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Zou, C. - Z., Zhou, L., Lin, L., Sun, N., Chen, Y., Flynn, L. E., et al. (2020). The Reprocessed Suomi NPP Satellite Observations. Remote Sensing, 12(18), 2891.
Abstract: The launch of the National Oceanic and Atmospheric Administration (NOAA)/ National Aeronautics and Space Administration (NASA) Suomi National Polar-orbiting Partnership (S-NPP) and its follow-on NOAA Joint Polar Satellite Systems (JPSS) satellites marks the beginning of a new era of operational satellite observations of the Earth and atmosphere for environmental applications with high spatial resolution and sampling rate. The S-NPP and JPSS are equipped with five instruments, each with advanced design in Earth sampling, including the Advanced Technology Microwave Sounder (ATMS), the Cross-track Infrared Sounder (CrIS), the Ozone Mapping and Profiler Suite (OMPS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the Clouds and the Earth’s Radiant Energy System (CERES). Among them, the ATMS is the new generation of microwave sounder measuring temperature profiles from the surface to the upper stratosphere and moisture profiles from the surface to the upper troposphere, while CrIS is the first of a series of advanced operational hyperspectral sounders providing more accurate atmospheric and moisture sounding observations with higher vertical resolution for weather and climate applications. The OMPS instrument measures solar backscattered ultraviolet to provide information on the concentrations of ozone in the Earth’s atmosphere, and VIIRS provides global observations of a variety of essential environmental variables over the land, atmosphere, cryosphere, and ocean with visible and infrared imagery. The CERES instrument measures the solar energy reflected by the Earth, the longwave radiative emission from the Earth, and the role of cloud processes in the Earth’s energy balance. Presently, observations from several instruments on S-NPP and JPSS-1 (re-named NOAA-20 after launch) provide near real-time monitoring of the environmental changes and improve weather forecasting by assimilation into numerical weather prediction models. Envisioning the need for consistencies in satellite retrievals, improving climate reanalyses, development of climate data records, and improving numerical weather forecasting, the NOAA/Center for Satellite Applications and Research (STAR) has been reprocessing the S-NPP observations for ATMS, CrIS, OMPS, and VIIRS through their life cycle. This article provides a summary of the instrument observing principles, data characteristics, reprocessing approaches, calibration algorithms, and validation results of the reprocessed sensor data records. The reprocessing generated consistent Level-1 sensor data records using unified and consistent calibration algorithms for each instrument that removed artificial jumps in data owing to operational changes, instrument anomalies, contaminations by anomaly views of the environment or spacecraft, and other causes. The reprocessed sensor data records were compared with and validated against other observations for a consistency check whenever such data were available. The reprocessed data will be archived in the NOAA data center with the same format as the operational data and technical support for data requests. Such a reprocessing is expected to improve the efficiency of the use of the S-NPP and JPSS satellite data and the accuracy of the observed essential environmental variables through either consistent satellite retrievals or use of the reprocessed data in numerical data assimilations.
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Tabaka, P. (2020). Pilot Measurement of Illuminance in the Context of Light Pollution Performed with an Unmanned Aerial Vehicle. Remote Sensing, 12(13), 2124.
Abstract: This article presents the methodology and results of pilot field illuminance measurements using an unmanned aerial vehicle (UAV). The main goal of the study was to quantify the luminous flux emitted in the upper hemisphere (toward the sky) based on obtained measurement data. The luminous flux emitted toward the sky is the source of undesirable light pollution. For test purposes, a height-adjustable mobile park lantern was constructed, at the top of which any type of luminaire can be installed. In the pilot measurements, two real opal sphere-type luminaires were considered. The lantern was situated in an open area located away from a large city agglomeration. To determine the unusable luminous flux, illuminance was measured, placing the necessary measuring equipment on board a UAV. The measurements were supplemented with the registration of illuminance on the ground upon which the lantern was installed. Based on these data, the useful luminous flux was calculated. The findings show that UAVs may be successfully used for the assessment of the influence of lighting on the light pollution effect.
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Yuan, X., Jia, L., Menenti, M., Zhou, J., & Chen, Q. (2019). Filtering the NPP-VIIRS Nighttime Light Data for Improved Detection of Settlements in Africa. Remote Sensing, 11(24), 3002.
Abstract: Observing and understanding changes in Africa is a hotspot in global ecological environmental research since the early 1970s. As possible causes of environmental degradation, frequent droughts and human activities attracted wide attention. Remote sensing of nighttime light provides an effective way to map human activities and assess their intensity. To identify settlements more effectively, this study focused on nighttime light in the northern Equatorial Africa and Sahel settlements to propose a new method, namely, the patches filtering method (PFM) to identify nighttime lights related to settlements from the National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) monthly nighttime light data by separating signal components induced by biomass burning, thereby generating a new annual image in 2016. The results show that PFM is useful for improving the quality of NPP-VIIRS monthly nighttime light data. Settlement lights were effectively separated from biomass burning lights, in addition to capturing the seasonality of biomass burning. We show that the new 2016 nighttime light image can very effectively identify even small settlements, notwithstanding their fragmentation and unstable power supply. We compared the image with earlier NPP-VIIRS annual nighttime light data from the National Oceanic and Atmospheric Administration (NOAA) National Center for Environmental Information (NCEI) for 2016 and the Sentinel-2 prototype Land Cover 20 m 2016 map of Africa released by the European Space Agency (ESA-S2-AFRICA-LC20). We found that the new annual nighttime light data performed best among the three datasets in capturing settlements, with a high recognition rate of 61.8%, and absolute superiority for settlements of 2.5 square kilometers or less. This shows that the method separates biomass burning signals very effectively, while retaining the relatively stable, although dim, lights of small settlements. The new 2016 annual image demonstrates good performance in identifying human settlements in sparsely populated areas toward a better understanding of human activities.
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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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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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