of necessarily limited observations, one needs an expression for the zenith brightness produced by towns of known site and distance.
The exact derivation of such a law is exceedingly complex, involving the computation of the radiation transfer in an atmosphere with absorption, multiple scattering, and complicated physical and geometrical parameters. Notwithstanding these difficulties, it is possible to obtain a useful physical insight into the general form of this law by considering a very simplified model, consisting of a homogeneous atmosphere, in which vertical heights are small in relation to the horizontal distances between town and observatory, and which the scattering is limited to a cone of small angle whose axis lies in the direction of the incident beam. The limited scale height and optical thickness of the real atmosphere, and the forward-scattering characteristics of aerosols lend some plausibility to these simplifications. Keywords: Skyglow
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Cao, X., Hu, Y., Zhu, X., Shi, F., Zhuo, L., & Chen, J. (2019). A simple self-adjusting model for correcting the blooming effects in DMSP-OLS nighttime light images. Remote Sensing of Environment, 224, 401–411.
Abstract: Night-time light (NTL) data from the Defense Meteorological Satellite Program (DMSP) Operation Linescan System (OLS) provide important observations of human activities; however, DMSP-OLS NTL data suffer from problems such as saturation and blooming. This research developed a self-adjusting model (SEAM) to correct blooming effects in DMSP-OLS NTL data based on a spatial response function and without using any ancillary data. By assuming that the pixels adjacent to the background contain no lights (i.e., pseudo light pixels, PLPs), the blooming effect intensity, a parameter in the SEAM model, can be estimated by pixel-based regression using PLPs and their neighboring light sources. SEAM was applied to all of China, and its performance was assessed for twelve cities with different population sizes. The results show that SEAM can largely reduce the blooming effect in the original DMSP-OLS dataset and enhance its quality. The images after blooming effect correction have higher spatial similarity with Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS) images and higher spatial variability than the original DMSP-OLS data. We also found that the average effective blooming distance is approximately 3.5 km in China, which may be amplified if the city is surrounded by water surfaces, and that the blooming effect intensity is positively correlated to atmospheric quality. The effectiveness of the proposed model will improve the capacity of DMSP-OLS images for mapping the urban extent and modeling socioeconomic parameters.
Keywords: Remote Sensing
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Li, P., Zhang, H., Wang, X., Song, X., & Shibasaki, R. (2020). A spatial finer electric load estimation method based on night-light satellite image. Energy, 209, 118475.
Abstract: As a fundamental parameter of the electric grid, obtaining spatial electric load distribution is the premise and basis for numerous studies. As a public, world-wide, and spatialized dataset, NPP/VIIRS night-light satellite image has been long used for socio-economic information estimation, including electric consumption, while little attention has been given to the electric load estimation. Additionally, most of the previous studies were performed at a large spatial scale, which could not reflect the electric information inner a city. Therefore, this paper proposes a method to estimate electric load density at a township-level spatial scale based on NPP/VIIRS night-light satellite data. Firstly, we reveal the different fitting relationships between EC (Electric Consumption)-NLS (Night-Light Sum) and EL (Electric Load)-NLI (Night-Light Intensity). Then, we validated the spatial-scale’s influence on the estimation accuracy by experiment via generating a series of simulated datasets. After working out the super-resolution night-light image with the SRCNN (Super-Resolution Convolutional Neural Network) algorithm, we established a finer spatial estimation model. By taking a monthly data of Shanghai as a case study, we validate the model we established. The result shows that estimating electric load at township-level based on night-light satellite data is feasible, and the SRCNN algorithm can improve the performance.
Keywords: Remote Sensing
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Li, X., & Zhou, Y. (2017). A Stepwise Calibration of Global DMSP/OLS Stable Nighttime Light Data (1992–2013). Remote Sensing, 9(6), 637.
Abstract: The Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) stable nighttime light (NTL) data provide a wide range of potentials for studying global and regional dynamics, such as urban sprawl and electricity consumption. However, due to the lack of on-board calibration, it requires inter-annual calibration for these practical applications. In this study, we proposed a stepwise calibration approach to generate a temporally consistent NTL time series from 1992 to 2013. First, the temporal inconsistencies in the original NTL time series were identified. Then, a stepwise calibration scheme was developed to systematically improve the over- and under- estimation of NTL images derived from particular satellites and years, by making full use of the temporally neighbored image as a reference for calibration. After the stepwise calibration, the raw NTL series were improved with a temporally more consistent trend. Meanwhile, the magnitude of the global sum of NTL is maximally maintained in our results, as compared to the raw data, which outperforms previous conventional calibration approaches. The normalized difference index indicates that our approach can achieve a good agreement between two satellites in the same year. In addition, the analysis between the calibrated NTL time series and other socioeconomic indicators (e.g., gross domestic product and electricity consumption) confirms the good performance of the proposed stepwise calibration. The calibrated NTL time series can serve as useful inputs for NTL related dynamic studies, such as global urban extent change and energy consumption.
Keywords: Remote Sensing
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